Title :
An implementable lossy version of the Lempel-Ziv algorithm. I. Optimality for memoryless sources
Author :
Kontoyiannis, Ioannis
Author_Institution :
Dept. of Stat., Purdue Univ., West Lafayette, IN, USA
fDate :
11/1/1999 12:00:00 AM
Abstract :
A new lossy variant of the fixed-database Lempel-Ziv coding algorithm for encoding at a fixed distortion level is proposed, and its asymptotic optimality and universality for memoryless sources (with respect to bounded single-letter distortion measures) is demonstrated: as the database size m increases to infinity, the expected compression ratio approaches the rate-distortion function. The complexity and redundancy characteristics of the algorithm are comparable to those of its lossless counterpart. A heuristic argument suggests that the redundancy is of order (log log m)/log m, and this is also confirmed experimentally; simulation results are presented that agree well with this rate. Also, the complexity of the algorithm is seen to be comparable to that of the corresponding lossless scheme. We show that there is a tradeoff between compression performance and encoding complexity, and we discuss how the relevant parameters can be chosen to balance this tradeoff in practice. We also discuss the performance of the algorithm when applied to sources with memory, and extensions to the cases of unbounded distortion measures and infinite reproduction alphabets
Keywords :
computational complexity; rate distortion theory; redundancy; source coding; Lempel-Ziv algorithm; asymptotic optimality; coding algorithm; complexity; compression performance; database size; distortion level; distortion measures; heuristic argument; implementable lossy version; lossless scheme; memoryless sources; rate-distortion function; redundancy; reproduction alphabets; universality; Data compression; Databases; Distortion measurement; Encoding; Image coding; Image reconstruction; Loss measurement; Propagation losses; Rate-distortion; Source coding;
Journal_Title :
Information Theory, IEEE Transactions on