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Vidwav Wavelet Video Coding Specifications

Vidwav Wavelet Video Coding Specifications. Student: Chia-Yang Tsai Advisor: Prof. Hsueh-Ming Hang Institute of Electronics, NCTU. Outline. Framework Main modules Motion Temporal transform Spatial transform Entropy coding Bitstream formation Additional modules Base layer In-band coding

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Vidwav Wavelet Video Coding Specifications

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  1. Vidwav Wavelet Video Coding Specifications Student: Chia-Yang TsaiAdvisor: Prof. Hsueh-Ming HangInstitute of Electronics, NCTU

  2. Outline • Framework • Main modules • Motion • Temporal transform • Spatial transform • Entropy coding • Bitstream formation • Additional modules • Base layer • In-band coding • Wavelet ringing reduction • Conclusions

  3. References • Microsoft Research Asia + ENST + INRIA , “Vidwav Wavelet Video Coding Specifications”, ISO/IEC JTC1/SC29/WG11, M12339, Poznan, July. 2005.

  4. Framework

  5. T+2D (Pre-spatial decomposition is void)

  6. 2D+t

  7. MotionME/MCModes/MV coding

  8. ME/MC • Adopted from H.264/AVC. • Performed by minimizing the Lagrangian cost function • J= D + λR

  9. MV Coding • Median prediction • For squre MC block size • 16x16, 8x8, 4x4 • (ABC) or (ABD) • Directional segmentation prediction • If predictor is not available, use median prediction 8x16 16x8 8x4 4x8

  10. Temporal TransformMotion aligned temporal filteringPrediction stepUpdate step

  11. Split MAP MAU MAU MAP Merge Motion Aligned Temporal Filtering • Lifting structure • MAP (motion aligned prediction) • MAU (motion aligned update)

  12. Motion Aligned Temporal Filtering(Cont.) • Temporal lifting steps of 5/3 biorthogonal wavelet

  13. Prediction • Bidirectional connection • Uni-directional connection When left-unidirectional connected When right-unidirectional connected

  14. Prediction (Cont.) • OBMC

  15. Update • Generated from H-frames through MC • Clipping

  16. Spatial Transform

  17. Structure • Decomposition structure • Description S<>S<>E<>E<>E<>E<>E<>E<>E<> S<> S<> S<> E<> E<> E<> E<>E<> E<> E<> S<> E<> E<> E<> E<> S<> E<> E<> E<> E<> S<> E<> E<> E<> E<>

  18. Entropy Coding3D-EBCOTBitstream

  19. EBCOT • Embedded Block Coding coding pass Code block Bitplanes  Fractional bitplanes

  20. Coding Pass Operation Significant Propagation Pass Magnitude Refinement Pass Previous bit-plane Normalization Pass ZC ZC ZC SC MR Insignificant sample SC Significant sample In previous bit-plane ZC Current bit-plane Significant sample In current bit-plane

  21. Bitstream • N of total bitplanes in the block • The coded bitstream of the block, which consists of 3N-2 segments, each segment corresponding to the output bitstream of one coding pass. • The length of each bitstream segment and/or the position of end-point of each coding pass. • The R-D slope information at the end of each coding pass.

  22. Bitstream FormationSyntaxBitstream selection

  23. Syntax • Global • GOP • Group of picture for MCTF • Layer • For quick bitstream truncation • Packet • One component (Y, U, or V) of one temporal sunbbad • Subband • 3D subband • Block • Block of 3D EBCOT • Pass • Coding pass

  24. Bitstream Selection • Optimized Truncation Block n+1 Block n RD slope iteration m iteration m-1 Coding pass index Rn Rn+1 ΣRi <= bitrate constrain

  25. Base Layer

  26. Embedded Base Layer Codec

  27. Motion Information Prediction • BASESKIP mode • Use base-layer motion vectors as motion predictors Macroblock partitions mode map rule to generate the predictors for higher spatial resolution

  28. Hierarchical B-Pictures • Provide extra- temporal resolutions

  29. In-Band CodingLeaky motion compensationMode-based temporal filtering

  30. In-Band MCTF • The forming of different quality reference of LL • Low quality reference as IP_DIR • High quality reference as IP_LBS

  31. In-Band MCTF • Leaky motion compensation • leaky factor • Attenuate the prediction based on the unknown information at the decoder • make a good trade-off between drifting errors and coding efficiency

  32. In-Band MCTF • Mode-based temporal filtering • Mode I: Low quality reference • Mode 2: High quality reference • Mode is selected by RD cost

  33. Wavelet Ringing Reduction

  34. Description • Purpose • Reduce artifact after EDWT • Similar like the de-blocking filter in DCT based coding • After experiments,

  35. Conclusions

  36. Wavelet Based SVC • Advantages • Nature for multi-resolution scalability • Open-loop prediction structure • Provides elegant SNR scalability without impairing full exploitation of spatial-temporal correlation • Simplifies the R-D model of the bitstreams. • Facilitates the bitstream truncation • each subband is independent with other subbands

  37. Wavelet Based SVC • Disadvantages • Decomposition modes (coding modes) selection • Texture & side information trade off • Intra-prediction • Badly-matched blocks • Downsampling filter problems

  38. Thanks for your attention!Any questions?

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