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Correlation channel modeling for practical Slepian-Wolf distributed video compression system using irregular LDPC codes

Authors: Li Li; Xiao Hu; Rui Zeng;

Correlation channel modeling for practical Slepian-Wolf distributed video compression system using irregular LDPC codes

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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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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