Near-lossless image compression: minimum-entropy, constrained-error DPCM

Author

Ke, Ligang ; Marcellin, Michael W.

Author_Institution

Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA

Volume

7

Issue

2

fYear

1998

fDate

2/1/1998 12:00:00 AM

Firstpage

225

Lastpage

228

Abstract

A near-lossless image compression scheme is presented. It is essentially a differential pulse code modulation (DPCM) system with a mechanism incorporated to minimize the entropy of the quantized prediction error sequence. With a “near-lossless” criterion of no more than a d gray-level error for each pixel, where d is a small nonnegative integer, trellises describing all allowable quantized prediction error sequences are constructed. A set of “contexts” is defined for the conditioning prediction error model and an algorithm that produces minimum entropy conditioned on the contexts is presented. Finally, experimental results are given

Keywords

data compression; differential pulse code modulation; error analysis; image coding; minimum entropy methods; prediction theory; quantisation (signal); algorithm; conditioning prediction error model; constrained-error DPCM; contexts; differential pulse code modulation; experimental results; gray-level error; minimum-entropy; near-lossless image compression; nonnegative integer; pixel; quantized prediction error sequence; trellises; Biomedical imaging; Context modeling; Entropy; Image coding; Image reconstruction; Medical diagnostic imaging; Modulation coding; Predictive models; Pulse modulation; Quantization;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.660999

Filename

660999