Block and Sliding-Block Lossy Compression via MCMC

• 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

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...