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Fractal image compression based on fuzzy theory
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作者 Berthe Kya and Yang YangInformation Engineering School, University of Science and Technology Beijing, Beijing 100083, China (Received 2001-11-13) 《Journal of University of Science and Technology Beijing》 CSCD 2002年第3期228-232,共5页
Though progress has been made in fractal compression techniques, the longencoding times still remain the main drawback of this technique, which results from the need ofperforming a large number of range-domain matches... Though progress has been made in fractal compression techniques, the longencoding times still remain the main drawback of this technique, which results from the need ofperforming a large number of range-domain matches. The total encoding time is the sum of the timerequired to perform each match. In order to make this method more efficient in practical use, thefuzzy theory based on feature extraction of the projection and normalized codebook method has beenprovided to optimize the encoding time, based on the c-means clustering approach. The results of theimplementation of Rate Mean Square (RMS), Peak signal noise ratio (PSNR) and the encoding time ofthis proposed method have been compared to other methods like the Feature Extraction andSelf-orgarnization methods to show its efficiency. 展开更多
关键词 fractal compression fractal optimization fuzzy logic c-mean clusteringalgorithm hybrid fractal-fuzzy compression
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