The Likelihood Encoder for Lossy Compression
Abstract
A likelihood encoder is studied in the context of lossy source compression. The analysis of the likelihood encoder is based on the soft-covering lemma. It is demonstrated that the use of a likelihood encoder together with the soft-covering lemma yields simple achievability proofs for classical source coding problems. The cases of the point-to-point rate-distortion function, the rate-distortion function with side information at the decoder (i.e. the Wyner-Ziv problem), and the multi-terminal source coding inner bound (i.e. the Berger-Tung problem) are examined in this paper. Furthermore, a non-asymptotic analysis is used for the point-to-point case to examine the upper bound on the excess distortion provided by this method. The likelihood encoder is also related to a recent alternative technique using properties of random binning.
Cite
@article{arxiv.1408.4522,
title = {The Likelihood Encoder for Lossy Compression},
author = {Eva C. Song and Paul Cuff and H. Vincent Poor},
journal= {arXiv preprint arXiv:1408.4522},
year = {2016}
}