Conditional entropy-constrained trellis-coded RVQ with application to image coding

Author

Khan, Mohammad A.U. ; Smith, Mark J T ; McLaughlin, Steven W.

Author_Institution

Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

7

Issue

3

fYear

2000

fDate

3/1/2000 12:00:00 AM

Firstpage

49

Lastpage

51

Abstract

This paper introduces an extension of conditional entropy-constrained RVQ (CEC-RVQ) that embodies trellis-coded quantization. The method, which we call conditional entropy-constrained trellis-coded residual vector quantization (CEC-TCRVQ), quantizes a supervector (made from a large number of neighboring vectors) to better extract the two-dimensional (2-D) correlation present in real images. Simulation results indicate that CEC-TCRVQ provides 0.3-0.4 dB improvement over CEC-RVQ for the 4/spl times/4 vector case and 1.3 dB improvement for the 8/spl times/8 case.

Keywords

data compression; entropy codes; image coding; trellis codes; vector quantisation; 2D correlation; CEC-RVQ; CEC-TCRVQ; conditional entropy-constrained RVQ; image coding; image compression; residual vector quantization; simulation results; supervector quantization; trellis-coded RVQ; trellis-coded quantization; Computational modeling; Entropy; Image coding; Lagrangian functions; Mirrors; Rate-distortion; Shape; Speech; Two dimensional displays; Vector quantization;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/97.823522

Filename

823522