JPEG2000

Yeh Po-Yin

Lien Shao-Chieh

Yang Yi-Lun

Outline

IntroductionFeaturesFlow chartDiscrete wavelet transformEBCOTROI codingComparison of ROI coding algorithmsConclusionReference

Introduction

The Joint Photographic Experts Group

Intended to create a new image coding system for different types of still images.

Compliment and not to replace the current JPEG standards

Features

Superior low bit-rate performanceBelow 0.25bpp for highly detailed gray-scale images

Lossless and lossy compression

Progressive transmission by pixel accuracy and resolution

Reconstruct images with increasing pixel accuracy

Features

Region-of-Interest codingMore important parts be coded and transmitted with better quality and less distortion

Random codestream access and processing

Robustness to bit-error

Open architecture

Features

Context-based descriptionImage archival, indexing and searching

Protective image securityWatermarking, labeling, stamping and encryption

Continuous-tone and bi-level compression

Flow chart

tile

tile

tile

tile

DWT Q

subbandsubband

subband

tile

codeblock

codeblock

codeblock

codeblock

subband

Input Image

Desired ROI contour Wavelet mask generation Differential ChainCoding (DCC)

Bit Plane Coding

Apply ROIbitplane shift

Binary Arithmetic Coding (MQ)

Output bit stream

codeblock

File formatting andLayer formation

EBCOT

Discrete Wavelet Transform

Convolution-based

Lifting-based9-tap/7-tap Filter - lossy

5-tap/3-tap Filter – lossless

Tap - number of coefficients

Lifting-based DWT

Multi-level DWT

Embedded block coding with optimized truncation (EBCOT)

Block coding and bitstream generation

Postcompression rate distortion (PCRD) optimization

Replaced by the MQ coder to avoid divisions

Layer formation and representation

EBCOT – block coding

Each block been coded independently

EBCOT – rate distortion

Minimize the overall distortion ,subject to the bit-rate constraint.

where is the distortion from code block Bi having truncation point ni

EBCOT

Layered Bit-Stream Formation

MQ coderRecursively subdivide the 0-1 interval

Base on the conditional probability of the input symbols

Input symbolsMore Probable Symbols (MPS)

Less Probable Symbols (LPS)

Region-of-Interest Coding

Particular regions of the image may be coded with better quality

ROI Mask Generation

In wavelet domain

ROI Bitplane shift

Generic scaling based methodScaling based arbitrary shape ROI coding methodMaxshift methodBitplane-by-Bitplane Shift methodGeneralized Bitplane-by-Bitplane Shift methodPartial Significant Bitplanes Shift method

Generic scaling based

Control the relative importance between ROIs and BG

Adjust the scaling values (s)

Support multiple ROIs

Most significant bitplane Least significant bitplane

ROI

BG

s

Generic scaling based

Not convenient to deal with different wavelet subbands in different ways

Needs to encode and transmit the shape information of the ROIs

Support rectangle and ellipse

Shape coding will consume a large number of bits if arbitrary ROI shapes are desired

Scaling based arbitrary shape ROI coding method

Improved Generic Scaling based method to support arbitrary shape ROI

Use Differential Chain Coding (DCC) to code the ROI contour information

Differential chain coding (DCC)

Code the ROI contour information

Begin from a seed point located at the top left-most contour pixel

Directions ( Huffman coded ):Same direction ( SD = 0 )

Different direction:Counter-clockwise ( DDCCW = 11 )

Clockwise ( DDCW = 10 )

MaxshiftCan have arbitrary shaped ROI

Choose different bitrates for the ROI and for the BG

Give similar results to general scaling method

No need of shape information to the decoder

Most significant bitplane Least significant bitplane

ROI

BG

Maxshift

Cannot support multiple ROIsNo priority difference

Cannot control the relative importance between ROIs and BG

Circularly shaped ROIThe quality of ROI remains while reducing bit rate

(a) 0.4bpp

(b) 0.5bpp

(c) 0.6bpp

(d) 0.7bpp

Take the advantages of Generic scaling based and Maxshift methods

Able to control the relative importance between ROIs and BG

No need of shape information to the decoder

Cannot support multiple ROIs

Bitplane-by-Bitplane shift

Most significant bitplane Least significant bitplane

ROI

BG

s1 = 6 s2 = 4

Comparison

24bpp RGB image decoded at 0.8bpp using (left) Maxshift method [s = 12], and (right) the BbBShift method [s1 = 6, s2 = 6]

Generalized Bitplane-by-Bitplane Shift

Transmit BP mask instead of scaling values

Provide better quality at BG without visual difference at ROI (compared with Maxshift method)

Cannot support multiple ROIsMost significant bitplane Least significant bitplane

ROI

BG

0 0 0 0 0 1 1 1011 1 111BP Mask 0 0 001

Comparison

Improved GBbBshift to support multiple ROIs

Coded with different quality according to their priorities in an image

Single ROI

Partial Significant Bitplane shift

Most significant bitplane Least significant bitplane

ROI

BG

s s

Comparison

(a) 0.5bpp using Maxshift [s = 12](b) 0.5bpp using PSBShift [s = 10]

Partial Significant Bitplane shift

Multiple ROIsMost significant bitplane Least significant bitplane

ROI - 1

BG

ROI - 2

ROI - 3

s1 = 8

s2 = 6

s3 = 4

S = Max(s1, s2, s3)

Multiple ROI coding results

PSNR

Decoding bit rate (bpp)

Conclusion

JPEG2000 is the new standard for still image compressionProvides a wide range of functionalities for still image applications

InternetColor facsimilePrintingScanningDigital photographyRemote sensingMobile applicationsMedical imageryDigital libraryE-commerce

Comparative resultJPEG2000 is indeed superior to existing still image compression standards

ReferencesC. Christopoulos, A. Skodras, and T. Ebrahimi, “The JPEG2000 still image coding system: An overview,” IEEE Trans. Consum. Electron., vol. 49, p1103-1124, Nov. 2000K. Andra, C. Chakrabarti, T. Acharya, “A High-Performance JPEG2000 Architecture,” IEEE Trans. Vol. 13, No 3, p209-218, March 2003L. Liu, G. Fan, “A New JPEG2000 Region-of-Interest Image Coding Method: Partial Significant Bitplanes Shift,” IEEE Signal Processing Letters, Vol. 10, No. 2, p35-38, Feb. 2003Chung-Jr Lian, Kuan-Fu Chen, Hong-Hui Chen, Lian-Gee Chen, “Lifting Based Discrete Wavelet Transform Architecture for JPEG2000,” IEEE, 0-7803-6685-9, p445-448, 2001M. Subedar, L. Karam, G. Abousleman, “An Embedded Scaling-Based Arbitrary Shape Region-of-Interest Coding Method for JPEG2000,” 0-7803-8484-9, p681-684, 2004K. Varma, A. Bell, “JPEG2000-Choices and Tradeoffs for Encoders,” IEEE Signal Processing Magazine, p70-75, Nov. 2004Z. Wang, A.Bovik, “Bitplane-by-Bitplane Shift (BbBShift)- A Suggestion for JPEG2000 Region of Interest Image Coding,” IEEE Signal Processing Letters, Vol. p, No. 5, p160-162, May. 2002Z. Wang, S. Banerjee, B. Evans, A. Bovik, “Generalized Bitplane-by-Bitplane Shift Method for JPEG2000 ROI Coding,” IEEE ICIP, p81-84, 2002王聰智 , “ 資料壓縮 , 專題報告 – JPEG2000,” http://140.116.72.203/pdf/course/Reports/JPEG_2000.pdf

Q&A

State information bits

Significance

Refinement

Sign

Coding method

Zero coding (ZC)

Sign coding (SC)

Run length coding (RLC)

Magnitude refinement coding (MRC)

Coding passes

Significance propagation pass

Magnitude refinement pass

Cleanup pass