Asymptotic performance of vector quantizers with the perceptual distortion measure

Jia Li, Navin Chaddha, Robert M. Gray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper generalizes the asymptotic bounds for block quantizers to input weighted quadratic distortion, a class of distortion measure often used for perceptually meaningful distortion. The second problem considered in the paper is source mismatching. When the quantizer uses a probability density estimation mismatched to the source, the asymptotic performance in terms of distortion increase in dB is shown to be linear in the relative entropy of the real probability density and the estimated one.

Original languageEnglish (US)
Title of host publicationProceedings - 1997 IEEE International Symposium on Information Theory, ISIT 1997
Number of pages1
DOIs
StatePublished - Dec 1 1997
Event1997 IEEE International Symposium on Information Theory, ISIT 1997 - Ulm, Germany
Duration: Jun 29 1997Jul 4 1997

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other1997 IEEE International Symposium on Information Theory, ISIT 1997
CountryGermany
CityUlm
Period6/29/977/4/97

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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