An improved fast fractal image compression using spatial texture correlation

doi:10.1088/1674-1056/20/10/104202

Abstract This paper utilizes a spatial texture correlation and the intelligent classification algorithm (ICA) search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.

Keywords: fractal image compression texture features intelligent classification algorithm spatial correlation

Received: 02 March 2011
Revised: 06 May 2011
Accepted manuscript online:

PACS:	42.30.Va	(Image forming and processing)
	42.30.Wb	(Image reconstruction; tomography)
	87.57.C-	(Image quality)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 60573172 and 60973152), the Superior University Doctor Subject Special Scientific Research Foundation of China (Grant No. 20070141014), and the Natural Science Foundation of Liaoning Province of China (Grant No. 20082165).

Cite this article:

Wang Xing-Yuan(王兴元), Wang Yuan-Xing(王远星), and Yun Jiao-Jiao(云娇娇) An improved fast fractal image compression using spatial texture correlation 2011 Chin. Phys. B 20 104202

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