Presentation on Efficient Wavelet-Based Video Compression
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(2) Where from? •. Research – – – – – –. Transform coding, 1970’s (Jain) Motion-Compensated Transform coding, 1980’s (Mussman) WT based compression, late 1980’s (Woods, Shapiro, …) Motion Compensated Temporal Filtering (Ohm 1994) X-lets (late 1990’s) Advanced space-time transforms (late 1990’s, Taubman, Pesquet-Popescu, …). Where from? •. Standardization – – – – – – – –. JPEG (Transform coding, late 1980’s) H.261 (MC Transform coding, late 1980’s) MPEG1, MPEG2 (MC Transform coding with B pictures, early 1990’s) JPEG 2000 (WT compression, early 2000) MPEG4 AVC, H.264 (MC Transform with improved entropy coding, early 2000) MPEG21 SVC (Interlayer MC predictive Transform coding, currently) In addition, MPEG exploration on Wavelet Video Coding (stopped at the last MPEG meeting). 2.
(3) Scalable Video Coding. QCIF 15 fps 150 kbps. Original 30 fps CIF. SV encoder CIF resolution 30 fps 2 Mbps. SV extractor. texture. SV decoder. mv. Decodable stream at the target operating point. Scalability requirements in video •. Typical (image) scalability – –. •. Add temporal scalability, i.e. –. •. Spatial resolution (dyadic, non dyadic) Quality (SNR) reduced frame rate (dyadic, non dyadic). Encapsulation of decoded bit-stream may turn out more complex for any desirable S-T-Q decoding path.. 3.
(4) Scalability requirements in video Scenario 1 – merged proposal for sub -extractions. spatial resolution. City, Crew, Harbour , Soccer. global bitstream. 4CIF. CIF bit-rates low. QCIF high. 60. 30. 15. 7.5. temporal resolution. Combined scalability test procedure defined at 69th ISO/MPEG Redmond, WA, USA (w6521). Making use of time redundancy •. Decorrelating in time –. 3D wavelet transform (space+time) > Poorly adapts to low temporal rate… > strong discontinuities in time at moving object boundaries. –. •. As in MC Transform Coding, need to take into account motion information. Motion Compensated Temporal Filtering –. Effective lifting implementation for Haar Transform, 5-3 filters, along motion trajectories.. 4.
(5) General framework for WT based video compression. Issues in WT based video compression •. Time then Space decomposition –. Block-based motion estimation > blocky displaced frame difference (DFD) • OBMC can reduce problem. –. DFD is not a piecewise smooth function > WT transform is not optimal > Less spatial Interband dependencies + difficult handling of subband coefficients due to poor energy compaction (sophistication of entropy coding). –. Shift variant nature of the WT > Non invertibility of the transform if lower spatial resolution needs to be reconstructed (unknown motion information). 5.
(6) Issues in WT based video compression •. Space then Time decomposition –. Shift variant nature of the WT > Different structure of spatial subband in presence of translation makes Motion Based Model inappropriate • Overcomplete spatial transform can reduce the problem. –. Motion fields can be quite different at various resolutions (loss of physical like motion) > small coding efficiency in motion representation. •. Layered representation (Laplacian pyramid) – –. Increased number of coefficients in transformed domain May be adequate to preserve motion field consistency across layers. JSVM comparison (see W8043) •. Objective comparison (Y PSNR) – –. •. SNR scalability: WT Spatial / Combined scalability: JSVM. Subjective comparison –. on average JSVM is slightly superior.. 6.
(7) Objective performance (Y PSNR only) SNR scalability only City sequence. Objective performance (Y PSNR only) SNR scalability only Crew sequence. 7.
(8) Objective performance (Y PSNR only) SNR scalability only Harbour sequence. Objective performance (Y PSNR only) Combined scalability 4CIF resolution. 8.
(9) Objective performance (average PSNR) Combined scalability (QCIF resol.) Multiple reference adjustments. Visual comparison City CIF 15fps 192kbps. STP-tool. JSVM3 (JVT). 9.
(10) Visual Comparison Harbour 4CIF 30fps 1024kbps. JSVM3 JVT. Visual Comparison: Harbour 4CIF 30fps 1024kbps. STP-tool. 10.
(11) Visual Comparison: Crew QCIF 15fps 128kbps JSVM. STP-tool STool. “t+2D”. Fr 17. Fr 31. Fr 83. JPEG 2000 comparison •. Objective comparison (combined scalability experiment) – –. Average PSNR: (4.Y+Cr+Cb)/6 Motion Adaptive WT significantly superior (both aceSVC and STP-tool) > performance gain for City 4-6 dB > Performance gain for Crew 2-3 dB. •. Subjective comparison – –. Unquestionable for City Superior for Crew. 11.
(12) JPEG 2000 comparison with respect to aceSVC. JPEG 2000 comparison with respect to STP-tool. Low spatial resolution points use different references. 12.
(13) Concluding remarks •. For a variety of applications that handle Moving Image Sequences – –. •. Preliminary simulations indicate – –. •. a substantial performance gain at a slightly higher complexity. Many additional interesting features, e.g. –. •. needs to have a more effective bandwidth representation ensures a baseline JPEG 2000 compatibility. Compressed domain processing for content description and information retrieval. THUS ISO/JPEG should open within AIC a study of technologies for better handling of temporal correlation. 13.
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