JPEG2000

1. JPEG2000 Yeh Po-Yin Lien Shao-Chieh Yang Yi-Lun

2. Outline • Introduction • Features • Flow chart • Discrete wavelet transform • EBCOT • ROI coding • Comparison of ROI coding algorithms • Conclusion • Reference

3. 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

4. Features • Superior low bit-rate performance • Below 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

5. Features • Region-of-Interest coding • More important parts be coded and transmitted with better quality and less distortion • Random codestream access and processing • Robustness to bit-error • Open architecture

6. Features • Context-based description • Image archival, indexing and searching • Protective image security • Watermarking, labeling, stamping and encryption • Continuous-tone and bi-level compression

7. tile tile code block code block subband subband subband tile tile code block code block tile subband Flow chart Desired ROI contour Wavelet mask generation Differential Chain Coding (DCC) Apply ROI bitplane shift Input Image DWT Q EBCOT code block Bit Plane Coding Binary Arithmetic Coding (MQ) File formatting and Layer formation Output bit stream

8. Discrete Wavelet Transform • Convolution-based • Lifting-based • 9-tap/7-tap Filter - lossy • 5-tap/3-tap Filter – lossless • Tap - number of coefficients

9. Lifting-based DWT

10. Multi-level DWT

12. 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

13. EBCOT – block coding • Each block been coded independently

14. 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

15. EBCOT • Layered Bit-Stream Formation

16. MQ coder • Recursively subdivide the 0-1 interval • Base on the conditional probability of the input symbols • Input symbols • More Probable Symbols (MPS) • Less Probable Symbols (LPS)

17. Region-of-Interest Coding • Particular regions of the image may be coded with better quality

18. ROI Mask Generation • In wavelet domain

19. ROI Bitplane shift • Generic scaling based method • Scaling based arbitrary shape ROI coding method • Maxshift method • Bitplane-by-Bitplane Shift method • Generalized Bitplane-by-Bitplane Shift method • Partial Significant Bitplanes Shift method

20. Least significant bitplane Most significant bitplane ROI BG s Generic scaling based • Control the relative importance between ROIs and BG • Adjust the scaling values (s) • Support multiple ROIs

21. 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

22. 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

23. 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 )

24. Least significant bitplane Most significant bitplane ROI BG Maxshift • Can 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

25. Maxshift • Cannot support multiple ROIs • No priority difference • Cannot control the relative importance between ROIs and BG

26. Circularly shaped ROI • The quality of ROI remains while reducing bit rate • (a) 0.4bpp • (b) 0.5bpp • (c) 0.6bpp • (d) 0.7bpp

27. Least significant bitplane Most significant bitplane ROI BG s1 = 6 s2 = 4 Bitplane-by-Bitplane shift • 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

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

29. Least significant bitplane Most significant bitplane ROI BG BP Mask 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 0 0 0 0 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 ROIs

30. Comparison

31. Least significant bitplane Most significant bitplane ROI BG s s Partial Significant Bitplane shift • Improved GBbBshift to support multiple ROIs • Coded with different quality according to their priorities in an image • Single ROI

32. Comparison • (a) 0.5bpp using Maxshift [s = 12] • (b) 0.5bpp using PSBShift [s = 10]

33. Least significant bitplane Most significant bitplane ROI - 1 s1 = 8 ROI - 2 s2 = 6 ROI - 3 s3 = 4 BG S = Max(s1, s2, s3) Partial Significant Bitplane shift • Multiple ROIs

34. Multiple ROI coding results PSNR Decoding bit rate (bpp)

35. Conclusion • JPEG2000 is the new standard for still image compression • Provides a wide range of functionalities for still image applications • Internet • Color facsimile • Printing • Scanning • Digital photography • Remote sensing • Mobile applications • Medical imagery • Digital library • E-commerce

36. Comparative result • JPEG2000 is indeed superior to existing still image compression standards

37. References • C. Christopoulos, A. Skodras, and T. Ebrahimi, “The JPEG2000 still image coding system: An overview,” IEEE Trans. Consum. Electron., vol. 49, p1103-1124, Nov. 2000 • K. Andra, C. Chakrabarti, T. Acharya, “A High-Performance JPEG2000 Architecture,” IEEE Trans. Vol. 13, No 3, p209-218, March 2003 • L. 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. 2003 • Chung-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, 2001 • M. Subedar, L. Karam, G. Abousleman, “An Embedded Scaling-Based Arbitrary Shape Region-of-Interest Coding Method for JPEG2000,” 0-7803-8484-9, p681-684, 2004 • K. Varma, A. Bell, “JPEG2000-Choices and Tradeoffs for Encoders,” IEEE Signal Processing Magazine, p70-75, Nov. 2004 • Z. 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. 2002 • Z. 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

38. Q&A

39. State information bits • Significance • Refinement • Sign

40. Coding method • Zero coding (ZC) • Sign coding (SC) • Run length coding (RLC) • Magnitude refinement coding (MRC)

41. Coding passes • Significance propagation pass • Magnitude refinement pass • Cleanup pass