Fractal image compression based on fuzzy theory

作     者：Berthe Kya and Yang YangInformation Engineering School, University of Science and Technology Beijing, Beijing 100083, China (Received 2001-11-13) 

作者机构：Information Engineering School University of Science and Technology Beijing Beijing 10083 China *** 

出 版 物：《Journal of University of Science and Technology Beijing》 (北京科技大学学报（英文版）)

年 卷 期：2002年第9卷第3期

页      面：228-232页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

主　　题：fractal compression fractal optimization fuzzy logic c-mean clusteringalgorithm hybrid fractal-fuzzy compression 

摘      要：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.