Predictive classified vector quantization

Author

Ngan, King N. ; Koh, Hee C.

Author_Institution

Dept. of Electr. & Syst. Eng., Monash Univ., Vic., Australia

Volume

1

Issue

3

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

269

Lastpage

280

Abstract

A vector quantization scheme based on the classified vector quantization (CVQ) concept, called predictive classified vector quantization (PCVQ), is presented. Unlike CVQ where the classification information has to be transmitted, PCVQ predicts it, thus saving valuable bit rate. Two classifiers, one operating in the Hadamard domain and the other in the spatial domain, were designed and tested. The classification information was predicted in the spatial domain. The PCVQ schemes achieved bit rate reductions over the CVQ ranging from 20 to 32% for two commonly used color test images while maintaining the same acceptable image quality. Bit rates of 0.70-0.93 bits per pixel (bpp) were obtained depending on the image and PCVQ scheme used

Keywords

data compression; encoding; filtering and prediction theory; picture processing; Hadamard domain; bit rate reductions; classification information; color test images; predictive classified vector quantization; spatial domain; Bit rate; Decoding; Image coding; Image quality; Mean square error methods; Nearest neighbor searches; Systems engineering and theory; Table lookup; Testing; Vector quantization;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.148602

Filename

148602