Entropy-constrained successively refinable scalar quantization

Hamid Jafarkhani, Hugh Brunk, Nariman Farvardin

Research output: Contribution to journalConference articlepeer-review

Abstract

We study the design of entropy-constrained successively refinable scalar quantizers. We propose two algorithms to minimize the average distortion and design such a quantizer. We consider two sets of constraints on the entropy: (i) constraint on the average rate and (ii) constraint on aggregate rates. Both algorithms can be easily extended to design vector quantizers.

Original languageEnglish
Pages (from-to)337-346
Number of pages10
JournalData Compression Conference Proceedings
StatePublished - 1997
EventProceedings of the 1997 Data Compression Conference, DCC'97 - Snowbird, UT, USA
Duration: Mar 25 1997Mar 27 1997

ASJC Scopus subject areas

  • Computer Networks and Communications

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