Variable rate vector quantization for medical image compression

Three 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 et al. The code design algorithms find subtrees of a given tree-structured vector...

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Bibliographic Details
Published inIEEE transactions on medical imaging Vol. 9; no. 3; pp. 290 - 298
Main Authors Riskin, E.A., Lookabaugh, T., Chou, P.A., Gray, R.M.
Format Journal Article
LanguageEnglish
Published United States IEEE 01.09.1990
Subjects
Biomedical imaging
Digital images
Image coding
Image converters
Image storage
Information systems
Laboratories
Magnetic resonance imaging
Pixel
Vector quantization
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Summary:Three 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 et al. 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.< >
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ISSN:0278-0062
1558-254X
DOI:10.1109/42.57766