Context models for palette images

Author

Ausbeck, Paul J., Jr.

Author_Institution

Dept. of Comput. Eng., California Univ., Santa Cruz, CA, USA

fYear

1998

fDate

30 Mar-1 Apr 1998

Firstpage

309

Lastpage

318

Abstract

A family of two dimensional context models appropriate for palette images is described. The models are designed for use with a binary arithmetic coder. A complete image encoder/decoder using three models from the family is disclosed. The new coder is compared against five alternate coding methods: JBIG bit plane coding, CALIC predictive coding, CALIC plus palette ordering, and two dictionary methods, GIF and PNG. The aggregate compression achieved by the new method on a corpus of fifteen palette images is 25% better than the best alternate method. The appropriateness of the corpus is validated by the similar aggregate compression achieved by the alternate methods even though compression varies widely from image to image. Remarkably, the new method achieves 20% better compression than a composite coder formed from the best alternate method for each image

Keywords

arithmetic codes; codecs; digital arithmetic; image coding; image colour analysis; piecewise constant techniques; 2D context models; CALIC predictive coding; GIF; JBIG bit plane coding; PNG; aggregate compression; binary arithmetic coder; color information; composite coder; dictionary methods; image encoder/decoder; lookup table; palette images; palette ordering; piecewise constant image model; Aggregates; Arithmetic; Color; Context modeling; Decoding; Dictionaries; Gray-scale; Image coding; Pixel; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Compression Conference, 1998. DCC '98. Proceedings

Conference_Location

Snowbird, UT

ISSN

1068-0314

Print_ISBN

0-8186-8406-2

Type

conf

DOI

10.1109/DCC.1998.672159

Filename

672159