DocumentCode :
588269
Title :
On random binning versus conditional codebook methods in multiple descriptions coding
Author :
Akyol, Emrah ; Viswanatha, Kumar ; Rose, Kenneth
Author_Institution :
Univ. of California, Santa Barbara, Santa Barbara, CA, USA
fYear :
2012
fDate :
3-7 Sept. 2012
Firstpage :
312
Lastpage :
316
Abstract :
There are two common types of encoding paradigms in multiple descriptions (MD) coding: i) an approach based on conditional codebook generation, which was originally initiated by El-Gamal and Cover for the 2 channel setting and later extended to more than 2 channels by Venkataramani, Kramer and Goyal (VKG), ii) and an approach based on Slepian and Wolf´s random binning technique, proposed by Pradhan, Puri and Ramchandran (PPR) for L >; 2 descriptions. It is well known that the achievable region due to PPR subsumes the VKG region for the symmetric Gaussian MD problem. Motivated by several practical advantages of random binning based methods over the conditional codebook encoding, this paper focuses on the following important questions: Does a random binning based scheme achieve the performance of conditional codebook encoding, even for the 2 descriptions scenario? Are random binning based approaches beneficial for settings that are not fully symmetric? This paper answers both these questions in the affirmative. Specifically, we propose a 2 descriptions coding scheme, based on random binning, which subsumes the currently known largest region for this problem due to Zhang and Berger. Moreover, we propose its extensions to L >; 2 channels and derive the associated achievable regions. The proposed scheme enjoys the advantages of both encoding paradigms making it particularly useful when there is symmetry only within a subset of the descriptions.
Keywords :
Gaussian distribution; source coding; 2 channel setting; Cover; El-Gamal; Pradhan, Puri and Ramchandran; Slepian random binning; Venkataramani, Kramer and Goyal; Wolf random binning; Zhang and Berger; conditional codebook encoding; conditional codebook generation; multiple descriptions coding; symmetric Gaussian MD problem; Conferences; Decoding; Encoding; Indexes; Random variables; Rate-distortion; Multiple description coding; ratedistortion theory; source coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory Workshop (ITW), 2012 IEEE
Conference_Location :
Lausanne
Print_ISBN :
978-1-4673-0224-1
Electronic_ISBN :
978-1-4673-0222-7
Type :
conf
DOI :
10.1109/ITW.2012.6404683
Filename :
6404683
Link To Document :
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