Entropy coded successively refinable uniform threshold quantizers

Hugh Brunk, Hamid Jafarkhani, Nariman Farvardin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We examine the performance of entropy coded successively refinable uniform threshold quantizers, which have been utilized in numerous proposed progressive image coders. We view a successively refinable quantizer with N stages of refinement as consisting of a sequence of partitions {Pn}, and a sequence of codebooks {Cn}, 1 ≤ n ≤ N. We denote the nth reconstruction of an input sample x as xn; it can be obtained using the nth partition and nth codebook and a simple quantization rule. We consider the design of entropy-coded successively refinable scalar quantizers in which the finest (highest rate) partition and corresponding codebook comprise a uniform threshold quantizer (UTQ). All codebooks are designed optimally for the corresponding partitions and it is well known that entropy coded UTQs perform within 0.255 bits/sample of the rate distortion bound for a variety of source distributions.

Original languageEnglish
Title of host publicationProceedings - 1997 IEEE International Symposium on Information Theory, ISIT 1997
Pages58
Number of pages1
DOIs
StatePublished - 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

Conference

Conference1997 IEEE International Symposium on Information Theory, ISIT 1997
Country/TerritoryGermany
CityUlm
Period6/29/977/4/97

ASJC Scopus subject areas

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

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