JPEG2000
合集下载
相关主题
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
Store or Transmit
Reconstructed Image Data
Inverse Transform
Dequantization
Entropy Decoding
Compressed Image Data
6
Block diagrams of encode
原始图像
预处理及 彩色变换
Wavelet Transform
Embedded Block Coding (Tier1)
cx
Optimized Truncation (Tier2) RateDistortion Control
Context Arithmetic bitstream quantized coefficients Modeling D Coding
25
Magnitude Refinement
• The magnitude refinement pass includes the bits from coefficients that are already significant (except those that have just become significant in the immediately proceeding significance propagation pass). • The context used is determined by the summation of the significance state of the horizontal, vertical, and diagonal neighbors. These are the states as currently known to the decoder, not the states used before the significance decoding pass. • Further, it is dependent on whether this is the first refinement bit (the bit immediately after the significance and sign bits) or not.
• 低码率压缩
– JPEG在低码率时效果不好
• 无失真与有失真压缩法统一
– JPEG用DCT及量化做有失真压缩，用预测及Huffman 编码和算术编码做无失真压缩
• 合成图像压缩
– JPEG在自然影像表现不错，但在合成影像表现不佳
• 局部强化(ROI)
– JPEG2000可以提高图像某一部分的解析度
18
Coding
• Based on bit-plane • Three passes
– Significant Propagation Pass – Magnitude Refinement Pass – Cleanup Pass
19
Introduction for EBCOT
• EBCOT algorithm consists of embedded block coding (tier1) and optimized truncation (tier2).
THE JPEG2000 STILL IMAGE CODING SYSTEM: AN OVERVIEW
1
Outline
• • • • • • • JPEG2000的优点 JPEG2000的框图 预处理和彩色转换 小波变换 编码 感兴趣区域 (ROI) 实验结果
2
Advantages of JPEG2000
– i.e. when reversible wavelet transform is used
• When step sizes are > 1:
– The step sizes are chosen in conjunction with rate control – They are transferred with the code stream
低通: 100 100 87.5 112.5 187.5 212.5 200 200 高通: 0 0 0 -50 50 0 0 0
还原: 低通: 100 100 106.5 112.5 162.5 212.5 206.25 200 高通: 0 0 -6.25 -12.5 37.5 -12.5 -6.25 0 相加: 100 100 100 100 200 200 200 200
20
BIT PLANES
MSB
2N-1
2N-2
LSB
20
21
Bit-plane Coding
22
Scanning Order & Neighbor
D0
V1 D2
V0
X V3
D1
V2 D3
23
About Significance state
• Each coefficient in a code-block has an associated binary state variable called its significance state. • Significance states are initialized to 0 (coefficient is insignificant) and may become 1 (coefficient is significant) during the course of the coding of the code-block.
YCbCr
12
Wavelet Transform
13
Wavelet Transform Example
(5, 3) filter: h0[n] = (-1 2 6 2 -1)/8 g0[n] = (1 2 1)/2 h1[n] = (-1 2 -1)/2 g1[n] = (-1 -2 6 -2 -1)/8 input: 100, 100, 100, 100, 200, 200, 200, 200, … (-100+200+600+400-200)/8 先向左扩展两个样点: 100, 100, 100, 100, 100, 100, 200, 200, 200, 200, …
27
Region of Interests Coding (ROI)
• An ROI is a part of an image that is coded earlier in the code stream than the rest of the image (the background). • The method used is the Maxshift method. • ROI allows certain parts of the image to be coded in better quality
3
JPEG at 0.125 bpp (enlarged)
4
JPEG2000 at 0.125 bpp
5
Block diagrams of the HPEG2000
Source Image Data
Forward Transform
Quantization
Entropy Encoding
Compressed Image Data
28
Examples of ROI
29
0.125bpp
0.0625bpp
30
ROI Mask
31
Scaling of ROI coefficients
32
MAXSHIFT
33
Advantages of Maxshift method
• Support for arbitrary shaped ROI’s with minimal complexity • No need to send shape information • No need for shape encoder and decoder • No need for ROI mask at decoder side • Decoder as simple as non-ROI capable decoder
Color Transformation
C1 C2
JPEG2000 encoding JPEG2000 encoding Compressed Image Data
G B
C3
JPEG2000 encoding
9
Tile 对图像质量的影响
10
RGB YCbCr
11
RGB YCbCr
RGB
Quantization
压缩码流
比特流组成
算术编码
7
预处理与彩色变换
• tiling
– 节省存储空间 – 不SWT)
– 每个tile独立编码
• 彩色转换
– RGB YCbCr
8
预处理流程图
R
Color image
DC level shifting DC level shifting DC level shifting
24
Significant Propagation Pass
• The significance propagation pass includes only bits of coefficients that were insignificant (the significance bit has yet to be encountered) and have a non-zero context. All other coefficients are skipped. • The context is delivered to the arithmetic decoder (along with the bit stream) and the decoded coefficient bit is returned. • If the value of this bit is 1 then the significance state is set to 1 and the immediate next bit to be decoded is the sign bit for the coefficient. Otherwise, the significance state remains 0. • When the contexts of successive coefficients and coding passes are considered, the most current significance state for this coefficient is used.
A zero output may be produced for larger values on the input, to avoid recording noise
17
Quantization (2)
• One quantization step size is allowed for each sub-band • This operation is lossy unless for step size equal to 1
26
Cleanup Pass
• All bits not encoded during the previous passes (i.e. coefficients that are insignificant and had the context value of zero during the significance propagation pass). • Use both neighbor context as in significant propagation pass and run-length coding.
14
2D Separate DWT
15
2D Separate DWT
LL L H HL HH LH
Image in spatial domain
LH HL HH HL
LH HH
16
Quantization
• A uniform scalar quantization with dead-zone about the origin
Reconstructed Image Data
Inverse Transform
Dequantization
Entropy Decoding
Compressed Image Data
6
Block diagrams of encode
原始图像
预处理及 彩色变换
Wavelet Transform
Embedded Block Coding (Tier1)
cx
Optimized Truncation (Tier2) RateDistortion Control
Context Arithmetic bitstream quantized coefficients Modeling D Coding
25
Magnitude Refinement
• The magnitude refinement pass includes the bits from coefficients that are already significant (except those that have just become significant in the immediately proceeding significance propagation pass). • The context used is determined by the summation of the significance state of the horizontal, vertical, and diagonal neighbors. These are the states as currently known to the decoder, not the states used before the significance decoding pass. • Further, it is dependent on whether this is the first refinement bit (the bit immediately after the significance and sign bits) or not.
• 低码率压缩
– JPEG在低码率时效果不好
• 无失真与有失真压缩法统一
– JPEG用DCT及量化做有失真压缩，用预测及Huffman 编码和算术编码做无失真压缩
• 合成图像压缩
– JPEG在自然影像表现不错，但在合成影像表现不佳
• 局部强化(ROI)
– JPEG2000可以提高图像某一部分的解析度
18
Coding
• Based on bit-plane • Three passes
– Significant Propagation Pass – Magnitude Refinement Pass – Cleanup Pass
19
Introduction for EBCOT
• EBCOT algorithm consists of embedded block coding (tier1) and optimized truncation (tier2).
THE JPEG2000 STILL IMAGE CODING SYSTEM: AN OVERVIEW
1
Outline
• • • • • • • JPEG2000的优点 JPEG2000的框图 预处理和彩色转换 小波变换 编码 感兴趣区域 (ROI) 实验结果
2
Advantages of JPEG2000
– i.e. when reversible wavelet transform is used
• When step sizes are > 1:
– The step sizes are chosen in conjunction with rate control – They are transferred with the code stream
低通: 100 100 87.5 112.5 187.5 212.5 200 200 高通: 0 0 0 -50 50 0 0 0
还原: 低通: 100 100 106.5 112.5 162.5 212.5 206.25 200 高通: 0 0 -6.25 -12.5 37.5 -12.5 -6.25 0 相加: 100 100 100 100 200 200 200 200
20
BIT PLANES
MSB
2N-1
2N-2
LSB
20
21
Bit-plane Coding
22
Scanning Order & Neighbor
D0
V1 D2
V0
X V3
D1
V2 D3
23
About Significance state
• Each coefficient in a code-block has an associated binary state variable called its significance state. • Significance states are initialized to 0 (coefficient is insignificant) and may become 1 (coefficient is significant) during the course of the coding of the code-block.
YCbCr
12
Wavelet Transform
13
Wavelet Transform Example
(5, 3) filter: h0[n] = (-1 2 6 2 -1)/8 g0[n] = (1 2 1)/2 h1[n] = (-1 2 -1)/2 g1[n] = (-1 -2 6 -2 -1)/8 input: 100, 100, 100, 100, 200, 200, 200, 200, … (-100+200+600+400-200)/8 先向左扩展两个样点: 100, 100, 100, 100, 100, 100, 200, 200, 200, 200, …
27
Region of Interests Coding (ROI)
• An ROI is a part of an image that is coded earlier in the code stream than the rest of the image (the background). • The method used is the Maxshift method. • ROI allows certain parts of the image to be coded in better quality
3
JPEG at 0.125 bpp (enlarged)
4
JPEG2000 at 0.125 bpp
5
Block diagrams of the HPEG2000
Source Image Data
Forward Transform
Quantization
Entropy Encoding
Compressed Image Data
28
Examples of ROI
29
0.125bpp
0.0625bpp
30
ROI Mask
31
Scaling of ROI coefficients
32
MAXSHIFT
33
Advantages of Maxshift method
• Support for arbitrary shaped ROI’s with minimal complexity • No need to send shape information • No need for shape encoder and decoder • No need for ROI mask at decoder side • Decoder as simple as non-ROI capable decoder
Color Transformation
C1 C2
JPEG2000 encoding JPEG2000 encoding Compressed Image Data
G B
C3
JPEG2000 encoding
9
Tile 对图像质量的影响
10
RGB YCbCr
11
RGB YCbCr
RGB
Quantization
压缩码流
比特流组成
算术编码
7
预处理与彩色变换
• tiling
– 节省存储空间 – 不SWT)
– 每个tile独立编码
• 彩色转换
– RGB YCbCr
8
预处理流程图
R
Color image
DC level shifting DC level shifting DC level shifting
24
Significant Propagation Pass
• The significance propagation pass includes only bits of coefficients that were insignificant (the significance bit has yet to be encountered) and have a non-zero context. All other coefficients are skipped. • The context is delivered to the arithmetic decoder (along with the bit stream) and the decoded coefficient bit is returned. • If the value of this bit is 1 then the significance state is set to 1 and the immediate next bit to be decoded is the sign bit for the coefficient. Otherwise, the significance state remains 0. • When the contexts of successive coefficients and coding passes are considered, the most current significance state for this coefficient is used.
A zero output may be produced for larger values on the input, to avoid recording noise
17
Quantization (2)
• One quantization step size is allowed for each sub-band • This operation is lossy unless for step size equal to 1
26
Cleanup Pass
• All bits not encoded during the previous passes (i.e. coefficients that are insignificant and had the context value of zero during the significance propagation pass). • Use both neighbor context as in significant propagation pass and run-length coding.
14
2D Separate DWT
15
2D Separate DWT
LL L H HL HH LH
Image in spatial domain
LH HL HH HL
LH HH
16
Quantization
• A uniform scalar quantization with dead-zone about the origin