Data-Processing Bounds for Scalar Lossy Source Codes With Side Information at the Decoder

DOI10.1109/TIT.2013.2249654zbMATH Open1364.94312arXiv1209.2066OpenAlexW2175431004MaRDI QIDQ5346446

Avraham Reani, Neri Merhav

Publication date: 8 June 2017

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Abstract: In this paper, we introduce new lower bounds on the distortion of scalar fixed-rate codes for lossy compression with side information available at the receiver. These bounds are derived by presenting the relevant random variables as a Markov chain and applying generalized data processing inequalities a la Ziv and Zakai. We show that by replacing the logarithmic function with other functions, in the data processing theorem we formulate, we obtain new lower bounds on the distortion of scalar coding with side information at the decoder. The usefulness of these results is demonstrated for uniform sources and the convex function $Q(t)=t^{1-alpha}$, $alpha>1$. The bounds in this case are shown to be better than one can obtain from the Wyner-Ziv rate-distortion function.

Full work available at URL: https://arxiv.org/abs/1209.2066

Mathematics Subject Classification ID

Information theory (general) (94A15) Source coding (94A29)

Related Items (1)

Side-Information Scalable Source Coding

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