In interframe wavelet video coding, wavelet-based motion-compensated temporal filtering (MCTF) is combined with spatial wavelet decomposition, allowing for efficient spatio-temporal decorrelation and temporal, spatial and SNR scalability. Contemporary interframe wavelet video coding concepts employ block-based motion estimation (ME) and compensation (MC) to exploit temporal redundancy between successive frames. Due to occlusion effects and imperfect motion modeling, block-based MCTF may generate temporal high frequency subbands with block-wise varying coefficient statistics, and low frequency subbands with block edges. Both effects may cause declined spatial transform gain and blocking artifacts. As a modification to MCTF, we present spatial highpass transition filtering (SHTF) and spatial lowpass transition filtering (SLTF), introducing smooth transitions between motion blocks in the high and low frequency subbands, respectively. Additionally, we analyze the propagation of quantization noise in MCTF and present an optimized quantization strategy to compensate for variations in synthesis filtering for different block types. Combining these approaches leads to a reduction of blocking artifacts, smoothed temporal PSNR performance, and significantly improved coding efficiency.
KEYWORDS: Video coding, Wavelets, Linear filtering, Motion estimation, Video, 3D modeling, Motion models, Quantization, Communication engineering, Spatial filters
For exploitation of temporal interdependencies between consecutive frames, in existing 3D wavelet video coding concepts a blockwise motion estimation (ME) and compensation (MC) is employed. Because of local object motion, rotation or scaling, the processing of occlusion areas is problematic. In these regions, the calculation of correct motion vectors (MV) is not always possible and blocking artifacts may appear at the motion boundaries to the connected areas, for which uniquely referenced MV could be estimated. In order to avoid this, smooth transitions can be included around the occlusion pixels, which means to blur out the block artifacts. The proposed algorithm is based on the MC-EZBC 3D wavelet video coder (Motion-Compensated Embedded video coding algorithm using ZeroBlocks of subband / wavelet coefficients and Context modeling), which employs a lifting approach for temporal filtering.
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