DocumentCode
1291049
Title
Pointwise redundancy in lossy data compression and universal lossy data compression
Author
Kontoyiannis, Ioannis
Author_Institution
Dept. of Stat., Purdue Univ., West Lafayette, IN, USA
Volume
46
Issue
1
fYear
2000
fDate
1/1/2000 12:00:00 AM
Firstpage
136
Lastpage
152
Abstract
We characterize the achievable pointwise redundancy rates for lossy data compression at a fixed distortion level. “Pointwise redundancy” refers to the difference between the description length achieved by an nth-order block code and the optimal nR(D) bits. For memoryless sources, we show that the best achievable redundancy rate is of order O(√n) in probability. This follows from a second-order refinement to the classical source coding theorem, in the form of a “one-sided central limit theorem”. Moreover, we show that, along (almost) any source realization, the description lengths of any sequence of block codes operating at distortion level D exceed nR(D) by at least as much as C√(nloglogn), infinitely often. Corresponding direct coding theorems are also given, showing that these rates are essentially achievable. The above rates are in sharp contrast with the expected redundancy rates of order O(log n) reported by various authors. Our approach is based on showing that the compression performance of an arbitrary sequence of codes is essentially bounded below by the performance of Shannon´s random code. We obtain partial generalizations of the above results for arbitrary sources with memory, and we prove lossy analogs of “Barron´s Lemma” (Barron 1985)
Keywords
block codes; memoryless systems; rate distortion theory; redundancy; source coding; Barren´s Lemma; Shannon´s random code; arbitrary sequence; description length; lossy analogs; lossy data compression; memoryless sources; nth-order block code; one-sided central limit theorem; optimal nR(D) bits; partial generalization; pointwise redundancy; second-order refinement; source coding; universal lossy data compression; Block codes; Data compression; Distortion measurement; Information theory; Random variables; Rate-distortion; Source coding; Statistics;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.817514
Filename
817514
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