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Theory and Practice of Rate Division in Distributed Video Coding

Peng WANG, Jia WANG, Songyu YU, Yuye PANG

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Peng WANG
Institute of Image Communication and Information Processing, Electronic Engineering Dept., Shanghai Jiao Tong University
Shanghai Key Laboratory of Digital Media Processing and Transmissions, Shanghai Jiao Tong University
The Institute of Electronics, Information and Communication Engineers
Jia WANG
Institute of Image Communication and Information Processing, Electronic Engineering Dept., Shanghai Jiao Tong University
Shanghai Key Laboratory of Digital Media Processing and Transmissions, Shanghai Jiao Tong University
Songyu YU
Institute of Image Communication and Information Processing, Electronic Engineering Dept., Shanghai Jiao Tong University
Shanghai Key Laboratory of Digital Media Processing and Transmissions, Shanghai Jiao Tong University
Yuye PANG
Institute of Image Communication and Information Processing, Electronic Engineering Dept., Shanghai Jiao Tong University
Shanghai Key Laboratory of Digital Media Processing and Transmissions, Shanghai Jiao Tong University

Corresponding author

Keywords:distributed source coding,distributed video coding,side-information frame,distributed frame

JOURNALRESTRICTED ACCESS

2008 Volume E91.AIssue 7Pages 1806-1811

DOIhttps://doi.org/10.1093/ietfec/e91-a.7.1806

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Published: July 01, 2008Received: August 27, 2007Available on J-STAGE: March 01, 2010Accepted: -Advance online publication: -Revised: -

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Abstract

Wyner and Ziv characterized the rate distortion function for lossy source coding with side information at the decoder. It is well known that for the quadratic Gaussian case, the Wyner-Ziv rate-distortion function coincides with the conditional rate-distortion function. In this paper, we extend the problem to the coding of multivariate Gaussian source with multiple Gaussian side information at the decoder. The achievable region is obtained, and it is easily extended to the case that the difference between the source and the side information is multivariate Gaussian, no matter what distributions the source and the side information are. We apply this theoretical model to Distributed Video Coding (DVC) by considering the difference of the Distributed frame (D frame) and the Side-information frame (S frame) to be multivariate Gaussian distributed. This introduces rate allocation problem into DVC, which can be solved by a reverse water-filling method. Simulation results show that around 1.5-2dB coding gain benefits from the multivariate Gaussian Wyner-Ziv coding model.

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