DocumentCode :
313997
Title :
Asymptotic performance of vector quantizers with the perceptual distortion measure
Author :
Li, Jia ; Chaddha, Navin ; Gray, Robert M.
Author_Institution :
Inf. Syst. Lab., Stanford Univ., CA, USA
fYear :
1997
fDate :
29 Jun-4 Jul 1997
Firstpage :
55
Abstract :
This paper generalizes the asymptotic bounds for block quantizers to input weighted quadratic distortion, a class of distortion measure often used for perceptually meaningful distortion. The second problem considered in the paper is source mismatching. When the quantizer uses a probability density estimation mismatched to the source, the asymptotic performance in terms of distortion increase in dB is shown to be linear in the relative entropy of the real probability density and the estimated one
Keywords :
entropy; estimation theory; probability; rate distortion theory; vector quantisation; asymptotic bounds; asymptotic performance; block quantizers; input weighted quadratic distortion; perceptual distortion measure; perceptually meaningful distortion; probability density estimation; relative entropy; source mismatching; vector quantizers; Density functional theory; Distortion measurement; Electric variables measurement; Entropy; Information systems; Laboratories; Probability density function; Random variables; Speech analysis; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Conference_Location :
Ulm
Print_ISBN :
0-7803-3956-8
Type :
conf
DOI :
10.1109/ISIT.1997.612970
Filename :
612970
Link To Document :
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