Block and Sliding-Block Lossy Compression via MCMC

We propose an approach to lossy compression of finite-alphabet sources that utilizes Markov chain Monte Carlo (MCMC) and simulated annealing methods. The idea is to define an energy function over the space of reconstruction sequences. The energy of a candidate reconstruction sequence is defined such...

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Bibliographic Details
Published inIEEE transactions on communications Vol. 60; no. 8; pp. 2187 - 2198
Main Authors Jalali, Shirin, Weissman, Tsachy
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.08.2012
Institute of Electrical and Electronics Engineers
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Summary:We propose an approach to lossy compression of finite-alphabet sources that utilizes Markov chain Monte Carlo (MCMC) and simulated annealing methods. The idea is to define an energy function over the space of reconstruction sequences. The energy of a candidate reconstruction sequence is defined such that it incorporates its distortion relative to the source sequence, its compressibility, and the point sought on the rate-distortion curve. The proposed algorithm samples from the Boltzmann distribution associated with this energy function using the "heat-bath" algorithm. The complexity of each iteration is independent of the sequence length and is only linearly dependent on a certain context parameter, which grows sub-logarithmically with the sequence length. We show that the proposed algorithm achieves optimum rate-distortion performance in the limits of large number of iterations, and sequence length, when employed on any stationary ergodic source. Inspired by the proposed block-coding algorithm, we also propose an algorithm for constructing sliding-block (SB) codes using similar ideas.
ISSN:0090-6778
DOI:10.1109/TCOMM.2012.061412.110194