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