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 the properties of random binning.
Original language | English (US) |
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Article number | 7406745 |
Pages (from-to) | 1836-1849 |
Number of pages | 14 |
Journal | IEEE Transactions on Information Theory |
Volume | 62 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2016 |
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Library and Information Sciences
Keywords
- Berger-Tung
- Wyner-Ziv
- likelihood encoder
- rate-distortion theory
- soft-covering
- source coding