Title :
Attribute cluster network and fractal image compression
Author :
Wang, Chunmei ; Cheng, Qiansheng
Author_Institution :
Dept. of Inf. Sci., Beijing Univ., China
Abstract :
The greatest disadvantage of fractal image compression is the length of time it takes; so this paper advises using attribute cluster network (ACN) to reduce the time complexity. Using ACN can classify the feature vectors of domain blocks and range blocks, and the searching complexity can be reduced. Moreover, the weight values from ACN indicate the importance of all the points, and the new feature vectors can be got only by picking up more important points from a block, which will reduce the needed memory and improve encoding speed and clustering speed. Experiments show that combining the attribute cluster network and fractal block coding together costs less encoding time and clustering time than the other methods; that is to say, the chosen important points can replace the block itself properly
Keywords :
computational complexity; data compression; fractals; image classification; image coding; pattern clustering; search problems; attribute cluster network; clustering speed; domain blocks; encoding speed; feature vectors; fractal image compression; range blocks; searching complexity; time complexity; weight values; Block codes; Costs; Decoding; Fractals; Image coding; Image quality; Image resolution; Image restoration; Information science; Nearest neighbor searches;
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
DOI :
10.1109/ICOSP.2000.893410