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Proceedings Paper

Correlation channel modeling for practical Slepian-Wolf distributed video compression system using irregular LDPC codes
Author(s): Li Li; Xiao Hu; Rui Zeng
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Paper 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.

Paper Details

Date Published: 14 November 2007
PDF: 9 pages
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
Show Author Affiliations
Li Li, Yunnan Normal Univ. (China)
Xiao Hu, GuangZhou Univ. (China)
Rui Zeng, Yunnan Normal Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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