DocumentCode :
384295
Title :
Wavelet-based image coding using fuzzy inference and adaptive quantization
Author :
Hsieh, Ming-Shing ; Tseng, Din-Chang
Author_Institution :
Inst. of Comput. Sci. & Electron. Eng., Nat. Central Univ., Chung-li, Taiwan
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
265
Abstract :
A class of image compression algorithms has been developed for exploiting dependencies between the hierarchical wavelet coefficients using zerotrees. The paper deals with a fuzzy inference filter for image entropy coding by choosing significant coefficients and zerotree roots in the higher frequency wavelet subbands. Moreover, an adaptive quantization is proposed to improve the coding performance. Evaluating with the popular images, the proposed approach is comparable or superior to most state-of-the-art coders.
Keywords :
data compression; entropy; filtering theory; fuzzy logic; image coding; quantisation (signal); wavelet transforms; adaptive quantization; coding performance; fuzzy inference; fuzzy inference filter; hierarchical wavelet coefficients; image compression algorithms; image entropy coding; wavelet-based image coding; zerotrees; Clustering algorithms; Compaction; Computer science; Entropy coding; Finite impulse response filter; Frequency; Image coding; Inference algorithms; Information management; Quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1048289
Filename :
1048289
Link To Document :
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