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Published August 2012 | public
Journal Article

Block and Sliding-Block Lossy Compression via MCMC

Abstract

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.

Additional Information

© 2012 IEEE. Paper approved by Z. Xiong, the Editor for Distributed Coding and Processing of the IEEE Communications Society. Manuscript received April 10, 2011; revised September 26, 2011 and January 19, 2012.

Additional details

Created:
August 22, 2023
Modified:
October 20, 2023