Transition filtering and optimized quantization in interframe wavelet video coding

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.