Lossless image compression by using gradient adjusted prediction and Burrows-Wheeler transformation

Author

Ng, K.S. ; Cheng, L.M.

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, Hong Kong

Volume

45

Issue

2

fYear

1999

fDate

5/1/1999 12:00:00 AM

Firstpage

380

Lastpage

386

Abstract

In general text compression techniques cannot be used directly in image compression because the model of text and image are different. Previously, a new class of text compression, namely, the block-sorting algorithm which involves Burrows and Wheeler (1994) transformation (BWT) gave excellent results in text compression. However, if we apply it directly in image compression, the result is poor. Surprisingly, good results can be obtained if we employ a prediction model such as the one defined in the JPEG standard before the BWT algorithm. Thus, the predictive model plays a critical role in the compression process. To further improve the compression efficiency, we use the gradient adjusted prediction (GAP). Experimental results show that the proposed method is better than lossless JPEG and some LZ-based compression methods

Keywords

data compression; gradient methods; image coding; prediction theory; transform coding; transforms; BWT algorithm; Burrows-Wheeler transformation; JPEG standard; LZ-based compression method; block-sorting algorithm; compression efficiency; experimental results; gradient adjusted prediction; lossless JPEG method; lossless image compression; prediction model; text compression techniques; Compression algorithms; Data compression; Entropy coding; IEC standards; ISO standards; Image coding; Performance loss; Predictive models; Sorting; Transform coding;

fLanguage

English

Journal_Title

Consumer Electronics, IEEE Transactions on

Publisher

ieee

ISSN

0098-3063

Type

jour

DOI

10.1109/30.793423

Filename

793423