One shot profilometry using a composite fringe pattern

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数字图像处理冈萨雷斯第二版答案

数字图像处理冈萨雷斯第二版答案

数字图像处理冈萨雷斯第二版答案数字图像处理冈萨雷斯第二版答案【篇一:数字图像处理第三版 (冈萨雷斯,自己整理的2)】特数。

通常的传输是以一个开始比特,一个字节(8 比特)的信息和一个停止比特组成的包完成的。

基于这个概念回答以下问题:(b) 以750k 波特 [这是典型的电话dsl(数字用户线)连接的速度]传输要用多少时间?2.两个图像子集s1和s2图下图所示。

对于v={1},确定这两个子集是(a)4-邻接,(b)8-邻接,(c)m-邻接。

a) s1 和s2 不是4 连接,因为q 不在n4(p)集中。

(b) s1 和s2 是8 连接,因为q 在n8(p)集中。

(c) s1 和s2 是m 连接,因为q 在集合nd(p)中,且n4(p)∩ n4(q)没有v 值的像素3. 考虑如下所示的图像分割(a) 令v={0,1}并计算p 和q 间的4,8,m 通路的最短长度。

如果在这两点间不存在特殊通路,试解释原因。

(b) 对于v={1,2}重复上题。

解:(a) 当v={0,1}时,p 和q 之间不存在4 邻接路径,因为不同时存在从p 到q 像素的4 毗邻像素和具备v 的值,如图(a)p 不能到达q。

8 邻接最短路径如图(b),最短长度为4。

m邻接路径如图(b)虚线箭头所示,最短长度为5。

这两种最短长度路径在此例中均具有唯一性。

(b) 当v={1, 2}时,最短的4 邻接通路的一种情况如图(c)所示,其长度为6,另一种情况,其长度也为6;8 邻接通路的一种情况如图(d)实线箭头所示,其最短长度为4;m 邻接通路的一种情况如图(d)虚线箭头所示,其最短长度为6.或解: (1) 在v={0,1}时,p和q之间通路的d4距离为∞,d8距离为4,dm距离为5。

(2) 在v={1,2}时,p和q之间通路的d4距离为6,d8距离为4,dm距离为6。

4为什么一般情况下对离散图像的直方图均衡化并不能产生完全平坦的直方图?【因为同一个灰度值的各个象素没有理由变换到不同灰度级,所以数字图像的直方图均衡化的结果一般不能得到完全均匀分布的直方图,只是近似均匀的直方图。

红外图像生成尾焰的初步模型探究(IJIGSP-V3-N4-7)

红外图像生成尾焰的初步模型探究(IJIGSP-V3-N4-7)

I.J. Image, Graphics and Signal Processing, 2011, 4, 46-52Published Online June 2011 in MECS (/)A Preliminary Model of Infrared ImageGeneration for Exhaust PlumeFei Mei, Shiguo Chen, Yong Jiang,Air Force Engineering University/ College of Engineering, Xi’an, ChinaEmail: meifeifff@Jing CaiChangcheng Institute of metrology & Measurement, BeiJing, ChinaEmail: caijing @Abstract—Based on the irradiance calculation of all pixels on the focal plane array, a preliminary infrared imaging prediction model of exhaust plume that have considered the geometrical and the thermal resolution of the camera was developed to understanding the infrared characteristics of exhaust plume. In order to compute the irradiance incident on each pixel, the gas radiation transfer path in the plume for the instantaneous field of view corresponds to the pixel was solved by the simultaneous equation of a enclosure cylinder which covers the exhaust plume and the line of sight. Radiance of the transfer path was calculated by radiation transfer equation for nonscattering gas. The radiative properties of combustion needed in the equation was provided by employing Malkmus model with EM2C narrow band database(25cm-1). The pressure, species concentration along the path was determination by CFD analysis. The relative irradiance intensity of each pixel was converted to color in the display according to gray map coding and hot map coding. Infrared image of the exhaust plumes from a subsonic axisymmetric nozzle with different relative position of camera and the plume was predicted with the model. By changing the parameters, such as FOV and space resolution, the image of different imaging system can be predicted.Index Terms—Exhaust plume; Infrared imaging; Radiative transfer equation; colormapI.I NTRODUCTIONA. Background and MotivationInfrared (IR) guided missiles have been one of the most deadly threats to aircraft, they have been responsible for most of the military and civilian aircraft downed in the last several decades [1]. From Vietnam through Desert Storm, they leaded to more aircraft shutdowns than any other anti-aircraft weapons. They have truly fire and forget capability as they acquire and intercept aircraft by passively detecting IR-radiation (heat signatures) from them[2].Since its advent in the early 1950’s, The IR guided missile has advanced from un-cooled reticle seeker to multi-color array imaging seeker. The early heat seeking missile usually used un-cooled Lead Sulphide (PbS) detectors, have a peak sensitivity at < 3µm, operating in the near-IR 2-2.7µm atmospheric window waveband, which tends to limit such missiles to rear engagements as the detector can only discern the hot metal parts of the engine and the hotter water emission in the plume. Whereas, the next generation cooled detectors have higher sensitivity and can detect warm skin of an aircraft or the hot exhaust gas plume. These cooled detectors, used materials such as Indium Antimonide (InSb) for detection in the mid-IR 3-5µm atmospheric window. As they working at longer wavelengths , the cooler parts of the engine, hot parts of the airframe, and the cooler CO2 emissions in the exhaust plume can be detected, thus allowing wider angles of engagement.The latest missiles usually equipped with imaging seekers working in the mid-IR or the far-IR wave band. The major advantages of this type of system are increased lock-on range and robustness to countermeasures.As the infrared imaging missiles has been the escalating threat to the aircraft, Thus understanding the knowledge of accurate characteristic of target’s IR image is necessary both in evaluating the threat against civilian aircraft and designing aircraft less susceptible to heat seeking missiles. It is also helpful for designing more lethal seekers.B. The Aircraft Sources of RadiationThe typical radiation sources of jet aircraft are the hot metal tail-pipe, metallic fuselage and the exhaust gas plume [3].The total radiance of an object can have con-tributions due to emission, transmission and reflection (scattering).Fuselage and tailpipe, are generally solid metal and opaque in nature and usually considered as gray body. We may assume that the “opaque objects” emit thermal radiations and reflect what they receive from the environment. But the transmission part may be neglected. Their infrared image or signature can be evaluated by computation of the effective intensity of the projected meshed facets in the instaneous field of view (IFOV) of the IR camera. The effective intensity of a facet is the sum of self-emitted intensity, the specular reflected intensity of other facets, earth, or sky, and the diffuse reflected intensity of the earth or sky. The self-emitted intensity is determined by Plank Law with their skin’s emissivity and temperature. For a complex geometry, the difficulty to get the effective intensity for them areA Preliminary Model of Infrared Image Generation for Exhaust Plume 47modeling the reflective relation accurately between different facets of the skin, obscuration calculation to determine which facets can be seen in the FOV of the IR camera.On the other hand, the exhaust plume which created by the engine combustion processes and released into the atmosphere is non-opaque in nature. Thus the exhaust gas plume may be assumed to emit thermal radiations and transmit the energy through a non-opaque volume. But the third element of reflection (or scattering) may be neglected. The exhaust plume is a gas mixture of H2O, CO2, CO and O2.The IR radiation from the plume is emitted by the vibrational energy of the gaseous species, and thermal energy of solid and liquid species, its emissivity changes sharply with wavelength. The gas thickness, temperature field and gas composition along given path all affected the total radiation.C. Previous Work of Plume Radaition Calculation Decher [4] and Chu et al. [5] developed a simple descriptive model for plume IR radiation estimation i. Heragu et al. [6] and Heragu and Rao [7] gave a comprehensive scheme for the prediction of radiation from an engine exhaust plume, based on the combination of radiation from the surface and the gaseous plume. The Standardized Infrared Radiation Model (SIRRM) code developed under JANNAF (Joint Army Navy NASA Air Force) project, predicts IR radiation from missile and aircraft plumes [8]. The code also predicts the effect of carbon particles on IR emission characteristics of plume. Bakker et al.[9] gave a brief methodology for computing plume IR signatures from naval ship gas turbine engines, using NATO’s NPLUME program for exhaust field computations. Hypothetical band models for plume IR radiation modeling are classified into narrow-band and wide-band models. Wide-band models are used for obtaining total quantities, while narrow-band models are used for spectral information [6]. Ibgui and Hartmann [10] and Ibgui et al. [11] developed an optimized line-by-line FORTRAN code for the calculation of aircraft plume IR signature. The results obtained by the model were in good agreement with the measured laboratory simulation results.The exhaust gas plume of an aircraft is usually the dominant source of thermal radiations in the 3 to 5 micron band. The plume length is several times more than the aircraft length; therefore, plume radiation is visible from a much wider view angle. With the intent to develop the stealth aircraft design and evaluation technology, this paper reviewed the imaging mechanism of infrared camera and the method of gas radiation computation. Some efforts were done on developing a preliminary methodology for infrared imaging generation of exhaust plume.II.A NALYSIS OF I NFRARED I MAGINGA. Description of Infrared Imaging SystemThere are three basic types of method to get a two-dimensional image, raster scan, parallel scan, and staring. In a raster scan, two mirrors are mechanically steer the field of view of a single detector in both the vertical and horizontal directions. A parallel scan needs only one mirror to mechanically scan the scene in a single horizontal sweep using a row of detectors. Staring system are the most efficient and expedient method which characterized by a two dimensional array of detectors andare scanned electronically.Figure 1. Schematic Illustration of IR Imaging SystemThe matrixes of detectors, called pixels, are located at the focal plane of the camera (see fig 1).Detector size ranges from approximately 20×20μm to 60×60μm. Common sizes of detector array are 128×128, 256×256,320×240 and 640×512 pixels. Each of the detectors has an instantaneous FOV (IFOV) and receives radiation from their own IFOV. The radiation was converted to electrical signal by the detector, and an amplifier was used to boost the signal. The output of the amplifier is digitized in an analog-to-digital converter (ADC) and then quantized into digital counts. The digital count is determined by the amount of irradiance on the detector and was used to control one pixel’s color at the display according to a color map. Size of infrared image at the display is the same as the size of detectors array. This is also called detector spatial resolution.B. Basic RelationshipThe pixel of the focal plane array (FPA) has a size of ba×, focus of the optical system is, distance between the target and the lens isfR, the projection area''It is obviously that:2''2RbafbaIFOV×=×=Ω (1) The radiant flux received by one pixel is)(0R LA ττΩ=Φ (2)L represents the radiance of the pixel’s projected area in the target plane. A is the projected area. Ω is thesolid angle of front optics which is determined by the distance and the front optics’ diameter .R 0D 2204f D π=Ω0τ or )(R τ is the transmittance of optic system oratmospheric is respectively.Thus, the irradiance incident on the pixel is20204)(f R D L ab E ττπ=Φ= (3)From equation (3) it is obvious that irradiance incidenton the pixel is directly proportional to the radiance L of plume in its IFOV, as the other parameters are camera specific constants.III M ETHODOLOGYIn order to predict the infrared image for a specific camera, it is important to calculate the irradiance of all the pixels. According to equation (3), this problem is equal to calculating the radiance in the IFOV for all the pixels. The related prediction work to the exhaust plumeFigure 3. IR Imaging Simulation Process for Subsonic Exhaust Plume A tation should be done before any other w . CFD AnalysisThe fluid compu orks. It provides data of the temperature, pressure andspecies concentrations needed by the gas radiation calculation.For simplified, a commercial software FLUENT was employed to do this work. An implicit, coupled solver with standard k-ε turbulance model has been used to model the plume emanating from the nozzle.A cylinder was built to enclosure the exhaust plume, the cylinder was exactly the computation zone for computation fluid dynamics (CFD) analysis.B. Gas Radiation Transfer Path in the IFOVGas radiation transfer path referred to the path in the infrared active gas volume. The cylinder that enclosure the exhaust plume and used in CFD Analysis was considered as the infrared source. In order to calculate the radiance in the pixel’s IFOV, the gas radiation transfer path for each pixel should be found.To find the path, the concept “line of sight” was employed. It was a line that connects the center of optical system and center of the pixel.Suppose that an IR camera is at 90° aspect angle (The position are most commonly be adopted to measure the infrared signature of exhaust plume), as demonstrated in fig.4, the gas radiation transfer path is between A and B. These two points are the intersection points of the cylinder boundary and the line of sight. Thus, the path was determined by the position, diameter of the cylinder enclosure, optical focus and the pixel position at the FPA. Method to calculate the coordinates of A and B is discussed below.Presupposition: FOV of the infrared camera is βα×, size of detector array is n m ×, the detector is at the focal plane, so the center of detectors array was at coordinate ()f ,0,0Coordinate of the ()th j i × pixel’s center is()()()⎪⎩⎪⎨⎧⋅=⋅=⋅=s c n m z s b n m y s a n m x ,,,000 (4)The coefficient’s expression is listed below()()222112sin 22sin 12sin 22sin b a c j m b i m a −−=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡−⎟⎠⎞⎜⎝⎛+⎟⎠⎞⎜⎝⎛−=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡−⎟⎠⎞⎜⎝⎛+⎟⎠⎞⎜⎝⎛−=ββααLine of sight from this pixel center()()()n m z zn m y y n m x x ,,,000== (5)From equation (4) and equation (5), equation (5) can be written in this form⎪⎩⎪⎨⎧⋅=⋅=⋅=t c z t b y t a x (6) t is a formalize parameter.Mathematic equation of the cylinder enclosure is(7) ()222r L z x =++Put equation (6) in (7), we get()2222222r r L ct t c a=−+++If the Cylinder can filled the FOV of the camera, this equation definitely have two real roots .Put the roots in equation (6), we get and ().2,1t x ()A A A z y x ,,B B B z y ,,Figure 4. Gas Radiation Transfer Path for one Pixel C. Rad of isothermal co g the given path ha haust plume is selectively ab propagation co resent ana E onse range for an infrared camera is The irradiance was normalized byiance Calculation along the PathThe path was divided into a number lumns. The solution adopted to compute the radiative transfer through the plume is based on the band model depending on the temperature along theline of sight(LOS). Curtis-Godson approximation is usedfor the mean transmissivity through inhomogeneousgases. Pressure, temperature and the concentration ofgases (water vapor, carbon dioxide, and carbon monoxide)which emit most strongly in the infrared band along the path were provided by CFD analysis.The details to compute radiance alon s been discussed in section IV.D. Atmospheric AttenuationRadiant flux from the ex sorbed by several atmospheric gases and scattered away by small particles suspended in atmosphere (aerosols). The absorption and scattering are usually considered as the topic of extinction which causes attenuation in the amount of radiant flux passing through the atmosphere. The transmission of the atmosphere present in between the scene and the sensor is calculated by various numerical models that on the basis of the absorption, scattering and refractive-index fluctuations or turbulence, such as LOWTRAN [12], MODTRAN andFASCODE. These were developed by Air Force Geophysics Laboratory, USA. There are also some othermodels such as 4A/OP[13] initially developed at LMD(Laboratoire de Météorologie Dynamique).LOWTRAN 7 is a low-resolution mputer code for predicting atmospheric transmittance and background radiance from 0 to 50,000 cm -1 at a resolution of 20cm -1 which has been validated against field measurements. It is suitable for low altitudes(less than 40 km) and at moderate temperatures. The code is based on the LOWTRAN 6 [14] model. Multiple scattered radiation has been added to the model as well as new molecular band model parameters.The LOWTRAN-7 code has been used in p lysis for computing atmospheric transmissivity. . Color MappingThe dynamic resp 0in to 0max E , The irradiance put on the detector’s FPA min E to E , andE ≤m E varies from max 0maxmax min 0min E E E ≤≤ E ⎟⎟⎠⎞⎜⎜⎝⎛−E E min ×−=number color E E Round I _min max (8) is the levels of colors for thecolor map, we assigne o render the pixels. Th number color _ d it 256 here.Two color maps were employed t e coding from I to RGB are showed in fig5 and fig6 respectively. 1) GrayFig. 5 Gray ap Coding2) HotH s smoothly from black through shades of red,or M ot varieange, and yellow, to white (Fig6).Figure 6. Hot Map Coding IV. G AS R ADIANCE C ALCULATIONWhen th ca the vibrational mode. The number, width, and emissivee target was metal, the radiance in the IFOV n be calculated by Planck’s law with the emissivity. Unfortunately, that’s not true for gas. Because radiation emitted by gas is at discrete frequency, a characteristic ofpowers of the various bands, depend on the gas composition, pressure, temperature, and thickness of gas volume. The variation of the spectral radiation intensity along a path is described by the RTE, which is an integral-differential equation that describes the spectral radiation intensity along a path in a fixed direction through an absorbing, emitting, scattering medium.A. Equation of Radiation Transfer for Nonscattering Gas In the RTE, the attenuation of intensity due to the absorption and scattering, and the augmentation of intensity resulted from the emission and scattering to the path are included. Since it has few scattering media, the RTE in nonscattering media was exactly right for aircraft exhaust plume. When the distributions of pressure, temperature, and species concentration are given explicitly as functions of the path distance u, the equation of transfer reads ()()()'''0',,,,du u u u u L u L u u ωτωωωω∂∂=∫(9) For a given path which was divided into a number ofisothermal columns, the equation is usually transformedinto a numerical summation form(10) Where the transmittance is()()1,,1−==−−=∑m m m Nm m T L L ωωωωττ⎟⎠⎞⎜⎝⎛−=∫du mu m 0,exp ωωκτFigure 7. Sketch Map of Discrete PathTo obtain the radiance for a waveband, the spectral radiance should be integrated across frequency,(11)As absorption coefficient ωωωωd L L ∫=21ωκi venum s usually a very rapidlyvarying function of wa ber ω, a precisedetermination of requi uation 11) at a verylarge number of frequencies. Such detailed calculationsmay be impractical or undesirable. The gas absorption coefficient varies much more rapidly across the spectrum than other quantities, such as blackbody intensity, etc. It is, therefore, in principle possible to replace the actual absorption coefficient (and intensity) by smoothened values appropriately averaged over a narrow spectralrange.L res eval of (()()1,,1−==−−=∑m m m Nm m b b T L L ωωωωττ (12)m,ωτspectral 1231/12−⋅⋅−=cm sr cm W e C L T C b ωωωB. Band ModelBand models are hypothetical models of simplified mathematical structure which are introduced to provide fair representations of the properties of real spectra at reasonable computing cost [15]. In general, a model consists of a set of lines in a spectral interval with specified properties regarding the intensities, shape, number, and distribution of the lines. Band model consists of Wide Band Model (WBD) and Narrow Band Model (NBD).NBD average the absorption coefficient over a smaller spectral interval, with higher accuracy than WBD.A number of such "narrow band models" have been developed some 40-50 years ago. They were divided into regular band model (Elsasser Model) and statistical bandmodel according to their own assumptive spectral linesdistribution.We can find several statistical band models which all assume that the positions of the individual spectral linesoccur at random and that all lines have identical shape, differing only in strength. Such as Lines of equal strength, exponential line strength distribution (Goody Model), exponential tailed line strength distribution (Malkmus Model)[16]. The radiative properties ofcombustion were computed by Malkmus model which having a good agreement with Line by Line method with EM2C narrow band database(25cm -1) [17] here.Kcm k hc C cm W hc C ⋅==×==−43879.1//10191.12221221⎥⎥⎦⎤⎢⎢⎣⎡⎟⎟⎠⎞⎜⎜⎝⎛−+−=112exp γγτd xplk d (13) For Inhomogeneous gas columns ,the Curtis-Godsonapproximation is convenient.⎪⎩⎪⎨⎧⎟⎟⎠⎞⎜⎜⎝⎛=⎟⎠⎞⎜⎝⎛=∑∑∑∑i i i i i i i i i i eq i i i i i i i eq k l p x d k l p x d l p x k l p x k //γγ (14) V. R ESULT AND C ONCLUSION The infrared imaging simulation was conducted for the exhaust plumes of a subsonic axisymmetric nozzle. The diameter of the nozzle exit is 20 cm. The primary boundary parameters for CFD analysis are listed in table I.TABLE I BOUNDARY PARAMETERS FOR CFD Nozzle exit environmentTotal pressure(pa) 104510 96700 Static pressure(pa) 96700 96700 Total temperature(K) 590 296 is a smoothened transmittance over a narrowrange defined by the band model. referred to blackbody radianceωb L Mole fraction of CO 2 0.1 3.79×10-4 Mole fraction of H 2O 0.1 0.005The total FOV of the infrared camera was supposed 22×15°, image size is 320×240. The spectral interval forsimulation is 2000-5000cm -1. The model can predict the infrared image of different imaging system by changing the parameters, such as FOV and space resolution.The camera is placed at 90°aspect angle, 500 cm away from the plume centerline and 220 cm away from the exit. The predicted infrared image is05010015020025030050100150200a) Hot05010015020025030050100150200b) GrayFigure 8. IR Image for 500cm AwayChange the relatively position of the camera and plume, the image can be predicted properly well too. Fig 4 showed the predicted infrared image when the camera is placed at 90°aspect angle, 400 cm away from the plume centerline and 200 cm away from the exit.05010015020025030050100150200a) hotThe predicted image was showed reasonable, bu work of the author is also a preliminary study. This model can produce an ideal image which was predicted by the consideration of the geometrical and the thermal resolution of the camera. It needs some other work such ion of the interior effect of camera. The an al nozzleplume model for infrared analysis. J.Aircraft 1981; 18(12): 1038–1043.[6] Heragu SS, Rao KVL, Raghunandan BN. Generalizedction of radiative transfer frompotential core of a hot jet. J Thermophys Heat Transfer 1994;8(2):368–70.[8] Nelson HF, Tucker EO. Infrared emission from exhaust plumes. AIAA paper no. AIAA-1986-465. Reston, VA, USA: AIAA Inc.; 1986. p. 8.[9] Bakker E.J, Fair M.L., Schle en H.M.A. Modelling multispectral im and NPLUME plume signature calculations—I: model and data. J Quant Spectrosc R [11] Ibgui Let al. A d line-b for calculations, II:comparisons with mea-nt Spec adiat Transfer 4(4): [1ettle, E.P “Lowtran 7 c de:FGL-TR 0177, Hanscom , MA05010015020025030050100150200b) grayFig. 9 IR Image for 400cm Awayt the as the considerat experiment to validation which is planned to be done with auxiliary power unit of a commercial airplane soon is also needed.A CKNOWLEDGMENTThe authors are grateful to graduate student Bing Wen, Air Force Engineering University, for the systematic discussion of the computation fluid dynamic knowledge. The authors also thank XuDong, Li of Xi’an Institute of Applied Optics for his many beneficial suggestions of the infrared imaging. This work was supported in part by a grant from China Aeronautics Science Grant.R EFERENCES[1] Hughes D. and Wall R, “Missile Attack on DHL Jet KeepsSelf-Defense Issue Bubbling,” Aviation Week & Space Technology November 2003.[2] Understanding the infrared threat, Journal of ElectronicDefense, vol.22 no.2, February 1999.[3] S.P. Mahulikar, G.A. Rao, H.R. Sonawane, etc, “ Infraredsignature studies of airborne target,” Poceedings of the International Conference on Aerospace Science and Technology, India, 2008.[4] Decher R. Infrared emissions from turbofans with highaspect ratio nozzles. J Aircraft 1981;18(12):1025–31.[5] Chu CW, Der J, Wun W. Simple two-dimension model for infrared perception from an engine exhaust. J. Thermophys Heat Transfer 2002;16(1):68–76.[7] Heragu SS, Rao KVL. Predi the engineijp agery data with NIRATAMv3.1 v1.6. In: Proceedings of SPIE—The International Society for Optical Engineering, Targets and backgrounds: char-acterization and representation—V, vol. 3699. Bellingham, WA, USA: SPIE; 1999. p. 80–91.[10] Ibgui L, Hartmann JM. An optimized line by line code foradiat Tra ;75(3):273–95., Valentin A,MerienneMF, Jenouvrier A nsfer 2002, Lux JP,y-line code Le Doucen R, n optimize plume signature surements. J Qua tr R osc 2 7002;401–15.2] Kneizys, F.X., Sh user's Manual,”A .etc,-88-om co puter AFB 1988.[13]L. Chaumat, C. Standfuss, B. Tournier, R. Armante and N.A. Scott, “4A/OP Reference Documentation,” NOV-3049-NT-1178-v4.0, NOVELTIS, LMD/CNRS, CNES.2009.[14]Kneizys, F.X., Shettle, E.P.etc, “Atmospheric Trans-mittance /Radiance: Computer Code LOWTRAN 6,” Air Force Geophysics Laboratory, Report AFGL-TR-83-0187,Hanscom AFB, MA. 1983.[15]C.B. Ludwing, W. Malkmus, J.E. Reardon, J.A.L.Thomson, “Handbook of Infrared Radiation from Combustion,” NASA-SP-3080, 1973.[16]Malkmus, W., “Random band Lorentz with exponentialtailed S-1 line-intensity distribution function,” Journal of the Optical Society of America. vol.57, no.3, pp. 323-329 ,1967 .[17]Saufiani, A. and Taine, J, “High temperature gas radiativeproperty parameters of statistical narrow-band model for H2O, CO2 and CO, and correlated-K model for H2O and CO2,” Int. J. of Heat Mass Tr l. 40, no. pp. 987-991,1997ei Mei was born in Jinxian, Jiangxi Province,China on July 30study of aircraft exhaust plume flow field. His current research interest is infrared signature of aircraft.ansfer, vo4,Fth 1984. Mei is now a doctor candidate at Air Force Engineering University(AFEU), City of Xi’an, Shannxi Province. Mei was awarded the Degree of Bachelor of Engineering in aeronautics in AFEU on July 22th, 2006.Mei received the Degree of Master in aerospace propulsion theory and engineering in AFEU on April, 2009.He has been worked to build an aero-engine test and data acquisition system in propulsion system laboratory in AFEU from Oct.2006 to Mar.2007. Then he has devoted to simulation and experimentShiguo. Chen was born in Shannxi Province of China in 1980.Chen is now an instructor at AFEU, Xi’an, Shannxi.Chen was awarded the Degree of Master in Mechanical Engineering in National University of Defense Technology on December,2006.His research interest is infrared signature modeling and simulation of aircraft and infrared counter-measures.。

物理学专业英语

物理学专业英语

华中师范大学物理学院物理学专业英语仅供内部学习参考!2014一、课程的任务和教学目的通过学习《物理学专业英语》,学生将掌握物理学领域使用频率较高的专业词汇和表达方法,进而具备基本的阅读理解物理学专业文献的能力。

通过分析《物理学专业英语》课程教材中的范文,学生还将从英语角度理解物理学中个学科的研究内容和主要思想,提高学生的专业英语能力和了解物理学研究前沿的能力。

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要求译文通顺、准确和专业化。

要求译文通顺、准确和专业化。

二、课程内容课程内容包括以下章节:物理学、经典力学、热力学、电磁学、光学、原子物理、统计力学、量子力学和狭义相对论三、基本要求1.充分利用课内时间保证充足的阅读量(约1200~1500词/学时),要求正确理解原文。

2.泛读适量课外相关英文读物,要求基本理解原文主要内容。

3.掌握基本专业词汇(不少于200词)。

4.应具有流利阅读、翻译及赏析专业英语文献,并能简单地进行写作的能力。

四、参考书目录1 Physics 物理学 (1)Introduction to physics (1)Classical and modern physics (2)Research fields (4)V ocabulary (7)2 Classical mechanics 经典力学 (10)Introduction (10)Description of classical mechanics (10)Momentum and collisions (14)Angular momentum (15)V ocabulary (16)3 Thermodynamics 热力学 (18)Introduction (18)Laws of thermodynamics (21)System models (22)Thermodynamic processes (27)Scope of thermodynamics (29)V ocabulary (30)4 Electromagnetism 电磁学 (33)Introduction (33)Electrostatics (33)Magnetostatics (35)Electromagnetic induction (40)V ocabulary (43)5 Optics 光学 (45)Introduction (45)Geometrical optics (45)Physical optics (47)Polarization (50)V ocabulary (51)6 Atomic physics 原子物理 (52)Introduction (52)Electronic configuration (52)Excitation and ionization (56)V ocabulary (59)7 Statistical mechanics 统计力学 (60)Overview (60)Fundamentals (60)Statistical ensembles (63)V ocabulary (65)8 Quantum mechanics 量子力学 (67)Introduction (67)Mathematical formulations (68)Quantization (71)Wave-particle duality (72)Quantum entanglement (75)V ocabulary (77)9 Special relativity 狭义相对论 (79)Introduction (79)Relativity of simultaneity (80)Lorentz transformations (80)Time dilation and length contraction (81)Mass-energy equivalence (82)Relativistic energy-momentum relation (86)V ocabulary (89)正文标记说明:蓝色Arial字体(例如energy):已知的专业词汇蓝色Arial字体加下划线(例如electromagnetism):新学的专业词汇黑色Times New Roman字体加下划线(例如postulate):新学的普通词汇1 Physics 物理学1 Physics 物理学Introduction to physicsPhysics is a part of natural philosophy and a natural science that involves the study of matter and its motion through space and time, along with related concepts such as energy and force. More broadly, it is the general analysis of nature, conducted in order to understand how the universe behaves.Physics is one of the oldest academic disciplines, perhaps the oldest through its inclusion of astronomy. Over the last two millennia, physics was a part of natural philosophy along with chemistry, certain branches of mathematics, and biology, but during the Scientific Revolution in the 17th century, the natural sciences emerged as unique research programs in their own right. Physics intersects with many interdisciplinary areas of research, such as biophysics and quantum chemistry,and the boundaries of physics are not rigidly defined. New ideas in physics often explain the fundamental mechanisms of other sciences, while opening new avenues of research in areas such as mathematics and philosophy.Physics also makes significant contributions through advances in new technologies that arise from theoretical breakthroughs. For example, advances in the understanding of electromagnetism or nuclear physics led directly to the development of new products which have dramatically transformed modern-day society, such as television, computers, domestic appliances, and nuclear weapons; advances in thermodynamics led to the development of industrialization; and advances in mechanics inspired the development of calculus.Core theoriesThough physics deals with a wide variety of systems, certain theories are used by all physicists. Each of these theories were experimentally tested numerous times and found correct as an approximation of nature (within a certain domain of validity).For instance, the theory of classical mechanics accurately describes the motion of objects, provided they are much larger than atoms and moving at much less than the speed of light. These theories continue to be areas of active research, and a remarkable aspect of classical mechanics known as chaos was discovered in the 20th century, three centuries after the original formulation of classical mechanics by Isaac Newton (1642–1727) 【艾萨克·牛顿】.University PhysicsThese central theories are important tools for research into more specialized topics, and any physicist, regardless of his or her specialization, is expected to be literate in them. These include classical mechanics, quantum mechanics, thermodynamics and statistical mechanics, electromagnetism, and special relativity.Classical and modern physicsClassical mechanicsClassical physics includes the traditional branches and topics that were recognized and well-developed before the beginning of the 20th century—classical mechanics, acoustics, optics, thermodynamics, and electromagnetism.Classical mechanics is concerned with bodies acted on by forces and bodies in motion and may be divided into statics (study of the forces on a body or bodies at rest), kinematics (study of motion without regard to its causes), and dynamics (study of motion and the forces that affect it); mechanics may also be divided into solid mechanics and fluid mechanics (known together as continuum mechanics), the latter including such branches as hydrostatics, hydrodynamics, aerodynamics, and pneumatics.Acoustics is the study of how sound is produced, controlled, transmitted and received. Important modern branches of acoustics include ultrasonics, the study of sound waves of very high frequency beyond the range of human hearing; bioacoustics the physics of animal calls and hearing, and electroacoustics, the manipulation of audible sound waves using electronics.Optics, the study of light, is concerned not only with visible light but also with infrared and ultraviolet radiation, which exhibit all of the phenomena of visible light except visibility, e.g., reflection, refraction, interference, diffraction, dispersion, and polarization of light.Heat is a form of energy, the internal energy possessed by the particles of which a substance is composed; thermodynamics deals with the relationships between heat and other forms of energy.Electricity and magnetism have been studied as a single branch of physics since the intimate connection between them was discovered in the early 19th century; an electric current gives rise to a magnetic field and a changing magnetic field induces an electric current. Electrostatics deals with electric charges at rest, electrodynamics with moving charges, and magnetostatics with magnetic poles at rest.Modern PhysicsClassical physics is generally concerned with matter and energy on the normal scale of1 Physics 物理学observation, while much of modern physics is concerned with the behavior of matter and energy under extreme conditions or on the very large or very small scale.For example, atomic and nuclear physics studies matter on the smallest scale at which chemical elements can be identified.The physics of elementary particles is on an even smaller scale, as it is concerned with the most basic units of matter; this branch of physics is also known as high-energy physics because of the extremely high energies necessary to produce many types of particles in large particle accelerators. On this scale, ordinary, commonsense notions of space, time, matter, and energy are no longer valid.The two chief theories of modern physics present a different picture of the concepts of space, time, and matter from that presented by classical physics.Quantum theory is concerned with the discrete, rather than continuous, nature of many phenomena at the atomic and subatomic level, and with the complementary aspects of particles and waves in the description of such phenomena.The theory of relativity is concerned with the description of phenomena that take place in a frame of reference that is in motion with respect to an observer; the special theory of relativity is concerned with relative uniform motion in a straight line and the general theory of relativity with accelerated motion and its connection with gravitation.Both quantum theory and the theory of relativity find applications in all areas of modern physics.Difference between classical and modern physicsWhile physics aims to discover universal laws, its theories lie in explicit domains of applicability. Loosely speaking, the laws of classical physics accurately describe systems whose important length scales are greater than the atomic scale and whose motions are much slower than the speed of light. Outside of this domain, observations do not match their predictions.Albert Einstein【阿尔伯特·爱因斯坦】contributed the framework of special relativity, which replaced notions of absolute time and space with space-time and allowed an accurate description of systems whose components have speeds approaching the speed of light.Max Planck【普朗克】, Erwin Schrödinger【薛定谔】, and others introduced quantum mechanics, a probabilistic notion of particles and interactions that allowed an accurate description of atomic and subatomic scales.Later, quantum field theory unified quantum mechanics and special relativity.General relativity allowed for a dynamical, curved space-time, with which highly massiveUniversity Physicssystems and the large-scale structure of the universe can be well-described. General relativity has not yet been unified with the other fundamental descriptions; several candidate theories of quantum gravity are being developed.Research fieldsContemporary research in physics can be broadly divided into condensed matter physics; atomic, molecular, and optical physics; particle physics; astrophysics; geophysics and biophysics. Some physics departments also support research in Physics education.Since the 20th century, the individual fields of physics have become increasingly specialized, and today most physicists work in a single field for their entire careers. "Universalists" such as Albert Einstein (1879–1955) and Lev Landau (1908–1968)【列夫·朗道】, who worked in multiple fields of physics, are now very rare.Condensed matter physicsCondensed matter physics is the field of physics that deals with the macroscopic physical properties of matter. In particular, it is concerned with the "condensed" phases that appear whenever the number of particles in a system is extremely large and the interactions between them are strong.The most familiar examples of condensed phases are solids and liquids, which arise from the bonding by way of the electromagnetic force between atoms. More exotic condensed phases include the super-fluid and the Bose–Einstein condensate found in certain atomic systems at very low temperature, the superconducting phase exhibited by conduction electrons in certain materials,and the ferromagnetic and antiferromagnetic phases of spins on atomic lattices.Condensed matter physics is by far the largest field of contemporary physics.Historically, condensed matter physics grew out of solid-state physics, which is now considered one of its main subfields. The term condensed matter physics was apparently coined by Philip Anderson when he renamed his research group—previously solid-state theory—in 1967. In 1978, the Division of Solid State Physics of the American Physical Society was renamed as the Division of Condensed Matter Physics.Condensed matter physics has a large overlap with chemistry, materials science, nanotechnology and engineering.Atomic, molecular and optical physicsAtomic, molecular, and optical physics (AMO) is the study of matter–matter and light–matter interactions on the scale of single atoms and molecules.1 Physics 物理学The three areas are grouped together because of their interrelationships, the similarity of methods used, and the commonality of the energy scales that are relevant. All three areas include both classical, semi-classical and quantum treatments; they can treat their subject from a microscopic view (in contrast to a macroscopic view).Atomic physics studies the electron shells of atoms. Current research focuses on activities in quantum control, cooling and trapping of atoms and ions, low-temperature collision dynamics and the effects of electron correlation on structure and dynamics. Atomic physics is influenced by the nucleus (see, e.g., hyperfine splitting), but intra-nuclear phenomena such as fission and fusion are considered part of high-energy physics.Molecular physics focuses on multi-atomic structures and their internal and external interactions with matter and light.Optical physics is distinct from optics in that it tends to focus not on the control of classical light fields by macroscopic objects, but on the fundamental properties of optical fields and their interactions with matter in the microscopic realm.High-energy physics (particle physics) and nuclear physicsParticle physics is the study of the elementary constituents of matter and energy, and the interactions between them.In addition, particle physicists design and develop the high energy accelerators,detectors, and computer programs necessary for this research. The field is also called "high-energy physics" because many elementary particles do not occur naturally, but are created only during high-energy collisions of other particles.Currently, the interactions of elementary particles and fields are described by the Standard Model.●The model accounts for the 12 known particles of matter (quarks and leptons) thatinteract via the strong, weak, and electromagnetic fundamental forces.●Dynamics are described in terms of matter particles exchanging gauge bosons (gluons,W and Z bosons, and photons, respectively).●The Standard Model also predicts a particle known as the Higgs boson. In July 2012CERN, the European laboratory for particle physics, announced the detection of a particle consistent with the Higgs boson.Nuclear Physics is the field of physics that studies the constituents and interactions of atomic nuclei. The most commonly known applications of nuclear physics are nuclear power generation and nuclear weapons technology, but the research has provided application in many fields, including those in nuclear medicine and magnetic resonance imaging, ion implantation in materials engineering, and radiocarbon dating in geology and archaeology.University PhysicsAstrophysics and Physical CosmologyAstrophysics and astronomy are the application of the theories and methods of physics to the study of stellar structure, stellar evolution, the origin of the solar system, and related problems of cosmology. Because astrophysics is a broad subject, astrophysicists typically apply many disciplines of physics, including mechanics, electromagnetism, statistical mechanics, thermodynamics, quantum mechanics, relativity, nuclear and particle physics, and atomic and molecular physics.The discovery by Karl Jansky in 1931 that radio signals were emitted by celestial bodies initiated the science of radio astronomy. Most recently, the frontiers of astronomy have been expanded by space exploration. Perturbations and interference from the earth's atmosphere make space-based observations necessary for infrared, ultraviolet, gamma-ray, and X-ray astronomy.Physical cosmology is the study of the formation and evolution of the universe on its largest scales. Albert Einstein's theory of relativity plays a central role in all modern cosmological theories. In the early 20th century, Hubble's discovery that the universe was expanding, as shown by the Hubble diagram, prompted rival explanations known as the steady state universe and the Big Bang.The Big Bang was confirmed by the success of Big Bang nucleo-synthesis and the discovery of the cosmic microwave background in 1964. The Big Bang model rests on two theoretical pillars: Albert Einstein's general relativity and the cosmological principle (On a sufficiently large scale, the properties of the Universe are the same for all observers). Cosmologists have recently established the ΛCDM model (the standard model of Big Bang cosmology) of the evolution of the universe, which includes cosmic inflation, dark energy and dark matter.Current research frontiersIn condensed matter physics, an important unsolved theoretical problem is that of high-temperature superconductivity. Many condensed matter experiments are aiming to fabricate workable spintronics and quantum computers.In particle physics, the first pieces of experimental evidence for physics beyond the Standard Model have begun to appear. Foremost among these are indications that neutrinos have non-zero mass. These experimental results appear to have solved the long-standing solar neutrino problem, and the physics of massive neutrinos remains an area of active theoretical and experimental research. Particle accelerators have begun probing energy scales in the TeV range, in which experimentalists are hoping to find evidence for the super-symmetric particles, after discovery of the Higgs boson.Theoretical attempts to unify quantum mechanics and general relativity into a single theory1 Physics 物理学of quantum gravity, a program ongoing for over half a century, have not yet been decisively resolved. The current leading candidates are M-theory, superstring theory and loop quantum gravity.Many astronomical and cosmological phenomena have yet to be satisfactorily explained, including the existence of ultra-high energy cosmic rays, the baryon asymmetry, the acceleration of the universe and the anomalous rotation rates of galaxies.Although much progress has been made in high-energy, quantum, and astronomical physics, many everyday phenomena involving complexity, chaos, or turbulence are still poorly understood. Complex problems that seem like they could be solved by a clever application of dynamics and mechanics remain unsolved; examples include the formation of sand-piles, nodes in trickling water, the shape of water droplets, mechanisms of surface tension catastrophes, and self-sorting in shaken heterogeneous collections.These complex phenomena have received growing attention since the 1970s for several reasons, including the availability of modern mathematical methods and computers, which enabled complex systems to be modeled in new ways. Complex physics has become part of increasingly interdisciplinary research, as exemplified by the study of turbulence in aerodynamics and the observation of pattern formation in biological systems.Vocabulary★natural science 自然科学academic disciplines 学科astronomy 天文学in their own right 凭他们本身的实力intersects相交,交叉interdisciplinary交叉学科的,跨学科的★quantum 量子的theoretical breakthroughs 理论突破★electromagnetism 电磁学dramatically显著地★thermodynamics热力学★calculus微积分validity★classical mechanics 经典力学chaos 混沌literate 学者★quantum mechanics量子力学★thermodynamics and statistical mechanics热力学与统计物理★special relativity狭义相对论is concerned with 关注,讨论,考虑acoustics 声学★optics 光学statics静力学at rest 静息kinematics运动学★dynamics动力学ultrasonics超声学manipulation 操作,处理,使用University Physicsinfrared红外ultraviolet紫外radiation辐射reflection 反射refraction 折射★interference 干涉★diffraction 衍射dispersion散射★polarization 极化,偏振internal energy 内能Electricity电性Magnetism 磁性intimate 亲密的induces 诱导,感应scale尺度★elementary particles基本粒子★high-energy physics 高能物理particle accelerators 粒子加速器valid 有效的,正当的★discrete离散的continuous 连续的complementary 互补的★frame of reference 参照系★the special theory of relativity 狭义相对论★general theory of relativity 广义相对论gravitation 重力,万有引力explicit 详细的,清楚的★quantum field theory 量子场论★condensed matter physics凝聚态物理astrophysics天体物理geophysics地球物理Universalist博学多才者★Macroscopic宏观Exotic奇异的★Superconducting 超导Ferromagnetic铁磁质Antiferromagnetic 反铁磁质★Spin自旋Lattice 晶格,点阵,网格★Society社会,学会★microscopic微观的hyperfine splitting超精细分裂fission分裂,裂变fusion熔合,聚变constituents成分,组分accelerators加速器detectors 检测器★quarks夸克lepton 轻子gauge bosons规范玻色子gluons胶子★Higgs boson希格斯玻色子CERN欧洲核子研究中心★Magnetic Resonance Imaging磁共振成像,核磁共振ion implantation 离子注入radiocarbon dating放射性碳年代测定法geology地质学archaeology考古学stellar 恒星cosmology宇宙论celestial bodies 天体Hubble diagram 哈勃图Rival竞争的★Big Bang大爆炸nucleo-synthesis核聚合,核合成pillar支柱cosmological principle宇宙学原理ΛCDM modelΛ-冷暗物质模型cosmic inflation宇宙膨胀1 Physics 物理学fabricate制造,建造spintronics自旋电子元件,自旋电子学★neutrinos 中微子superstring 超弦baryon重子turbulence湍流,扰动,骚动catastrophes突变,灾变,灾难heterogeneous collections异质性集合pattern formation模式形成University Physics2 Classical mechanics 经典力学IntroductionIn physics, classical mechanics is one of the two major sub-fields of mechanics, which is concerned with the set of physical laws describing the motion of bodies under the action of a system of forces. The study of the motion of bodies is an ancient one, making classical mechanics one of the oldest and largest subjects in science, engineering and technology.Classical mechanics describes the motion of macroscopic objects, from projectiles to parts of machinery, as well as astronomical objects, such as spacecraft, planets, stars, and galaxies. Besides this, many specializations within the subject deal with gases, liquids, solids, and other specific sub-topics.Classical mechanics provides extremely accurate results as long as the domain of study is restricted to large objects and the speeds involved do not approach the speed of light. When the objects being dealt with become sufficiently small, it becomes necessary to introduce the other major sub-field of mechanics, quantum mechanics, which reconciles the macroscopic laws of physics with the atomic nature of matter and handles the wave–particle duality of atoms and molecules. In the case of high velocity objects approaching the speed of light, classical mechanics is enhanced by special relativity. General relativity unifies special relativity with Newton's law of universal gravitation, allowing physicists to handle gravitation at a deeper level.The initial stage in the development of classical mechanics is often referred to as Newtonian mechanics, and is associated with the physical concepts employed by and the mathematical methods invented by Newton himself, in parallel with Leibniz【莱布尼兹】, and others.Later, more abstract and general methods were developed, leading to reformulations of classical mechanics known as Lagrangian mechanics and Hamiltonian mechanics. These advances were largely made in the 18th and 19th centuries, and they extend substantially beyond Newton's work, particularly through their use of analytical mechanics. Ultimately, the mathematics developed for these were central to the creation of quantum mechanics.Description of classical mechanicsThe following introduces the basic concepts of classical mechanics. For simplicity, it often2 Classical mechanics 经典力学models real-world objects as point particles, objects with negligible size. The motion of a point particle is characterized by a small number of parameters: its position, mass, and the forces applied to it.In reality, the kind of objects that classical mechanics can describe always have a non-zero size. (The physics of very small particles, such as the electron, is more accurately described by quantum mechanics). Objects with non-zero size have more complicated behavior than hypothetical point particles, because of the additional degrees of freedom—for example, a baseball can spin while it is moving. However, the results for point particles can be used to study such objects by treating them as composite objects, made up of a large number of interacting point particles. The center of mass of a composite object behaves like a point particle.Classical mechanics uses common-sense notions of how matter and forces exist and interact. It assumes that matter and energy have definite, knowable attributes such as where an object is in space and its speed. It also assumes that objects may be directly influenced only by their immediate surroundings, known as the principle of locality.In quantum mechanics objects may have unknowable position or velocity, or instantaneously interact with other objects at a distance.Position and its derivativesThe position of a point particle is defined with respect to an arbitrary fixed reference point, O, in space, usually accompanied by a coordinate system, with the reference point located at the origin of the coordinate system. It is defined as the vector r from O to the particle.In general, the point particle need not be stationary relative to O, so r is a function of t, the time elapsed since an arbitrary initial time.In pre-Einstein relativity (known as Galilean relativity), time is considered an absolute, i.e., the time interval between any given pair of events is the same for all observers. In addition to relying on absolute time, classical mechanics assumes Euclidean geometry for the structure of space.Velocity and speedThe velocity, or the rate of change of position with time, is defined as the derivative of the position with respect to time. In classical mechanics, velocities are directly additive and subtractive as vector quantities; they must be dealt with using vector analysis.When both objects are moving in the same direction, the difference can be given in terms of speed only by ignoring direction.University PhysicsAccelerationThe acceleration , or rate of change of velocity, is the derivative of the velocity with respect to time (the second derivative of the position with respect to time).Acceleration can arise from a change with time of the magnitude of the velocity or of the direction of the velocity or both . If only the magnitude v of the velocity decreases, this is sometimes referred to as deceleration , but generally any change in the velocity with time, including deceleration, is simply referred to as acceleration.Inertial frames of referenceWhile the position and velocity and acceleration of a particle can be referred to any observer in any state of motion, classical mechanics assumes the existence of a special family of reference frames in terms of which the mechanical laws of nature take a comparatively simple form. These special reference frames are called inertial frames .An inertial frame is such that when an object without any force interactions (an idealized situation) is viewed from it, it appears either to be at rest or in a state of uniform motion in a straight line. This is the fundamental definition of an inertial frame. They are characterized by the requirement that all forces entering the observer's physical laws originate in identifiable sources (charges, gravitational bodies, and so forth).A non-inertial reference frame is one accelerating with respect to an inertial one, and in such a non-inertial frame a particle is subject to acceleration by fictitious forces that enter the equations of motion solely as a result of its accelerated motion, and do not originate in identifiable sources. These fictitious forces are in addition to the real forces recognized in an inertial frame.A key concept of inertial frames is the method for identifying them. For practical purposes, reference frames that are un-accelerated with respect to the distant stars are regarded as good approximations to inertial frames.Forces; Newton's second lawNewton was the first to mathematically express the relationship between force and momentum . Some physicists interpret Newton's second law of motion as a definition of force and mass, while others consider it a fundamental postulate, a law of nature. Either interpretation has the same mathematical consequences, historically known as "Newton's Second Law":a m t v m t p F ===d )(d d dThe quantity m v is called the (canonical ) momentum . The net force on a particle is thus equal to rate of change of momentum of the particle with time.So long as the force acting on a particle is known, Newton's second law is sufficient to。

Statistical Theory of Passive Location Systems

Statistical Theory of Passive Location Systems

TRANSMITTER
\Id
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i
BEARING LINE
of1
axl x=xo
Of,
Oxn x=X0
Fig. 2. Bearing lines from aircraft positions.
(7)
three dimensions and possibly other parameters such as the time of emission of the radiation. A set of N measurements ri, i = 1, 2, ..., N, is collected at various positions. In the absence of random measurement errors, ri is equal to a known functionf.(x). In the presence of additive errors, (1) i = 1, 2, ..., N. ri = fi(x) + ni,
Oxl
afN
X=XO
afN
:X0
These N equations can be written as a single equation for N-dimensional column vectors: r = f(x) + n. (2) approximation. Combining (5) and (6) gives The measurement error n is assumed to be a multivariate Q(x) = (r -GX)TN- 1(rl - Gx) random vector with an N x N positive-definite covariance matrix where

Motion Estimation

Motion Estimation

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2 Introduction to Digital Video 2.1 Definitions and terminology . . . . . 2.1.1 Images . . . . . . . . . . . . . 2.1.2 Video sequences . . . . . . . 2.1.3 Video interlacing . . . . . . . 2.1.4 Contrast . . . . . . . . . . . . 2.1.5 Spatial frequency . . . . . . . 2.2 Digital image processing . . . . . . . 2.2.1 Fourier transform . . . . . . . 2.2.2 Convolution . . . . . . . . . . 2.2.3 Digital filters . . . . . . . . . 2.2.4 Correlation . . . . . . . . . . 2.3 MPEG-2 video compression . . . . . 2.3.1 The discrete cosine transform 2.3.2 Quantization . . . . . . . . . 2.3.3 Motion compensation . . . . 2.3.4 Efficient representation . . .
ii
c Philips Electronics N.V. 2001
no classification

数电外教——PulseWaveforms

数电外教——PulseWaveforms

Figure 8.1.11
Logic symbol for the 74LS122 retriggerable one-shot
An output pulse of 5 μs duration is to be generated by a 74LS122 one-shot. Using a capacitor of 10,000 pF, determine the value of the external resistance required.
Figure 8.4.1
Internal functional diagram of a 555 timer
NOTE: pin numbers are in parenthesis
Figure 8.4.4
The 555 timer connected as a one-shot
Tw = 1.1 R1 C1
A certain application requires a one-shot with a pulse width of approximately 100 ms. Using a 74121, show the connections and component values.
A sequential timing circuit for the 74121 nonretriggerable one-shot
The effect of using a Schmitt trigger (B) instead of a comparator (A).
Schmitt Trigger
Schmitt trigger action
The Schmitt trigger action uses a comparator to produce stable levelcrossing switches in contrast to the action of a straight reference comparison.

纹理物体缺陷的视觉检测算法研究--优秀毕业论文

纹理物体缺陷的视觉检测算法研究--优秀毕业论文

摘 要
在竞争激烈的工业自动化生产过程中,机器视觉对产品质量的把关起着举足 轻重的作用,机器视觉在缺陷检测技术方面的应用也逐渐普遍起来。与常规的检 测技术相比,自动化的视觉检测系统更加经济、快捷、高效与 安全。纹理物体在 工业生产中广泛存在,像用于半导体装配和封装底板和发光二极管,现代 化电子 系统中的印制电路板,以及纺织行业中的布匹和织物等都可认为是含有纹理特征 的物体。本论文主要致力于纹理物体的缺陷检测技术研究,为纹理物体的自动化 检测提供高效而可靠的检测算法。 纹理是描述图像内容的重要特征,纹理分析也已经被成功的应用与纹理分割 和纹理分类当中。本研究提出了一种基于纹理分析技术和参考比较方式的缺陷检 测算法。这种算法能容忍物体变形引起的图像配准误差,对纹理的影响也具有鲁 棒性。本算法旨在为检测出的缺陷区域提供丰富而重要的物理意义,如缺陷区域 的大小、形状、亮度对比度及空间分布等。同时,在参考图像可行的情况下,本 算法可用于同质纹理物体和非同质纹理物体的检测,对非纹理物体 的检测也可取 得不错的效果。 在整个检测过程中,我们采用了可调控金字塔的纹理分析和重构技术。与传 统的小波纹理分析技术不同,我们在小波域中加入处理物体变形和纹理影响的容 忍度控制算法,来实现容忍物体变形和对纹理影响鲁棒的目的。最后可调控金字 塔的重构保证了缺陷区域物理意义恢复的准确性。实验阶段,我们检测了一系列 具有实际应用价值的图像。实验结果表明 本文提出的纹理物体缺陷检测算法具有 高效性和易于实现性。 关键字: 缺陷检测;纹理;物体变形;可调控金字塔;重构
Keywords: defect detection, texture, object distortion, steerable pyramid, reconstruction
II

数码相机英语试题答案

数码相机英语试题答案

数码相机英语试题答案一、选择题1. The term "megapixel" refers to:A. The camera's lens quality.B. The camera's resolution or image quality.C. The camera's zoom capability.D. The camera's storage capacity.答案:B2. Which of the following is not a component of a digital camera?A. LensB. ShutterC. MirrorD. Image sensor答案:C3. What is the function of Image Stabilization (IS) indigital cameras?A. It enhances the camera's processing speed.B. It reduces the appearance of noise in low light conditions.C. It minimizes the blur caused by camera movement.D. It improves the quality of zoomed-in images.答案:C4. What does the term "aperture" refer to in photography?A. The degree of lightness or darkness in a photograph.B. The size of the camera's lens opening.C. The distance between the camera and the subject.D. The sharpness of the image.答案:B5. Which of the following is a benefit of using a digital camera over a film camera?A. Instant image review and deletion.B. Higher image quality.C. Longer battery life.D. Lower cost per image.答案:A二、填空题1. The ________ is the part of the digital camera that captures light and converts it into digital signals.答案:image sensor2. The ________ setting on a digital camera allows you to take several pictures in quick succession.答案:burst mode3. Digital cameras often provide a ________ feature thatautomatically adjusts the camera settings based on the typeof scene or subject.答案:scene recognition4. A higher ________ value on a digital camera indicates a faster shutter speed, which is useful for capturing fast-moving subjects.答案:shutter speed5. In digital photography, ________ refers to the process of adjusting the colors in an image to make them appear more natural or aesthetically pleasing.答案:white balancing三、简答题1. 请简述数码相机的工作原理。

Spin-Flip Noise in a Multi-Terminal Spin-Valve

Spin-Flip Noise in a Multi-Terminal Spin-Valve

a r X i v :c o n d -m a t /0307070v 1 [c o n d -m a t .m e s -h a l l ] 3 J u l 2003Spin-Flip Noise in a Multi-Terminal Spin-ValveW.BelzigDepartement f¨u r Physik und Astronomie,Klingelbergstr.82,4056Basel,SwitzerlandM.ZareyanMax-Planck-Institut f¨u r Physik komplexer Systeme,N¨o thnitzer Str.38,01187Dresden,Germany andInstitute for Advanced Studies in Basic Sciences,45195-159,Zanjan,Iran(Dated:February 2,2008)We study shot noise and cross correlations in a four terminal spin-valve geometry using a Boltzmann-Langevin approach.The Fano factor (shot noise to current ratio)depends on the mag-netic configuration of the leads and the spin-flip processes in the normal metal.In a four-terminal geometry,spin-flip processes are particular prominent in the cross correlations between terminals with opposite magnetization.The discovery of the giant magneto resistance effect in magnetic multi-layers has boosted the interest in spin-dependent transport in the last years (for a review see e.g.[1]).In combination with quantum transport ef-fects the field is termed spintronics [2].In recent ex-periments spin-dependent transport in metallic multi-terminal structures has also been demonstrated [3].One important aspect of quantum transport is the generation of shot noise in mesoscopic conductors [4,5].Probabilis-tic scattering in combination with Fermionic statistics leads to a suppression of the shot noise from its classical value [6,7,8].A particular interesting phenomenon are the nonlocal correlations between currents in different terminals of a multi-terminal structure.For a non-interacting fermionic system the cross correlations are generally negative [9].In a one-channel beam splitter the negative sign was con-firmed experimentally [10,11].If the electrons are in-jected from a superconductor,the cross correlations may change sign and become positive [12,13,14,15].In these studies,however,the spin was only implicitly present due to the singlet pairing in the superconductor.Current noise in ferromagnetic -normal metal struc-tures,in which the spin degree of freedom plays an essen-tial role,has so far attracted only little attention.Non-collinear two-terminal spin valves have been studied in [16]and it was shown that the noise depends on the rela-tive magnetization angle in a different way than the con-ductance.Thus,the noise reveals additional information on the internal spin-dynamics.Noise has been exploited to study the properties of localized spins by means of electron spin resonance[17].Quantum entanglement of itinerant spins can also be probed through noise mea-surements [18].In this work we propose a new instrument for the study of spin-dependent transport:the use of cross correlations in a multi-terminal structure.The basic idea is to use a four-terminal structure like sketched in Fig.1.An elec-tron current flows from the left terminals to the right ter-minals and is passing a scattering region.In the absence(b)FIG.1:Four-terminal setup to measure spin-flip correlations.(a)a possible experimental realization with a normal diffusive metal strip,on which four ferromagnetic strips are deposited (of different width to facilitate different magnetization ori-entations).The total length of the diffusive metal under-neath the ferromagnetic contacts should be less that the spin-diffusion length in the normal metal.(b)theoretical model of the device.Spin ↑(↓)current is flowing in the upper(lower)branch.Spin-flip scattering connects the two spin-branches and is modelled as resistor with also induces additional flutu-ation.of spin-flip scattering the currents of spin-up electrons and spin-down electron are independent,and the cross correlations between any of the two currents in different spin channels vanish.However,spin-flip scattering can convert spin-up into spin-down electrons and vice versa,and induces correlations between the different spin cur-rents.This has two effects.First,the equilibration of the spin-populations leads to a weakened magneto-resistance effect.Second,the current cross correlations between the differently polarized terminals contain now information on the spin-flip processes taking place in the scattering region.To this end we will study a four-terminal structure,in which the currents can be measured in all four terminals independently.The layout is shown in Fig.1,in which the various currents are defined.For simplicity,we as-sume that all four terminals are coupled by tunnel junc-tions to one node.The node is assumed to have negligible resistance,but provides spin-flip scattering.The ferro-magnetic character of the terminals is modelled by spin-dependent conductances of the tunnel junctions.The two2 left(right)terminals have chemical potential V1(V2).Inmost of thefinal results we will assume zero temperature,but this is not crucial.Furthermore,we will assume fullypolarized tunnel contacts,characterized by g aσ,wherea=L,R denotes left and right terminals,andσ=↑,↓stands for the spin directions(in equations we take↑=+1and↓=−1).The currentfluctuations in our structure can be de-scribed by aBoltzmann-Langevin formalism[19].The time-dependent currents at energy E through contact aσare written asI aσ(t,E)=g aσ[f aσ(E)−f cσ(E)−δf cσ(t,E)]+δI aσ(t,E).(1) The averaged occupations of the terminals are denoted by f aσ(E),the one of the central node by f cσ(E).The occupation of the central node isfluctuating asδf cσ(t,E). The Langevin sourceδI aσ(t,E)inducesfluctuations due to the probabilistic scattering in contact aσ.We assume elastic transport in the following,so all equations are understood to be at the same energy E.Since we assume tunnel contacts,thefluctuations are Poissonian and given by[4]δI aσ(t)δI a′σ′(t′) =(2)g aσδσσ′δaa′δ(t−t′)[f aσ+f cσ−2f aσf cσ].The brackets ··· denote averaging over thefluctua-tions.The conservation of the total current at all times t leads to the conservation law[20]a,σI aσ(t)=0(3)The equation presented so far describe the transport of two unconnected circuits for spin-up and spin-down elec-trons,i.e.the spin current is conserved in addition to the total current.Spin-flip scattering on the dot leads to a non-conserved spin current,which we write asa,σσI aσ(t)=2g sf[f c↑+δf c↑(t)−f c↓−δf c↓(t)]+2δI sf(t).(4) Here we introduced a phenomenological spin-flip conduc-tance g sf,which connects the two spin occupations on the node.Correspondingly,we added an additional Langevin sourceδI sf(t),which is related to the probabilistic spin scattering and has a correlation function[21]δI sf(t)δI sf(t′) =g sfδ(t−t′)(5)×[f c↑(1−f c↓)+f c↓(1−f c↑)]. Eqs.(1)-(5)form a complete set and determine the aver-age currents and the current noise of our system.Solving for the average occupations of the node we obtainf cσ=[(g−σg Lσ+g sf g L)f L(6)+(g−σg Rσ+g sf g R)f R]/Z.Here we introduced gσ=g Lσ+g Rσ,g L(R)=g L(R)↑+ g L(R)↓,and Z=g↑g↓+(g↑+g↓)g sf.The average currents are thenI Lσ=g LσZ[(g Rσg−σ+(g−σ+g Rσ)g sf)δI Lσ−g Lσ(g−σ+g sf)δI Rσ+σg Lσg−σδI sf−g Lσg sf(δI L−σ+δI R−σ)].(9) Now we can calculate all possible current correlators in the left terminals,defined byS Lσσ′= ∞−∞dτ ∆I Lσ(t+τ)∆I Lσ′(t) .(10) The total current noise in the left terminals isS L=S L↑↑+S L↓↓+2S L↑↓.(11) Of course the same quantities can be calculated for the right terminals.From particle conservation it follows that S L=S R,but in the presence of spin-flip scat-tering the individual correlators can differ.For conve-nience we also define a Fano factor F=S L/e|I|,where I=I L↑+I L↓is the total current.We will discuss general results below,butfirst concen-trate on simple limiting cases.We will restrict ourselves to zero temperature from now on.Assuming a bias volt-age V is applied between the right and the left terminals, the occupations are f L=1and f R=0in the energy range0≤E≤eV.The full current noise can be written asS L=|eV|Z(g↓g L↑−g↑g L↓)2(g sf g R+gσg R−σ)×(g sf g L+g−σg Lσ)].For the cross correlations at the left side wefindS L↑↓=−g sf|eV|g L↑g L↓Z(g−σg Lσ+g sf g L)(gσg R−σ+g sf g R) .3It can be shown,that thecrosscorrelations are alwaysnegative,as it should be[9].In the case of a two-terminal geometry two different configurations are possible.Either both terminals have the same spin-direction,or the opposite configuration.In thefirst case we can take g↓=0.There is no effect of the spin-flip scattering and we obtain for the Fano factor F=(g2L+g2R)/(g L+g R)2,in agreement with the known results[4].If the two terminals have different spin orien-tations(’antiferromagnetic’configuration),the situation is completely different,since transport is allowed only by spin-flip scattering.We take g L↓=g R↑=0.The Fano factor isF=1−2g sf g L g R(g L+g R)(g L+g sf)(g R+g sf)|eV|=−2g sfg L↑g L↓g↑g↓ .(15)Thefirst term is also present in a spin-symmetric sit-uation,and is caused by the additional current path opened by the spin-flip scattering.The second term in the Eq.(15)depends on the amount of spin accumulation on the central metal,i.e.is proportional to(f c↑−f c↓)2. Wefirst consider the symmetric’ferromagnetic’config-uration g L↑=g R↑=g↑/2and g L↓=g R↓=g↓/2.Note, that also g L=g R follows in this configuration.The Fano factor of the full current noise is F=1/2,i.e.we recover the usual suppression of the shot noise characteristic for a symmetric double barrier structure.There is no spin accumulation in this configuration,and,consequently,no effect of the spin-flip scattering on the Fano factor.The cross correlations in the’ferromagnetic’configuration areS L↑↓=−g sfg↑g↓+g sf(g↑+g↓)|eV|.(16)Thus,in the limit of strong spin-flip scattering the cross correlations become independent on g sf.Next we consider the symmetric’antiferromagnetic’configuration g L↑=g R↓=g1and g L↓=g R↑=g2.The012gsf/(gL+gR)-0.1-0.05SLud/eIL0.50.60.70.8SL/eIL012gsf/(gL+gR)0.40.60.81IL/(gL+gR)eV(pL,pR)(pL=pR)(0.4,-0.4)(0.8,-0.8)(0,0)(0.4,0.4)(0.4,-0.4)(0.8,-0.8)(0.8,0.8)(p,p)(0.4,-0.4)(0.8,-0.8)FIG.2:Cross correlations,Fano factor and average currents (symmetric case).We assume symmetric contacts g L=g R and parametrize the magnetic properties with the spin po-larization p L(R)=(g L(R)↑−g L(R)↓)/(g L(R)↑+g L(R)↓).The upper part shows the Fano factor of the currentfluctuations in the left contacts for different polarization configurations. Inset:average current.The lower part shows the spin-flip in-duced cross correlations between↑-and↓-currents in the left terminals.Fano factor isF=1(g+2g sf)2 2g2sf g+2g sf.(17) The second term in the brackets in Eq.(17)can be either positive or negative.In the latter case F drops below the symmetric double barrier value of1/2.For the cross correlations we obtainS L↑↓2g2(g+2g sf)4 g(g+2g sf)3+(g1−g2)2 3g2+6gg sf+4g sf2 ,(18) where we introduced the abbreviation g=g1+g2.Again, the second term in the brackets in Eq.(18)is proportional to the spin accumulation of the island,which enhances the spin-flip induced cross correlations.The transport properties for symmetric junctions are shown in Fig.2.For equal polarizations of both sides there is no effect of spin-flip scattering on the Fano fac-tor and average currents.However,the cross correlations do depend on the polarizations even in this case.For small g sf the cross correlations rapidly increase in mag-nitude.For g sf≫g L+g R the cross correlations become independent of the relative polarizations.Their absolute value,however,depends strongly on the absolute value of the polarization.For antiparallel polarizations the Fano factor differs strongly from its value1/2in the unpolar-ized case.With increasing spin-flip scattering rate,the4g sf /(g L +g R )S L u d /e I LS L /e I LFIG.3:Cross correlations,Fano factor and average currents (asymmetric case).We take here g L =4g R .The definition of the polarizations are taken over from Fig.2.Fano factor goes from a value larger than 1/2through a minimum,which is always lower that 1/2.Let us now turn to the general case of asymmetric junc-tions.The noise correlations are plotted in Fig.3.We have taken g L =4g R and various configurations of the polarizations 0.3and 0.7.The Fano factors and the av-erage currents are now different for all parameter combi-nations.However,the variations of the Fano factors are small,i.e.they are alway close to the unpolarized case.This is different for the cross correlations.Even for weak spin-flip scattering they change dramatically if some of the polarizations are reversed.In conclusion we have suggested to use shot noise and cross correlations as a tool to study spin-flip scattering in mesoscopic spin-valves [23].In a two-terminal device with antiferromagnetically oriented electrodes spin-flip scattering leads to a transition from full Poissonian shot noise (Fano factor F =1)to a double-barrier behaviour (F =1/2)with increasing spin-flip rate.We have pro-posed to measure the spin correlations induced by spin-flips in a four-terminal device.If the spin-flip scattering rate is small,the cross-correlation beween currents in ter-minal with opposite spin-orientation gives direct access to the spin-flip scattering rate.Presently,we have as-sumed fully polarized terminals,but a generalization to arbitrary polarizations is straightforward.We acknowledge discussion with C.Bruder.W.B.was financially supported by the Swiss NSF and the NCCR Nanoscience.M.Z.thanks the University of Basel for hospitality.During preparation of this manuscript,a work appeared,in which a similar model was studied[24].[1]M.A.M.Gijs and G.E.W.Bauer,Adv.Phys.46,285(1997).[2]G. A.Prinz,Phys.Today 282,1660-1663(1998);S.Datta and B.B.Das,Appl.Phys.Lett.56,665(1990);J.M.Kikkawa, D. D.Awschalom,Nature 397,139(1999);R.Fiederling et al.,Nature 402,787(2000);Y.Ohno et al.,Nature 402,790(2000);I.Malajovich et al.,Phys.Rev.Lett.84,1015(2000).[3]F.J.Jedema et al.,Nature 410,345(2000);Nature 416,713(2002).[4]Ya.M.Blanter and M.B¨u ttiker,Phys.Rep.336,1(2000).[5]Quantum Noise in Mesoscopic Physics ,ed.by Yu.V.Nazarov,Yu.V.(Kluwer,Dordrecht,2003).[6]V.A.Khlus,Sov.Phys.JETP 66,1243(1987).[7]G.B.Lesovik,JETP Lett.49,592(1989).[8]M.B¨u ttiker,Phys.Rev.Lett.65,2901(1990).[9]M.B¨u ttiker,Phys.Rev.B 46,12485(1992).[10]M.Henny et al.,Science 284,296(1999);S.Oberholzeret al.,Physica (Amsterdam)6E ,314(2000).[11]W.D.Oliver et al.,Science 284,299(1999).[12]T.Martin,Phys.Lett.A 220,137(1996);M.P.Anantram and S.Datta,Phys.Rev.B 53,16390(1996);G.B.Lesovik,T.Martin,and J.Torre´s ,Phys.Rev.B 60,11935(1999).J.Torres and T.Martin,Eur.Phys.J.B 12,319(1999).[13]J.B¨o rlin,W.Belzig,and C.Bruder Phys.Rev.Lett.88,197001(2002).[14]P.Samuelsson and M.B¨u ttiker,Phys.Rev.Lett.89,046601(2002).[15]F.Taddei and R.Fazio,Phys.Rev.B 65,134522(2002).[16]Y.Tserkovnyak and A.Brataas,Phys.Rev.B 64,214402(2001).[17]H.-A.Engel and D.Loss,Phys.Rev.B 65,195321(2002).[18]D.Loss and E.V.Sukhorukov,Phys.Rev.Lett.84,1035(2000);G.Burkard, D.Loss,and E.V.Sukho-rukov,Phys.Rev.B 61,R16303(2000);J.C.Egues,G.Burkard,and D.Loss,Phys.Rev.Lett.89,176401(2002).[19]K.E.Nagaev,Phys.Lett.A 169,103(1992);Phys.Rev.B 57,4628(1998).[20]In our calculation we neglect all charging effects,i.e.we assume that g aσ≫e 2/h .We are also only interested here in current fluctuations on time-scales longer than all RC -times.[21]M.Zareyan and W.Belzig (unpublished).[22]A similar effect was recently reported in E.G.Mishchenko,cond-mat/0305003(unpublished).[23]The four-terminal structure suggested in Fig.1(a)is par-ticularly suitable.Without applying an external mag-netic field the magnetic configuration can be switched by changing the potentials of the different terminals.[24]D.Sanch´e z et al.,cond-mat/0306132(unpublished).。

KODAK DX4900数字相机说明说明书

KODAK DX4900数字相机说明说明书

Shoot a picture, touch the button, and share your pictures with your world.T he EasyShare SystemGet incredible image quality Introducing the first print-optimized 4.0MP point-and-shoot digital camera designed to be one-touch simple. With the DX4900’s 4.0MP ,you’ll get stunning prints from 4"x 6"to 20"x 30".And thanks to KODAK color science, you’ll get superb color consistency and more versatility for better pictures no matter where or what you’re shooting. The KODAK all-glass, high-quality aspheric lens with 6X zoom lets you zero in on your subjects with crisp detail. And with our exclusive Advanced Digital Zoomtechnology, you’ll get great 4"x 6"and 5"x 7" prints.Take creative controlThe DX4900 has automatic and manual settings that cover everything from color, focus,sharpness, and burst mode to ISO,white balance, and shutter speed. Its six resolution settings mean you can pick the right size for your needs,from e-mailing to enlargements. 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螺杆压缩机外文文献翻译、中英文翻译、外文翻译

螺杆压缩机外文文献翻译、中英文翻译、外文翻译

螺杆压缩机外文文献翻译、中英文翻译、外文翻译英文原文Screw CompressorsN. Stosic I. Smith A. KovacevicScrew CompressorsMathematical Modellingand Performance CalculationWith 99 FiguresABCProf. Nikola StosicProf. Ian K. SmithDr. Ahmed KovacevicCity UniversitySchool of Engineering and Mathematical SciencesNorthampton SquareLondonEC1V 0HBU.K.e-mail:n.stosic@/doc/d6433edf534de518964bcf 84b9d528ea81c72f87.htmli.k.smith@/doc/d6433edf534de51896 4bcf84b9d528ea81c72f87.htmla.kovacevic@/doc/d6433edf534de51 8964bcf84b9d528ea81c72f87.htmlLibrary of Congress Control Number: 2004117305ISBN-10 3-540-24275-9 Springer Berlin Heidelberg New York ISBN-13 978-3-540-24275-8 Springer Berlin Heidelberg New YorkThis work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the GermanCopyright Law.Springer is a part of Springer Science+Business Media/doc/d6433edf534de518964bcf84b9d 528ea81c72f87.html_c Springer-Verlag Berlin Heidelberg 2005Printed in The NetherlandsThe use of general descriptive names, registered names, trademarks, etc. in this publication does not imply,even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.Typesetting: by the authors and TechBooks using a Springer LATEX macro packageCover design: medio, BerlinPrinted on acid-free paper SPIN: 11306856 62/3141/jl 5 4 3 2 1 0PrefaceAlthough the principles of operation of helical screw machines, as compressors or expanders, have been well known for more than 100 years, it is only during the past 30 years thatthese machines have become widely used. The main reasons for the long period before they were adopted were their relatively poor efficiency and the high cost of manufacturing their rotors. Two main developments led to a solution to these difficulties. The first of these was the introduction of the asymmetric rotor profile in 1973. This reduced the blowhole area, which was the main source of internal leakage by approximately 90%, and thereby raised the thermodynamic efficiency of these machines, to roughly the same level as that of traditional reciprocating compressors. The second was the introduction of precise thread milling machine tools at approximately the same time. This made it possible to manufacture items of complex shape, such as the rotors, both accurately and cheaply.From then on, as a result of their ever improving efficiencies, high reliability and compact form, screw compressors have taken an increasing share of the compressor market, especially in the fields of compressed air production, and refrigeration and air conditioning, and today, a substantial proportion of compressors manufactured for industry are of this type.Despite, the now wide usage of screw compressors and the publication of many scientific papers on their development, only a handful of textbooks have been published to date, which give a rigorous exposition of the principles of their operation and none of these are in English.The publication of this volume coincides with the tenth anniversary of the establishment of the Centre for Positive Displacement Compressor Technology at City University, London, where much, if not all, of the material it contains was developed. Its aim is to give an up to date summary of the state of the art. Its availability in a single volume should then help engineers inindustry to replace design procedures based on the simple assumptions of the compression of a fixed mass of ideal gas, by more up to date methods. These are based on computer models, which simulate real compression and expansion processes more reliably, by allowing for leakage, inlet and outlet flow and other losses, VI Preface and the assumption of real fluid properties in the working process. Also, methods are given for developing rotor profiles, based on the mathematical theory of gearing, rather than empirical curve fitting. In addition, some description is included of procedures for the three dimensional modelling of heat and fluid flow through these machines and how interaction between the rotors and the casing produces performance changes, which hitherto could not be calculated. It is shown that only a relatively small number of input parameters is required to describe both the geometry and performance of screw compressors. This makes it easy to control the design process so that modifications can be cross referenced through design software programs, thus saving both computer resources and design time, when compared with traditional design procedures.All the analytical procedures described, have been tried and proven on machines currently in industrial production and have led to improvements in performance and reductions in size and cost, which were hardly considered possible ten years ago. Moreover, in all cases where these were applied, the improved accuracy of the analytical models has led to close agreement between predicted and measured performance which greatly reduced development time and cost. Additionally, the better understanding of the principles of operation brought about by such studies has led to an extension of the areas of application of screw compressors and expanders.It is hoped that this work will stimulate further interest in an area, where, though much progress has been made, significant advances are still possible.London, Nikola StosicFebruary 2005 Ian SmithAhmed KovacevicNotationA Area of passage cross section, oil droplet total surfacea Speed of soundC Rotor centre distance, specific heat capacity, turbulence model constantsd Oil droplet Sauter mean diametere Internal energyf Body forceh Specific enthalpy h = h(θ), convective heat transfer coefficient betweenoil and gasi Unit vectorI Unit tensork Conductivity, kinetic energy of turbulence, time constant m Massm˙ Inlet or exit mass flow rate m˙ = m˙ (θ)p Rotor lead, pressure in the working chamber p = p(θ)P Production of kinetic energy of turbulenceq Source term˙Q Heat transfer rate between the fluid and the compressor surroundin gs˙Q= ˙Q(θ)r Rotor radiuss Distance between the pole and rotor contact points, control volume surfacet TimeT Torque, Temperatureu Displacement of solidU Internal energyW Work outputv Velocityw Fluid velocityV Local volume of the compressor working chamber V = V (θ)˙VVolume flowVIII Notationx Rotor coordinate, dryness fraction, spatial coordinatey Rotor coordinatez Axial coordinateGreek Lettersα Temperature dilatation coefficientΓ Diffusion coefficientε Dissipation of kinetic energy of turbulenceηi Adiabatic efficiencyηt Isothermal efficiencyηv Volumetric efficiencySpecific variableφ Variableλ Lame coefficientμ Viscosityρ Densityσ Prand tl numberθ Rotor angle of rotationζ Compound, local and point resistance coefficientω Angular speed of rotationPrefixesd differentialΔ IncrementSubscriptseff Effectiveg Gasin Inflowf Saturated liquidg Saturated vapourind Indicatorl Leakageoil Oilout Outflowp Previous step in iterative calculations SolidT Turbulentw pitch circle1 main rotor, upstream condition2 gate rotor, downstream conditionContents1Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………………………. . . . . . . . . . . . . . . 1 1.1 Basic Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. .. . . . . . . . . 4 1.2 Types of Screw Compressors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . ….. . . . . . . .7 1.2.1 The Oil Injected Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . …... . .71.2.2 The Oil Free Machine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . ….... .7 1.3 Screw Machine Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .8 1.4 Screw Compressor Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .101.5RecentDevelopments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.5.1RotorProfiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . 13 1.5.2CompressorDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2ScrewCompressorGeometry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.1 The Envelope Method as a Basis for the Profiling of Screw CompressorRotors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………………………….. . . . . ….. . . . . . . . 19 2.2 Screw Compressor Rotor Profile s . . . . . . . . . . . . . . . . . . . . …. . . . . . . . . . . . . . . . . . . ….. . . 20 2.3 Rotor ProfileCalculation . . . . . . . . . . . . . . . . . . . . . . . . . . . …………………………. . . . . .23 2.4 Review of Most Popular Rotor Profiles . . . . . . . . . . . . . . . ………………………….. . . . . . 23 2.4.1 Demonstrator Rotor Profile (“N” Rotor Generated) . . ………………………………….. . 24 2.4.2 SKBK Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………... . . . . . . . . .26 2.4.3 Fu Sheng Profile . . . . . . . . . . . . . . . . . . . . . . . . . ………………………………. . . . . . . . .27 2.4.4 “Hyper”Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………………………………. . .27 2.4.5 “Sigma” Profile . . . . . . . . . . . . . . . . . . . . . . .. . . . . . ………………………………. . . . . .28 2.4.6 “Cyclon” Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………………………………. . . . . .28 2.4.7 Symmetric Prof ile . . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………… . . . . .29 2.4.8 SRM “A” Profile . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………… . . . . . . .30 2.4.9 SRM “D” Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………… . . . . . .31 2.4.10 SRM “G” Profile . . . . . . . . . . . . . . . .. . . . . . . . …………………………….. . . . . . . . . .32 2.4.11 City “N” Rack Generated Rotor Profile . . . . . . . . . . . ………………………………… . . 32 2.4.12 Characteristics of “N” Profile . . . . . . . . . . . . . . . . . . . ………………………………. . . . 34 2.4.13 Blower Rot or Profile . . . . . . . . . . . . . . . . . . . . …………………………….. . . . . . . . . . . 39 X Contents2.5 Identification of Rotor Positionin Compressor Bearings . . . . . . . . . . . . . . . . . . . . . . . . . . …………………………….. . . . . . . .40 2.6 Tools for Rotor Manufacture . . . . . . . . . . . . . . . . . . . . . . …………………………. . . . . . . .45 2.6.1 Hobbing Tools . . . . . . . . . . . . . . . . . . . . . . . . . . ………….…..………………. . . . . . . . . .45 2.6.2 Milling and Grinding Tools . . . . . . . . . . . . . . . . . . . ……………………………….... . . . . 482.6.3 Quantification of ManufacturingImperfections . . . . . ……………………………….... . . 483 Calculation of Screw Compressor Performance . . . . . . . . . . ………………………………. . . 49 3.1 One Dimensional Mathematical Model . . . . . . . . . . . . . . …………………………... . . . . . .49 3.1.1 Conservation Equationsfor Control Volume and Auxiliary Relationships . . . . ............................................... . . 50 3.1.2 Suction and Discharge Ports . . . . . . . . . . . . . . . . . . . ....................................... . . . . 53 3.1.3 Gas Leakages . . . . . . . . . . . . . . . . . . . . . . . . . . .................................... . . . . . . . . . .54 3.1.4 Oil or Liquid Injection . . . . . . . . . . . ...................................... . . . . . . . . . . . . . . . . . 55 3.1.5 Computation of Fluid Properties . . . . . . . . ........................................ . . . . . . . . . . . 57 3.1.6 Solution Procedure for Compressor Thermodynamics . (58)3.2 Compressor Integral Parameters . . . . . . . . . . . . . . . . . . . ………………………….. . . . . . . . 59 3.3 Pressure Forces Actingon Screw Compressor Rotors . . . . . . . . . . . . . . . . . . . . . . ................................... . . . . . . . 61 3.3.1 Calculation of Pressure Radial Forces and Torque . . . . .. (61)3.3.2 Rotor Bending Deflections . . . . . . . . . . . . . . . . . . . . . ……………………………….. . . . 64 3.4 Optimisation of the Screw Compressor Rotor Profile,Compressor Design and Operating Parameters . . . . . . . . . . ……………………………….. . . . 65 3.4.1 OptimisationRationale . . . . . . . . . . . . . . . . . . . . . . . . ……………………………….. . . . 65 3.4.2 Minimisation Method Usedin Screw CompressorOptimisation . . . . . . . . . . . ……………………………………… . . . . . . 67 3.5 Three Dimensional CFD and Structure Analysisof a Screw Compressor . . . . . . . . . . . . . . . . . . . . . . . . . …………………………….. . . . . . . . .71 4 Principles of Screw Compressor Design. . . . . . . . . . . …………………………… . . . . . . . . 77 4.1 Clearance Management. . . . . . . . . . . . . . . . . . . . . . . . ………….….………… . . . . . . . . . .78 4.1.1 Load Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………….………………….. . . .79 4.1.2 Compressor Size and Scale . . . . . . . . . . . . . . ………………………………. . . . . . . . . . . 80 4.1.3 RotorConfiguration . . . . . . . . . . . . . . . . . . . . . . . ……………………………... . . . . . . .82 4.2 Calculation Example:5-6-128mm Oil-Flooded Air Compressor . . . . . . . . . . . . . . . ……………………………... . . . 824.2.1 Experimental Verification of the Model . . . . . . . . . . . ………………………………. . . . 845 Examples of Modern Screw Compressor Designs . . . . . . . ……………………………… . . . 89 5.1 Design of an Oil-Free Screw CompressorBased on 3-5 “N” Rotors . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………. . . . . . . 90 5.2 The Design of Familyof Oil-Flooded Screw Compressors Basedon 4-5 “N” Rotors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . …………………………… . . . . . . .93 Contents XI.5.3 Design of Replacement Rotorsfor Oil-FloodedCompressors . . . . . . . . . . . . . . . . . . . . . . . . . . . ................................. . .96 5.4 Design of Refrigeration Compressors . . . . . . . . . . . . . . . .............................. . . . . . . 100 5.4.1 Optimisation of Screw Compressors for Refrigeration . . . (102)5.4.2 Use of New Rotor Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . (103)5.4.3 Rotor Retrofits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ……………………………. . . 103 5.4.4 Motor Cooling Through the Superfeed Port in Semihermetic Compressors . . . . . . . . . . . . . . . . . . . …………………………………… . . . 103 5.4.5 Multirotor Screw Compressors . . . . . . . . . . . . . . . . . …………………………….... . . . . 104 5.5 Multifunctional Screw Machines . . . . . . . . . . . . . . . . . . ……………………….. . . . . . . . . 108 5.5.1 Simultaneous Compression and Expansionon One Pair of Rotors . . . . . . . . . . . . . . . . . . . . . . . . . . ............................................ . 108 5.5.2 Design Characteristics of Multifunctional Screw Rotors .. (109)5.5.3 Balancing Forces on Compressor-Expander Rotors . …………………..……………. . . 1105.5.4 Examples of Multifunctional Screw Machines . . . . . . . . (111)6Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . …………………… . . . . . . . . . 117A Envelope Method of Gearin g . . . . . . . . . . . . . . . . . . . . . . . . ………………………… . . . . . 119B Reynolds TransportTheorem. . . . . . . . . . . . . . . . . . . . . . . …………………………. . . . . . . 123C Estimation of Working Fluid Propertie s . . . . . . . . . . . . . . . …………………………….. . . . 127 Re ferences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ………………… . . . . . . . . . . 133中文译文螺杆压缩机N.斯托西奇史密斯先生A科瓦切维奇螺杆压缩机计算的数学模型和性能尼古拉教授斯托西奇教授伊恩史密斯博士艾哈迈德科瓦切维奇工程科学和数学北安普敦广场伦敦城市大学英国电子邮件:n.stosic@/doc/d6433edf534de518964bcf 84b9d528ea81c72f87.htmli.k.smith@/doc/d6433edf534de51896 4bcf84b9d528ea81c72f87.htmla.kovacevic@/doc/d6433edf534de51 8964bcf84b9d528ea81c72f87.html国会图书馆控制号:2004117305isbn-10 3-540-24275-9 纽约施普林格柏林海德堡isbn-13 978-3-540-24275-8 纽约施普林格柏林海德堡这项工作是受版权保护,我们保留所有权利。

Single Molecule localization microscopy for superresolution

Single Molecule localization microscopy for superresolution

Home Search Collections Journals About Contact us My IOPscienceSingle molecule localization microscopy for superresolutionThis content has been downloaded from IOPscience. Please scroll down to see the full text.2013 J. Opt. 15 094001(/2040-8986/15/9/094001)View the table of contents for this issue, or go to the journal homepage for moreDownload details:IP Address: 219.217.234.32This content was downloaded on 22/10/2015 at 03:18Please note that terms and conditions apply.IOP P UBLISHING J OURNAL OF O PTICS J.Opt.15(2013)094001(15pp)doi:10.1088/2040-8978/15/9/094001Single molecule localization microscopy for superresolutionJohn R Allen1,Stephen T Ross2and Michael W Davidson11National High Magnetic Field Laboratory and Department of Biological Science,The Florida StateUniversity,1800East Paul Dirac Drive,Tallahassee,FL32304,USA2Nikon Instruments,Incorporated,1300Walt Whitman Road,Melville,NY11747,USAE-mail:davidson@Received8July2013,accepted for publication30July2013Published10September2013Online at /JOpt/15/094001AbstractIn recent years there has been a rash of developments in light microscopies circumventingtraditional resolution limits associated with the diffraction of light occurring between thesample and the detector.Collectively,these techniques are referred to as‘superresolution’microscopies.One major family of superresolution techniques,variably referred to as PALM,FPALM and STORM,uses temporal control of the excited state offluorophores tosequentially identify single non-overlapping emitters in time and space.Conventional imagesof single point emitters arefitted to sub-diffraction-limited areas,and a composite image isreconstructed from position data collected over many thousands of individual imaging frames.This paper provides a brief overview of superresolution microscopy,followed by a detaileddiscussion of STORM,including practical guidelines for sample preparation designed to helpto make the technique more accessible to the non-specialist.Keywords:STORM,PALM,FPALM,diffraction,superresolution,nanoscopy,fluorescenceS Online supplementary data available from /JOpt/15/094001/mmedia(Somefigures may appear in colour only in the online journal)1.IntroductionFor decadesfluorescence microscopy has served a vital role in biology and the biomedical sciences,occupying a unique niche between electron microscopy and large-scale low-resolution techniques such as magnetic resonance imaging (MRI)and positron emission tomography(PET).Though not capable of the sub-nanometer resolutions routinely achieved using electron microscopy,light microscopies have several significant advantages,specifically the ability to perform time-lapse imaging of biological samples in vitro(Michalet et al2003).Fluorescence microscopy,in particular,has revolutionized the visualization of sub-cellular interactions in living samples.However,despite hundreds of years of development,the classical Abbe limit of optical resolution had continued to define maximum achievable spatial resolutions of200(nanometers)nm and500nm in the lateral and axial dimensions,respectively.The Abbe limit accounts for the diffraction of light waves occurring between the sample and detector,this limiting factor popularly known as the‘diffraction barrier’.In recent decades,several novel fluorescence microscopy techniques have been developed that circumvent the established diffraction barrier;achieving sub-diffraction limit resolutions,they are collectively termed ‘superresolution’techniques.The approximate resolution ranges of several different forms of microscopy are presented infigure1.Here we review the superresolution technique known as stochastic optical reconstruction microscopy (STORM)(Rust et al2006)and provide practical guidelines for its use.Thefirst superresolution microscopy images were taken using near-field scanning optical microscopy(NSOM)in 1986(Betzig et al1986).By placing the detector a distance considerably shorter than the excitation wavelength from the sample,the aperture size(rather than diffraction)becomes the only factor limiting resolution.Specifically,NSOM is used toparison of the spatial resolutions possible utilizing different biological imaging techniques.Note that far-field superresolution techniques such as STORM are capable of approximately10nm resolution.detect normally inaccessible evanescentfields containing very high frequency spatial information.However,NSOM suffers from several limitations;chief among them is confinement of the technique to surface studies,precluding its use for observing intracellular activities.In the early1990s,the interference-based techniques4Pi(Hell and Stelzer1992)and I5M(Gustafsson et al1999)were introduced,significantly improving axial resolution to as low as100nm.These techniques use opposed objectives‘sandwiching’the sample; both are used to illuminate the sample and collect emission light,effectively doubling the numerical aperture(NA)of the system.Some of thefirst far-field microscopies to break the diffraction barrier in the lateral dimensions are those based on the concept of reversibly saturable opticalfluorescence transitions(RESOLFT)advanced by Hell and colleagues (Hell2005).RESOLFT outlines the potential application of reversible,optically-induced molecular transitions between any two states A and B towards diffraction-unlimited imaging.Popular techniques based on this concept include stimulated emission depletion(STED)(Hell and Wichmann 1994),ground state depletion(GSD)(Hell and Kroug1995) and saturated structured illumination microscopy(SSIM) (Gustafsson2005).Though SSIM had not been realized in a biological context until relatively recently(Rego et al2012), STED imaging has been used to create superresolution images of biological structures since about2000(Klar et al2000). During this time several structured illumination microscopy (SIM)techniques practically demonstrating a doubling of conventional diffraction-limited resolution were introduced (Heintzmann and Cremer1998,Frohn et al2000,Gustafsson 2000).SIM methods use illumination of a known pattern to modulatefluorescent signal such that normally unobservable high frequency information is artificially brought into an observable region of frequency space,and subsequently restored to its proper place through computational processing.Though STED is capable of theoretically unlimited resolution,with sub-10-nm resolution having been demon-strated(Rittweger et al2009);it is only compatible with a relatively small selection offluorescent probes and is difficult to apply towards multicolor imaging.SIM,on the other hand,can be used with almost anyfluorescent probe, is simply applied to multicolor and live-cell imaging,but is ultimately limited to about100nm lateral resolution.In 2006,several new superresolution microscopies based upon the temporal localization of singlefluorescent emitters were introduced.These techniques,known as stochastic optical reconstruction microscopy(STORM)(Rust et al2006), photoactivated localization microscopy(PALM)(Betzig et al2006)andfluorescence-photoactivated localization microscopy(FPALM)(Hess et al2006),are capable of approximately10–30nm lateral resolution.Additionally these‘single molecule’superresolution approaches have repeatedly been demonstrated with live cells(including tissues)and with multiple colors.Indeed,these powerful techniques have spawned a burgeoning family of single molecule detection-based superresolution methods;including direct STORM(dSTORM)(Heilemann et al2008),ground state depletion individual molecule return(GSDIM)(Foelling et al2008),PALM with independently running acquisition (PALMIRA)(Egner et al2007),and more.Collectively these pointillist techniques can be referred to as single molecule localization microscopy(SMLM).Figure2.Basic principle of STORM superresolution imaging.(a)Illustration of the real-space distribution of tagged microtubule protein.(b)–(e)Small,unique stochastic subsets of thefluorophore ensemble are activated,excited tofluoresce,and subsequently returned to the dark state.Each emitter isfitted to a sub-diffraction-limited area and all recorded emitter positions are assembled into a superresolution reconstruction(f).Redrawn and used with permission from Annual Reviews(Huang et al2009),c 2009.2.STORM microscopy2.1.STORM backgroundEach superresolution technique is endowed with a unique set of advantages and limitations,the investigator must choose the one that is compatible with their particular imaging needs.Factors to take into consideration include resolution,acquisition speed,live-cell sensitivity,and so forth. Included here is a detailed discussion of STORM,from general theory to the most recent advances,as well as some practical STORM imaging‘pointers’applied by the authors. As stated,SMLM techniques share a lot in common and are highly interchangeable:where applicable,advances in related methods will also be discussed.All SMLMs rely upon the sequential acquisition of sparse subsets of the entire fluorophore ensemble labeling the structure of interest,as illustrated byfigure2.Very few molecules should be allowed tofluoresce at any time;each emitter must be optically resolvable from each other emitter in order to precisely localize each emission event.Imaging is performed for several hundred to(sometimes)hundreds of thousands of frames, depending on the experimental requirements,with a unique stochastically activated subset of molecules being localized in each frame.Localizations from each frame are combined in a composite superresolution reconstruction.Data is captured using high performance electron multiplying charge-coupled devices(EMCCDs)with single photon sensitivity.Key to implementing single molecule imaging is the use of photoswitchablefluorescent probes,with the preferred type of probe being the primary difference between most SMLMs. STORM relies upon organicfluorophores that can be driven to a dark state with high-power imaging(reporter)lasers, allowing for subsequent re-activation of sparse subsets of molecules for repeated detection and localization.PALM and FPALM utilize genetically encoded optical highlighter-class fluorescent proteins.Fluorescent probes for SMLM will be discussed in greater detail.All other details,from microscope configuration to localization algorithms,are highly interchangeable between techniques.For example,an investigator can run a PALM experiment on a single molecule superresolution system branded for‘STORM’,and vice versa.2.2.Localization offluorescent signal2.2.1.Localization precision.Single molecule localization precision(position uncertainty)is dependent on several factors;chief among them is the number of photons emitted before a molecule returns to a dark state.The most commonly used method for characterizing the PSF of an emitter is to apply a two-dimensional Gaussianfit.Localization precision (a)can be approximated by the equation:a≈ /√N(1) where is the width of the observed PSF and N is the number of detected photons.PSF size is minimized by using high numerical aperture objectives.High performanceFigure3.The importance of molecular density in single molecule superresolution imaging.The fraction of pixels measured increases from top to bottom and the number of pixels per line from left to right.Note that with increasing number of pixels/line and decreasing fraction of pixels measured that the sampling interval is insufficient.This illustrates the importance of satisfying the Nyquist criterion,which calls for at least two measurements per resolution unit.Thus greater localization precision(analogous to the number of pixels/line)results in the need for proportionally greater sampling ed with permission from Macmillan Publishers Ltd:Nature Methods(Shroff et al 2008),c 2008.fluorophores for STORM,such as Cy5,emit approximately 6000photons per switching cycle and have a corresponding localization precision of approximately10nm(Huang et al 2008).Afluorescent protein,however,will generally emit in the range of200–600photons per cycle,with corresponding localization precisions closer to30nm(Betzig et al2006). Molecules often emit over multiple imaging frames,requiring one to establish threshold values for determining whether or not emitters should be grouped together,and thus considered a single molecule.As originally published,continuously emitting molecules displaced by no more than1pixel are grouped together into a single‘string’(Rust et al2006).The centroid position of the molecule is identified independently for each frame and averaged for thefinal localization,with each centroid position being weighted by the number of photons emitted during the respective frame(Rust et al2006).Localization precision can be tricky to define;arguably, the most practical method is to experimentally quantify structural resolution by resolving object features of known size.This has repeatedly been performed with cellular features such as microtubules,clathrin coated pits,and more(Bates et al2007,Huang et al2008).Precision can also be defined as the drift-corrected standard deviation of the Gaussian distributions of a single emitter,or the full width at half maximum of that standard deviation.Other metrics have been proposed,for example,a unifying measure of resolution for both conventional and superresolution microscopies has been advanced(Mukamel and Schnitzer2012).Termed the ‘information transfer function’,it provides a measure of resolution accuracy as a function of spatial frequency.For conventional microscopies it is proportional to the square of the modulation transfer function.Another factor to be mindful of is whether or not localization densities meet the Nyquist criterion of at least two measurements per resolution unit(Nyquist1932,Shannon1949).For example,if one’s calculated optical resolution for a single molecule experiment is20nm,then molecules would have to be spaced a maximum of10nm apart to satisfy the Nyquist density requirement. For densely labeled structures one does not typically have to worry about Nyquist resolution,but it may be problematic for more diffuse targets and can account for differences in the calculated optical resolution and realized structural resolution. The relationship betweenfluorophore density and resolution is illustrated byfigure3.2.2.2.Localization algorithms.One of the most time-consuming aspects of single molecule imaging is the required post-acquisition image analysis step for producing the superresolution reconstruction.This step can take upwards of an hour for larger datasets,even on computers equipped for the task.A generalized procedure for localizing single molecules is given byfigure4.Single molecule localization algorithms are largely adapted from earlier work in single particle tracking experiments(Cheezum et al2001,Thompson et al2002),wherefluorescence was sparse enough that temporal control of emission was not required.STORM was originally introduced using an algorithm thatfits individual localizations with a GaussianFigure 4.Illustration of the single molecule localization procedure.(a)An illustration of an idealized point-spread function (PSF)of a single fluorescent emitter.(b)Actual intensity data from a single emitter captured by an electron multiplying charge-coupled device (EMCCD)and characterized using a Gaussian fit.(c)Captured pixel data and data point localized to a sub-diffraction-limited area.PSF of variable size and ellipticity using non-linear least squares regression,rejecting molecules with dimensions deviating from defined acceptable values (Rust et al 2006).A similar approach also involves fitting localizations with a Gaussian PSF,but of fixed size and ellipticity (Wolter et al 2010).Additionally,localization can be performed using a maximum likelihood estimator rather than least squares (Aguet et al 2005,Smith et al 2010),which entails finding the model parameters most likely to produce the observed data,instead of finding the one that produces the least difference.The primary drawback of these types of algorithms is that they do not perform well for high density localization of emitters;they are generally limited to less than 0.6emitters per square micron.The past few years have seen the inception of many new localization algorithms for high density imaging of partially overlapping fluorophores (Huang et al 2011,Quan et al 2011,Cox et al 2012),including DAOSTORM (Holden et al 2011)and its three-dimensional analog 3D-DAOSTORM (Babcock et al 2012),which fit overlapping emitters with multiple PSF models (instead of just one),allowing the user to localize individual molecules that,using the single-PSF model algorithms,would have been thrown out.An exciting development is the application of pair-correlation analysis to PALM (PC-PALM)for probing the spatial relationships of clusters of localized molecules (Sengupta and Lippincott-Schwartz 2012).Using this suite of algorithms,one can quantitatively estimate both the number of detected proteins and their organization.Image analysis includes a vitally important drift correction step.Regardless of how ‘high-end’a system might be,drift (be it thermal,mechanical,etc)will occur during the imaging process,and must be corrected for.One method is to track a set of fiducial markers located within the imaging frame throughout the experiment,correcting using the drift of the markers as a model (Betzig et al 2006,Rust et al 2006).Fiducial markers can be fluorescent (e.g.gold or fluorescent beads,quantum dots,and more)or non-fluorescent and tracked in a corresponding bright field image (Vaughan et al 2012).Fluorescent fiducial markers can often be troublesome to use,accurate drift correctionrequires tracking a certain minimum population of markers over the course of the experiment,but having too many can interfere with visualization of the structure of interest.Drift correction can also be model-based:cross-correlation algorithms allow for the actual sample structure to be used to determine drift (Huang et al 2008,Mlodzianoski et al 2011).This approach has been applied by techniques such as atomic force microscopy (Rahe et al 2010)when structure shape is constant but spatial position varies.Drift correction is most complicated when applied to live-cell datasets,the dynamic nature of such an environment precludes the use of normal drift correction algorithms,but this can be overcome by using fiducial markers.2.3.Fluorescent probes for STORM2.3.1.Synthetic dye pairs.STORM was developed using antibodies labeled with two different organic fluorophores.These pairs,termed ‘molecular switches’,consist of an ‘activator’and a ‘reporter’dye:the reporter is the dye molecule being localized,ideally one will emit a large number of photons,have a prolonged off-state (low duty cycle),and can be repeatedly switched between the bright and dark states (Rust et al 2006).Activators are shorter wavelength dyes that,upon absorption,can return a reporter molecule in close proximity from a dark to fluorescent state.Activators are thus used to exert a measure of control over the number of associated reporters stochastically activated to a fluorescent state in each frame.The response of sample molecular switches to activation pulses is illustrated by figure 5.The most important advantage conferred by molecular switches,however,is the ability to use the same reporter dye coupled to several different activators,allowing one to control the proportion of reporters tagging different structures that fluoresce in each frame simply by changing the color of the activation light.At first glance this practice may seem silly,but one of the greatest challenges associated with STORM imaging is identifying probes with the right properties.At present almost all of the best STORM probes emit in the far-red spectrum,with the highest-performing andparison of the properties of many of the most popularfluorescent proteins and synthetic dyes for single moleculebest-characterized dyes being the carbocyanines Alexa Fluor 647and its structural analog Cy5(Dempsey et al2011).A table listing some of the best current single molecule superresolution probes is located in table1.The use of molecular switches introduces the need for an additional analysis step:crosstalk correction.For example,if one were imaging two different structures,one labeled with the switch Alexa405-Cy5and the other with Cy3–Cy5,the use of blue activation light does not mean that some of the Cy3-associated Cy5will notfluoresce. Activation only controls the proportion of reporters that are excited;it cannot account for non-specific and false activation events.The actual crosstalk operation determines the probability that localization is the‘wrong’color based on the observed local densities for each channel.Crosstalk ratios of15–35%between channels are normal for switches using the same reporter,and depend on thefluorophores used and experimental parameters such as laser power,exposure time,etc(Bates et al2007).Methods for reducing crosstalk include using higher activation laser power,increasing the frame rate,and decreasing reporter laser intensity.The user must set crosstalk thresholds following image analysis in order to restore data to its proper place or remove it from analysis altogether.However,this operation is not perfect,Figure5.Photoswitchable activator–reporterfluorophore pairs for STORM imaging.(a)Fluorescence intensity spikes from three different activator–reporter pairs.All three pairs share a common activator,thus upon activation all three probes can be excited tofluoresce simultaneously.(b)Chemical structures of the different example cyanine dyes from(a).Redrawn and used with permission from Science (Bates et al2007),c 2007.can be highly qualitative,and is especially problematic for switches labeling structures in very close proximity, virtually precluding the use of switches when superresolution colocalization analysis is the goal.2.3.2.Synthetic dyes.Another popular approach to STORM imaging relies upon using reporter dyes not coupled to an activator;the technique known alternatively dSTORM or GSDIM.Perhaps the greatest advantage of this technique is that the user does not have to rely on potentially misleading crosstalk correction operations when performing multicolor imaging.However,in order to perform multicolor imaging with dSTORM one must choose less-than-optimal probes from outside of the far-red spectrum. Additionally the user should be especially aware of the possible effects of chromatic aberration,though often trivial at diffraction-limited resolution;its effects can be magnified by superresolution imaging.Investigators in our laboratory have achieved great results with many of the dyes listed in supplementary table1(available at /JOpt/15/ 094001/mmedia),especially ATTO488,Cy3B,Alexa Fluor 568,and others.For comprehensive evaluations of large numbers of syntheticfluorophores,refer to the works of Dempsey et al(2011)and van de Linde et al(2011b).Many standard organic dyes have been extensively characterized for STORM imaging.Identification of alternate probes and methods for improving existing probes for STORM is of utmost interest in thefield;probe quality arguably defining the greatest limitation of single molecule imaging.2.3.3.Fluorescent proteins.As mentioned,it is possible to perform single molecule superresolution imaging with optical highlighterfluorescent proteins(FPs)(Betzig et al 2006,Hess et al2006).Though STORM does not technically exclude their use,they are mentioned as potential probes in the original STORM paper(Rust et al2006),as so far their use is primarily associated with PALM/FPALM and related derivatives.A large number of differentfluorescent proteins have been applied towards SMLM-type imaging, for an excellent review on their variety and superresolution applications refer to the work of Patterson et al(2010).Optical highlighter FPs generally come in one of three varieties. They can be photoactivatable(PA),switching permanently from a dark to afluorescent state.Popular examples include PA-GFP(dark to greenfluorescence)(Patterson and Lippincott-Schwartz2002)and PA-mCherry(dark to red fluorescence)(Subach et al2009),which have been used together in two-color PALM imaging experiments(Subach et al2009).Similarly,FPs can be photoswitchable:capable of reversible switching between a dark andfluorescent state for several cycles.Examples include reversibly dark-green fluorescent photoswitches Dronpa(Habuchi et al2005) and mGeos(Chang et al2012),which are activated with UV–violet light and imaged/returned to a dark state using blue light.Thefinal class is the photoconverters,which switch emission spectra upon activation.Perhaps the most popular FP in this class is EosFP(Wiedenmann et al2004),including the monomeric mEos2variant(McKinney et al2009),which is converted from a greenfluorescent state to red upon activation with UV–violet light.An interesting exceptionto this categorization is IrisFP(Adam et al2008)and its monomeric variant mIrisFP(Fuchs et al2010),which are both photoswitchable and photoconvertible.Strong UV–violet activation permanently converts molecules from a green to redfluorescent state,but weak activation can additionally be used to reversibly photoswitch both the green and red species from a dark tofluorescent state.Single molecule superresolution has been demonstrated using conventional fluorescent proteins;driving them into a dark state with high excitation intensities and subsequently imaging stochastic subsets of molecules returning to thefluorescent state when illuminated with much lower intensities(Biteen et al2008, Shaner et al2013).2.3.4.Quantum stly,quantum dots have been applied towards STORM-type imaging.Quantum dots are su-perconductor nanocrystals generally composed of a cadmium selenide core,whose size directly determines its emission characteristics(Alivisatos1996,Chan and Nie1998).Though many quantum dots do exhibit intrinsic blinking behavior, utilization of this property for SMLM has proven difficult pho-toluminescent blinking of quantum dots is largely attributed to chargefluctuations,and thus not directly photo-dependent (Galland et al2011),making it difficult to control the size of thefluorophore population in the‘on’state.Quantum dots can be potentially toxic to the cellular environment,UV illumination can cause photolysis of the CdSe nanocrystals, releasing toxic cadmium ions into the culture medium(Ballou et al2004,Pelley et al2009).Additionally,quantum dots are difficult to use as biologicalfluorescent markers,though they can be conjugated to biological targeting peptides,antibodies, etc,they are much larger in size(∼10–15nm across)than a typical synthetic dye molecule.However,the bluing property of certain types of quantum dots has been applied to single molecule detection(Hoyer et al2011).The emission spectra of stochastic subsets of the quantum dot population are slowly and stochastically blue-shifted,allowing for the serial detection of individual emitters.3.Advances in STORM imaging3.1.Multicolor STORM imagingMulticolor STORM imaging has undergone several ad-vancements since the inception of the technique.Thefirst reported multicolor STORM experiments relied exclusively upon molecular switches,using Cy5coupled to several different activators to produce three-color images of a model DNA sample(Rust et al2006)and two-color images of microtubules and clathrin(Bates et al2007). About this time multicolor PALM imaging of adhesion complex proteins using spectrally distinct photoswitchable fluorescent proteins was demonstrated(Shroff et al2007). Multicolor dSTORM was realized later,thefirst reported experiment using ATTO520and ATTO655to image the co-distribution of microtubules and cytochrome c(Heilemann et al2008).An example multicolor dSTORM image is given byfigure6,where microtubules are tagged with Alexa647and mitochondria with ATTO488.These methods rely upon sequential imaging offluorophores,and are thus not ideal for capturing the real-time dynamics of living cells.Simultaneous imaging offluorophores with distinct emission spectra but similar excitation requirements has been demonstrated with a variety of probes.Simultaneous four-color dSTORM imaging has been performed using a single laser line and two detection channels(Testa et al2010).Fluorescence is assigned to a fluorophore based on a characteristic proportion of photons emitted in one channel as compared to the other,with approximately10%crosstalk in probe identification.A similar approach uses a dichroic emission splitter to image Alexa647 and Alexa700simultaneously,exciting using a single647nm laser line(Lampe et al2012).This approach demonstrates less than1.5%crosstalk.Recently,six-color STORM imaging has been reported using switches with a model sample(Bates et al2012):two different reporters(Alexa647and750)are each coupled to three different activators(Alexa405,Cy2,or Cy3).Two detection channels are used;one for Alexa647and the other for Alexa750.Probes with the same activator are imaged simultaneously whilst those with different activators are imaged sequentially.It is also possible to perform multicolor imaging using different classes of probes,such as FPs in combination with organic dyes(Bock et al2007).3.2.Three-dimensional STORM imagingBefore discussing three-dimensional STORM imaging in detail,it is important to note that STORM and related techniques are often used in conjunction with total internal reflectionfluorescence(TIRF)microscopy(Axelrod1981),a powerful technique for exclusively excitingfluorophores lying within a few hundred nanometers of the coverglass–medium interface.Instead of true TIRF,many researchers prefer a pseudo-TIRF excitation regime where light is incident at an oblique,slightly sub-critical angle,allowing for deeper excitation penetration that stops short of becoming true epifluorescent illumination.An exciting variation of this approach,termed highly inclined and laminated optical sheet(HILO),has been used to constrain illumination to a well-defined optical sheet between5and10µm thick, dependent on the diameter of the incident illumination beam (Tokunaga et al2008,Baddeley et al2011).Both TIRF and HILO-type imaging provide a powerful optical-sectioning capability to single molecule imaging.Though great for imaging structures in thinner samples,adherent tissue culture cells being the preferred test medium,TIRF-type illumination is not compatible with the imaging of thick samples where the structure of interest is not located within TIRF range. TIRF is not required for STORM imaging,it is a convenient method for reducing background and thus for detecting individual photon bursts;it can be considered more important for PALM-type imaging due to the generally lower photon outputs and contrast ratios offluorescent proteins as compared to organic dyes(Betzig et al2006).Three-dimensional STORM imaging wasfirst realized by introducing a z-dependent ellipticity to the PSF of individual emitters(Huang et al2008).This is accomplished by。

ssd1963ql9使用手册

ssd1963ql9使用手册
5.1 5.2 80 BALLS TFBGA................................................................................................................................................10 128 PINS LQFP ....................................................................................................................................................11
7.1 MCU INTERFACE .................................................................................................................................................16 7.1.1 6800 Mode ..................................................................................................................................................16 7.1.2 8080 Mode ..................................................................................................................................................16 7.1.3 Register Pin Mapping .................................................................................................................................16 7.1.4 Pixel Data Format ......................................................................................................................................16 7.1.5 Tearing Effect Signal (TE) ..........................................................................................................................17 7.2 SYSTEM CLOCK GENERATION .............................................................................................................................18 7.3 FRAME BUFFER....................................................................................................................................................19 7.4 SYSTEM CLOCK AND RESET MANAGER ...............................................................................................................19 7.5 LCD CONTROLLER ..............................................................................................................................................20 7.5.1 Display Format ...........................................................................................................................................20 7.5.2 General Purpose Input/Output (GPIO) ......................................................................................................20

SHOT COUNTER

SHOT COUNTER

专利名称:SHOT COUNTER 申请号:JP2551277申请日:19770310公开号:JPS6362731B2公开日:19881205专利内容由知识产权出版社提供摘要:An improved calculator structure primarily for use with photographic apparatus is disclosed. A base member carries therein certain electronics including a light sensing device which receives light from an electronic flash associated with a camera and reflected from the subject to be photographed through an aperture in the base and through one of a plurality of apertures carried by a top member which is rotatable with respect to the base about a first axis. Carried by the base member are a first set of indicia indicative of the maximum distance from camera to subject available from the electronic flash being used. The first set of indicia are viewable through a window carried by the top member. A middle member is carried by the top member and is rotatable about a second axis displaced from the first axis. The middle member carries a second set of indicia indicative of various ASA film speeds and these are also viewable through the window in the top member. The middle member also carries a third set of indicia indicative of various F stop settings. These are viewable through a cutaway portion of the top member and in cooperation with an indicia bearing means mounted on the base member.更多信息请下载全文后查看。

数字图像处理第二章课后习题及中文版解答

数字图像处理第二章课后习题及中文版解答

数字图像处理(冈萨雷斯版,第二版)课后习题及解答(部分)Ch 22.1使用2.1节提供的背景信息,并采用纯几何方法,如果纸上的打印点离眼睛0.2m 远,估计眼睛能辨别的最小打印点的直径。

为了简明起见,假定当在黄斑处的像点变得远比视网膜区域的接收器(锥状体)直径小的时候,视觉系统已经不能检测到该点。

进一步假定黄斑可用1.5mm × 1.5mm 的方阵模型化,并且杆状体和锥状体间的空间在该阵列上的均匀分布。

解:对应点的视网膜图像的直径x 可通过如下图题2.1所示的相似三角形几何关系得到,即()()220.20.014d x = 解得x =0.07d 。

根据2.1节内容,我们知道:如果把黄斑想象为一个有337000个成像单元的正方形传感器阵列,它转换成一个大小580×580成像单元的阵列。

假设成像单元之间的间距相等,这表明在总长为1.5 mm 的一条线上有580个成像单元和579个成像单元间隔。

则每个成像单元和成像单元间隔的大小为s =[(1.5 mm)/1159]=1.3×10-6 m 。

如果在黄斑上的成像点的大小是小于一个可分辨的成像单元,在我们可以认为改点对于眼睛来说不可见。

换句话说,眼睛不能检测到以下直径的点:x =0.07d<1.3×10-6m ,即d <18.6×10-6 m 。

下图附带解释:因为眼睛对近处的物体聚焦时,肌肉会使晶状体变得较厚,折射能力也相对提高,此时物体离眼睛距离0.2 m ,相对较近。

而当晶状体的折射能力由最小变到最大时,晶状体的聚焦中心与视网膜的距离由17 mm 缩小到14 mm ,所以此图中选取14mm(原书图2.3选取的是17 mm)。

图 题2.12.2 当在白天进入一个黑暗的剧场时,在能看清并找到空座位时要用一段时间适应,2.1节(视觉感知要素)描述的视觉过程在这种情况下起什么作用?解:根据人眼的亮度适应性,1)由于户外与剧场亮度差异很大,因此当人进入一个黑暗的剧场时,无法适应如此大的亮度差异,在剧场中什么也看不见;2)人眼不断调节亮度适应范围,逐渐的将视觉亮度中心调整到剧场的亮度范围,因此又可以看见、分清场景中的物体了。

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equivalent pattern gives us the phase without using an unwrapping process. By scaling this phase, we can get the fringe orders of the high frequency components irrespective of phase discontinuities. These fringe orders help us to unwrap the phase and to determine its ambiguities caused by phase jumps greater than 2π. This method resembles the one proposed in Ref. [10], with the difference that they project the single period and the high frequency patterns independently; also, to get its phase values, they use phase shifting techniques, which requires at least three images of each one.
cxðx; yÞ ¼ 2πf x; cyðx; yÞ ¼ 2πf y; cxyðx; yÞ ¼ 2πðf þ 1Þx þ 2πf y ð2Þ
then the following relation holds,
cxyðx; yÞÀcxðx; y源自Àcyðx; yÞ ¼ 2πx;ð3Þ
26
C.A. García-Isáis, N. Alcalá Ochoa / Optics and Lasers in Engineering 53 (2014) 25–30
2. Theory
Let us explain our proposal. Using a computer, we generate a composite pattern to be projected onto the object surface given by
iDðx; yÞ ¼ ðG=6Þf3 þ cos ð2πf xÞ þ cos ð2πf yÞ
þ cos ½2πðf þ 1Þx þ 2πf yg;
ð1Þ
where f is a carrier frequency, G is a constant that represents the amplitude value introduced to obtain the maximum gray level range (i.e. G ¼ 255 for eight bit images), ðx; yÞ are the normalized pixel coordinates, and iDðx; yÞ is the image with its gray levels in the range [0,G]. It can be noticed that the pattern given by Eq. (1) comprises the sum of three fringe patterns: one with vertical fringes, another with horizontal fringes, and the last one with fringes almost at 451. If we denote the carrier terms as follows,
article info
Article history: Received 10 January 2013 Received in revised form 29 July 2013 Accepted 9 August 2013 Available online 6 September 2013
Keywords: Profilometry FFT Shape measurement Robotics
Optics and Lasers in Engineering 53 (2014) 25–30
Contents lists available at ScienceDirect
Optics and Lasers in Engineering
journal homepage: /locate/optlaseng
n Corresponding author. Tel.: þ 52 477 4414200; fax: þ 52 477 4414000. E-mail address: alon@cio.mx (N. Alcalá Ochoa).
0143-8166/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. /10.1016/j.optlaseng.2013.08.006
& 2013 Elsevier Ltd. All rights reserved.
1. Introduction
There is a diversity of techniques to get the shape of objects that have surface discontinuities or spatially isolated surfaces through the projection of light; perhaps the simplest is the projection of a single line, with the disadvantage of needing a scanning process [1]. In general, most methods, such as temporal phase unwrapping [2] or multi-frequency fringe projection [3], require the manipulation of various images; a detailed description of them can be found on the review articles of Refs. [4] and [5]. In order to reduce the erroneous measurements caused by object movements during the image grabbing process, or to decrease the acquisition time, it is desirable to get the 3D shape information from a single image. Takeda et al. [6] have proposed a method based on a two-frequency fringe pattern and modifications to the Gushov–Solodkin algorithm. Later, other single-shot methods have been proposed, as the two-frequency fringe pattern of [7], which requires an unwrapping process for both the high and low frequency phases. Also, a single color pattern has been proposed [8], but it requires an additional calibration process to avoid color crosstalk; moreover, the color absorption of some materials restricts its use. Additional references that utilize one image to get the surface profile can be found in the reviewed article of Ref. [9].
its cosine is a one period vertical fringe. This is an important relation that we will use later on. To simplify our notation, we will drop off the ðx; yÞ variables, but they will be implicit, although in some formulas, they are included to emphasize their dependence.
Our proposal deals with the projection of a single image (gray levels) to get the shape of objects having discontinuities or being spatially isolated. It is based on the projection of a composite fringe pattern with three frequencies and the calculation of a fringe pattern with an equivalent period of one. The phase of this
ð4Þ
where a and b are background and amplitude terms that depend on the object's reflectivity, respectively, and φx, φy and φxy are the phase functions related to the surface height hðx; yÞ. Eq. (4) can be
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