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arXiv · 1408.4522

The Likelihood Encoder for Lossy Compression

Eva C. Song·Paul Cuff·H. Vincent Poor
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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.

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Eva C. Song, Paul Cuff, H. Vincent Poor. 2016-04-05. The Likelihood Encoder for Lossy Compression. https://doi.org/10.1109/tit.2016.2529657

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