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Asymptotic Performance of Vector Quantizers with a Perceptual Distortion Measure
 in Proc. IEEE Int. Symp. on Information Theory, p. 55
, 1997
"... Gersho's bounds on the asymptotic performance of vector quantizers are valid for vector distortions which are powers of the Euclidean norm. Yamada, Tazaki and Gray generalized the results to distortion measures that are increasing functions of the norm of their argument. In both cases, the dist ..."
Abstract

Cited by 36 (3 self)
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Gersho's bounds on the asymptotic performance of vector quantizers are valid for vector distortions which are powers of the Euclidean norm. Yamada, Tazaki and Gray generalized the results to distortion measures that are increasing functions of the norm of their argument. In both cases, the distortion is uniquely determined by the vector quantization error, i.e., the Euclidean difference between the original vector and the codeword into which it is quantized. We generalize these asymptotic bounds to inputweighted quadratic distortion measures, a class of distortion measure often used for perceptually meaningful distortion. The generalization involves a more rigorous derivation of a fixed rate result of Gardner and Rao and a new result for variable rate codes. We also consider the problem of source mismatch, where the quantizer is designed using a probability density different from the true source density. The resulting asymptotic performance in terms of distortion increase in dB is shown...
The Accuracy of Measurements from Medical Images Compressed by Vector Quantization
, 1997
"... This paper has several purposes. One is to describe a particular set of algorithms for clustering and to show how they led to codes which can be used to compress images. The approach is called treestructured vector quantization and amounts to a binary treestructured twomeans clustering, very much ..."
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This paper has several purposes. One is to describe a particular set of algorithms for clustering and to show how they led to codes which can be used to compress images. The approach is called treestructured vector quantization and amounts to a binary treestructured twomeans clustering, very much in the spirit of CART TM . Another purpose is to put the coding into the larger framework of information theory. And a third is to report on how the methodology for image compression was applied in a clinical setting where the medical issue was the measurement of major blood vessels in the chest and the tedhnology magnetic resonance imaging (MR). Measuring the sizes of blood vessels, other organs, and tumors is fundamental to evaluating aneurysms, especially prior to surgery. We argue for digital approaches to imaging in general, two benefits being improved archiving and transmission, and another improved clinical usefulness through the application of digital image processing. These goals ...