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 in:	IEEE transactions on communications Vol. 60; no. 8; pp. 2187 - 2198
Main Authors:	Jalali, Shirin, Weissman, Tsachy
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.08.2012 Institute of Electrical and Electronics Engineers
Subjects:	Applied sciences Coding, codes Compression algorithms Encoding Entropy Exact sciences and technology Gibbs sampler Information, signal and communications theory Markov chain Monte Carlo Markov processes Rate-distortion Rate-distortion coding Signal and communications theory Simulated annealing Telecommunications and information theory universal lossy compression Vectors Alphabet Lossy compression Performance evaluation Block code Energy function Rate distortion theory Ergodicity Iterative method Gibbs sampling Gibbs sampler MCMC algorithm Coding universal lossy compression Markov chain Monte Carlo Simulated annealing Rate-distortion coding
ISSN:	0090-6778
Online Access:	Get full text
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