Title :
A Fast Matching Algorithm Based on Adaptive Classification Scheme
Author :
Fan, Ce ; Liu, Peihua
Author_Institution :
Fac. of Inf. Sci. & Technol., Guangdong Univ. of Foreign Studies
Abstract :
This paper purposes a novel matching algorithm for image encoding using adaptive classification scheme (ACS) in fractal image compression. It works based on standard deviation (STD) between range blocks and domain blocks. In this paper, there are two main work i) the threshold is set to be the ratio of the STD difference and made adaptive ii) we enhance Tongs STD search algorithm by introducing a domain ACS and classification algorithm, so that domain blocks being matched with similar STD values are located directed. And finally we present experimental results which show the efficiency of the proposed scheme. It improves the original Tongs STD algorithm without any loss in the reconstructed image quality, and the encoding time is decreased greatly based on the ACS. It is very efficient to obtain a no search scheme for range-domain match. Also, experimental results shows that images either complex or simple can be encoded in less than 10s
Keywords :
data compression; image classification; image coding; adaptive classification; fast matching algorithm; fractal image compression; image encoding; standard deviation; Classification algorithms; Cognitive informatics; Fractals; Image coding; Image processing; Image quality; Image reconstruction; Partitioning algorithms; Pixel; Redundancy; Adaptive Classification; Compression; Encoding; Similarity; Standard Deviation;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365543
