14 November 2007 Correlation channel modeling for practical Slepian-Wolf distributed video compression system using irregular LDPC codes
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Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904L (2007) https://doi.org/10.1117/12.774796
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
The development of practical distributed video coding schemes is based on the consequence of information-theoretic bounds established in the 1970s by Slepian and Wolf for distributed lossless coding, and by Wyner and Ziv for lossy coding with decoder side information. In distributed video compression application, it is hard to accurately describe the non-stationary behavior of the virtual correlation channel between X and side information Y although it plays a very important role in overall system performance. In this paper, we implement a practical Slepian-Wolf asymmetric distributed video compression system using irregular LDPC codes. Moreover, based on exploiting the dependencies of previously decode bit planes from video frame X and side information Y, we present improvement schemes to divide different reliable regions. Our simulation results show improving schemes of exploiting the dependencies between previously decoded bit planes can get better overall encoding rate performance as BER approach zero. We also show, compared with BSC model, BC channel model is more suitable for distributed video compression scenario because of the non-stationary properties of the virtual correlation channel and adaptive detecting channel model parameters from previously adjacent decoded bit planes can provide more accurately initial belief messages from channel at LDPC decoder.
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Li Li, Li Li, Xiao Hu, Xiao Hu, Rui Zeng, Rui Zeng, } "Correlation channel modeling for practical Slepian-Wolf distributed video compression system using irregular LDPC codes", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904L (14 November 2007); doi: 10.1117/12.774796; https://doi.org/10.1117/12.774796
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