Optimal variable-rate mean-gain-shape vector quantization for image coding

Author

Lightstone, Michael ; Mitra, Sanjit K.

Author_Institution

Chromatic Res. Inc., Sunnyvale, CA, USA

Volume

6

Issue

6

fYear

1996

fDate

12/1/1996 12:00:00 AM

Firstpage

660

Lastpage

668

Abstract

A method for rate-distortion optimal variable rate mean-gain-shape vector quantization (MGSVQ) is presented with application to image compression. Conditions are derived within an entropy-constrained product code framework that result in an optimal bit allocation between mean, gain, and shape vectors at all rates. An extension to MGSVQ called hierarchical mean-gain-shape vector quantization (HMGSVQ) is similarly introduced. By considering the statistical dependence between adjacent means, this method is able to provide an improvement in the rate-distortion performance over traditional MGSVQ, especially at low bit rates. Simulation results are provided to demonstrate the rate-distortion performance of MGSVQ and HMGSVQ for image data

Keywords

entropy codes; image coding; optimisation; rate distortion theory; statistical analysis; vector quantisation; HMGSVQ; MGSVQ; entropy constrained product code; gain vectors; hierarchical mean gain shape vector quantization; image compression; image data; low bit rates; mean gain shape vector quantization; mean vectors; optimal bit allocation; optimal variable rate; rate distortion performance; shape vectors; simulation results; statistical dependence; Bit rate; Cost function; Distortion measurement; Encoding; Image coding; Lagrangian functions; Product codes; Rate-distortion; Shape; Vector quantization;

fLanguage

English

Journal_Title

Circuits and Systems for Video Technology, IEEE Transactions on

Publisher

ieee

ISSN

1051-8215

Type

jour

DOI

10.1109/76.544737

Filename

544737