Title :
A Fractal Image Compression Method Based on Block Classification and Quadtree Partition
Author :
Qin, Feng-Qing ; Min, Jun ; Guo, Hong-Rong ; Yin, De-hui
Author_Institution :
Dept. of Comput. Sci. & Technol., Yibin Univ., Yibin, China
fDate :
March 31 2009-April 2 2009
Abstract :
Under the precondition of guaranteeing the compression ratio, in order to improve the quality of the reconstructed image, a fractal image compression method based on block classification and quadtree partition is proposed. Firstly, the image is partitioned through adaptive quadtree method. Then, the subblocks in each level are classified, according to the statistical characteristics of the subblocks. The experimental results show that the reconstructed image gained by our method has higher peak signal-to-noise ratio (PSNR) and better visual effect than the adaptive quadtree partition method, meanwhile the compression ratio is increased.
Keywords :
data compression; image coding; image reconstruction; pattern classification; quadtrees; statistical analysis; adaptive quadtree partition method; block classification; compression ratio; fractal image compression method; higher peak signal-to-noise ratio; image reconstruction quality; statistical characteristic; visual effect; Biomedical engineering; Biomedical imaging; Computer science; Educational institutions; Fractals; Image coding; Image reconstruction; PSNR; Pixel; Visual effects; Fractal; Image compression;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.230
