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Adaptive MCTF based on Correlation Noise Model for SNR Scalable Video Coding
Toronto, ON, Canada July 09-July 12
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICME.2006.2629182006 IEEE International Conference on ...
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Ruiqin Xiong, Institute of Computing Technology, Chinese Academy of Sciences; Microsoft Research Asia
Jizheng Xu, Microsoft Research Asia
Feng Wu, Microsoft Research Asia
Shipeng Li, Microsoft Research Asia
This paper proposes a subband adaptive motion compensated temporal filtering (MCTF) technique for scalable video coding and introduces a revised synthesis gain model for the quantization in this adaptive MCTF scheme. In scalable video coding, hierarchical MCTF is extensively adopted to exploit the temporal correlation across video frames. In this hierarchical MCTF structure, the strength of temporal correlation varies with the level of temporal transform and varies with the various spatial frequency components in a frame. The reconstruction noises also have diverse strength at various subbands. According to the correlation and noise characteristics of various subbands, we can adjust the strength of motion compensated prediction step in MCTF to maximally take the advantage of temporal correlation but restrict the propagation of reconstruction noise. The quantization step of each subband is also adjusted according to synthesis gain determined by the MCTF structure. In this way an adaptive MCTF scheme is formed and the proposed technique improves the coding performance of scalable video coding.
Citation:
Ruiqin Xiong, Jizheng Xu, Feng Wu, Shipeng Li, "Adaptive MCTF based on Correlation Noise Model for SNR Scalable Video Coding," icme, pp.1865-1868, 2006 IEEE International Conference on Multimedia and Expo, 2006
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