Variable Rate Vector Quantization for Medical Image Compression

Eve A. Riskin, Tom Lookabaugh, Philip A. Chou, Robert M. Gray

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

Abstract

Three new techniques for variable rate vector quantizer design are applied to medical images. The first two are extensions of an algorithm for optimal pruning in tree-structured classification and regression due to Breiman, Friedman, Olshen, and Stone. The code design algorithms find subtrees of a given tree-structured vector quantizer (TSVQ), each one optimal in that it has the lowest average distortion of all subtrees of the TSVQ with the same or lesser average rate. Since the resulting subtrees have variable depth, natural variable rate coders result. The third technique is a joint optimization of a vector quantizer and a noiseless variable rate code. This technique is relatively complex but it has the potential to yield the highest performance of all three techniques.

Original languageEnglish
Pages (from-to)290-298
Number of pages9
JournalIEEE Transactions on Medical Imaging
Volume9
Issue number3
DOIs
StatePublished - Sep 1990

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