手机camera test工具
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• Seen as “color fringing” near corners. • Can be digitally corrected.
original | with CA
SFR (Spatial frequencΒιβλιοθήκη Baidu response)
Imatest : introduction
Norman Koren www.imatest.com
original | blurred
SFR (Spatial frequency response)
Log frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 9
Sharpening
• Most digital images look soft without sharpening. • Subtracts a fraction of neighboring pixels from each pixel. • Boosts contrast & MTF at high spatial frequencies. • Applied to virtually all digital camera images— in the camera, RAW converter, and/or image editor.
Image quality measurement:
real world challenges
Norman Koren Imatest LLC Boulder, Colorado
www.imatest com
• Background: Predicting image quality; Imatest structure • Image quality factors and how they are measured • Imatest modules: review
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 10
Sharpness (oversharpening)
original | oversharpened
• Too much digital sharpening causes severe “halos” at edges. • Peak in MTF response. • Boosts MTF50. • Common in compact digital cameras. • Looks OK in small images; bad enlarged.
Spatial frequency response (SFR); Modulation transfer function (MTF) • • Upper: Sine and bar patterns: original and blurred. Middle: Level of the blurred bar pattern (red curve). Contrast decreases at high spatial frequencies. Lower: the corresponding MTF (SFR) curve (blue curve). Low frequency MTF is defined to be 1 (100%). MTF can be larger than 1. Strongly affected by signal processing (sharpening).
Imatest: Background
• Created to enable individual photographers to test lenses and cameras.
– Lens sharpness? – Camera dynamic range? – Color reproduction accuracy?
quency response)
Colorcheck, Multicharts Stepchart Light Falloff Distortion
Module
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 7
Measuring sharpness
May. 18, 2006
P. 13
Noise
• A serious degradation; corresponding to grain in film. • Software noise reduction can remove fine detail.
original | noisy
Stepchart Colorcheck
original | color-shifted
Colorcheck
May. 18, 2006
Original on left
Degraded on right
P. 6
Imatest : introduction
Norman Koren www.imatest.com
Module summary SFR (Spatial freLog frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 14
Color accuracy
• Uses the GretagMacbeth ColorChecker (in Colorcheck; other charts in Multicharts). • Errors displayed in L*a*b* space. • Several color difference metrics can be selected. • Reference colors can be selected to be accurate or pleasing.
Image quality factor
Sharpness Lateral chromatic aberration Loss of detail (NR) Noise Color accuracy Tonal response and contrast Dynamic range Lens flare Exposure accuracy Uniformity Lens distortion
Black– unsharpened Red: sharpened
• Different amounts of sharpening in different cameras makes comparisons challenging.
Transfer function: MTFsharp( f ) = (1 – ksharp cos(2π f V ))/(1-ksharp) where V = Sharpening radius / pixel spacing
A+
A
B+
B
C+ 69-79
C 59-69
D
F
94-100 89-94 84-89 79-84
49-59 Under 49
CSF of the human eye
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 12
Lateral chromatic aberration
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 2
Image quality example
Flare light? Sharpness
JPEG artifacts Lost tonal detail
DOC/NIST building in Boulder (atomic clock): Street view boundary Poor sharpness, smudged shadow detail, JPEG artifacts, flare light(?)
Imatest was created to predict imaging system performance.
May. 18, 2006
Imatest : introduction Norman Koren www.imatest.com
P. 3
Imatest: Basics
• Photograph test chart (standard or user-created) in controlled environment or as part of a scene.
•
Analyze image for relevant quality factor.
•
Cannot separate lens, sensor, signal processing.
Imatest : introduction
Norman Koren www.imatest.com P. 4
May. 18, 2006
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 5
Tour of image quality factors with examples of Imatest analysis
Monument Valley/Hunt’s Mesa image illustrates image quality factor degradations. Issues to think about: • Capture vs. post-processing • Objective measurements vs. subjective judgment
Spatial frequency
May. 18, 2006
• • •
Imatest : introduction
Norman Koren www.imatest.com
P. 8
Sharpness (loss)
• Arguably the most important factor • Determines how much detail can be conveyed • Affected by the lens, sensor, and digital signal processing (sharpening) • Measured by Spatial frequency response (SFR), AKA Modulation Transfer Function (MTF)
• MTF, A measure of subjective (perceptual) sharpness, optionally displayed in SFR, that combines
• The human eye’s Contrast sensitivity function (CSF) (peaks at 6-8 cycles/degree), • Image height, • Viewing distance
• • • •
Widely adopted by industry: mobile imaging and many others. Compiled Matlab. Downloaded from www.imatest.com. Modules analyze images of standard targets.
SFR (Spatial frequency response)
Log frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 11
SQF: Subjective Quality Factor
original | with CA
SFR (Spatial frequencΒιβλιοθήκη Baidu response)
Imatest : introduction
Norman Koren www.imatest.com
original | blurred
SFR (Spatial frequency response)
Log frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 9
Sharpening
• Most digital images look soft without sharpening. • Subtracts a fraction of neighboring pixels from each pixel. • Boosts contrast & MTF at high spatial frequencies. • Applied to virtually all digital camera images— in the camera, RAW converter, and/or image editor.
Image quality measurement:
real world challenges
Norman Koren Imatest LLC Boulder, Colorado
www.imatest com
• Background: Predicting image quality; Imatest structure • Image quality factors and how they are measured • Imatest modules: review
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 10
Sharpness (oversharpening)
original | oversharpened
• Too much digital sharpening causes severe “halos” at edges. • Peak in MTF response. • Boosts MTF50. • Common in compact digital cameras. • Looks OK in small images; bad enlarged.
Spatial frequency response (SFR); Modulation transfer function (MTF) • • Upper: Sine and bar patterns: original and blurred. Middle: Level of the blurred bar pattern (red curve). Contrast decreases at high spatial frequencies. Lower: the corresponding MTF (SFR) curve (blue curve). Low frequency MTF is defined to be 1 (100%). MTF can be larger than 1. Strongly affected by signal processing (sharpening).
Imatest: Background
• Created to enable individual photographers to test lenses and cameras.
– Lens sharpness? – Camera dynamic range? – Color reproduction accuracy?
quency response)
Colorcheck, Multicharts Stepchart Light Falloff Distortion
Module
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 7
Measuring sharpness
May. 18, 2006
P. 13
Noise
• A serious degradation; corresponding to grain in film. • Software noise reduction can remove fine detail.
original | noisy
Stepchart Colorcheck
original | color-shifted
Colorcheck
May. 18, 2006
Original on left
Degraded on right
P. 6
Imatest : introduction
Norman Koren www.imatest.com
Module summary SFR (Spatial freLog frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 14
Color accuracy
• Uses the GretagMacbeth ColorChecker (in Colorcheck; other charts in Multicharts). • Errors displayed in L*a*b* space. • Several color difference metrics can be selected. • Reference colors can be selected to be accurate or pleasing.
Image quality factor
Sharpness Lateral chromatic aberration Loss of detail (NR) Noise Color accuracy Tonal response and contrast Dynamic range Lens flare Exposure accuracy Uniformity Lens distortion
Black– unsharpened Red: sharpened
• Different amounts of sharpening in different cameras makes comparisons challenging.
Transfer function: MTFsharp( f ) = (1 – ksharp cos(2π f V ))/(1-ksharp) where V = Sharpening radius / pixel spacing
A+
A
B+
B
C+ 69-79
C 59-69
D
F
94-100 89-94 84-89 79-84
49-59 Under 49
CSF of the human eye
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 12
Lateral chromatic aberration
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 2
Image quality example
Flare light? Sharpness
JPEG artifacts Lost tonal detail
DOC/NIST building in Boulder (atomic clock): Street view boundary Poor sharpness, smudged shadow detail, JPEG artifacts, flare light(?)
Imatest was created to predict imaging system performance.
May. 18, 2006
Imatest : introduction Norman Koren www.imatest.com
P. 3
Imatest: Basics
• Photograph test chart (standard or user-created) in controlled environment or as part of a scene.
•
Analyze image for relevant quality factor.
•
Cannot separate lens, sensor, signal processing.
Imatest : introduction
Norman Koren www.imatest.com P. 4
May. 18, 2006
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 5
Tour of image quality factors with examples of Imatest analysis
Monument Valley/Hunt’s Mesa image illustrates image quality factor degradations. Issues to think about: • Capture vs. post-processing • Objective measurements vs. subjective judgment
Spatial frequency
May. 18, 2006
• • •
Imatest : introduction
Norman Koren www.imatest.com
P. 8
Sharpness (loss)
• Arguably the most important factor • Determines how much detail can be conveyed • Affected by the lens, sensor, and digital signal processing (sharpening) • Measured by Spatial frequency response (SFR), AKA Modulation Transfer Function (MTF)
• MTF, A measure of subjective (perceptual) sharpness, optionally displayed in SFR, that combines
• The human eye’s Contrast sensitivity function (CSF) (peaks at 6-8 cycles/degree), • Image height, • Viewing distance
• • • •
Widely adopted by industry: mobile imaging and many others. Compiled Matlab. Downloaded from www.imatest.com. Modules analyze images of standard targets.
SFR (Spatial frequency response)
Log frequencyContrast
May. 18, 2006
Imatest : introduction
Norman Koren www.imatest.com
P. 11
SQF: Subjective Quality Factor