Fractal image encoding with flexible classification sets

作     者：Jianji Wang Xuguang Lan Yuehu Liu Nanning Zheng 

作者机构：Institute of Artificial Intelligence and RoboticsXi’an Jiaotong University 

出 版 物：《Chinese Science Bulletin》 (Chin. Sci. Bull.)

年 卷 期：2014年第59卷第14期

页      面：1597-1606页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统] 

基　　金：supported by the National Basic Research Program of China(2010CB327902) the National Natural Science Foundation of China(61231018) 

主　　题：分形图像编码 分类策略 Pearson相关系数 设置 分形图像压缩 图像质量 变量表达式 FIC 

摘      要：Fractal image compression(FIC)technology is an interesting attempt at structure similarity-based image *** has been widely applied in many fields such as image encryption,image retrieval,image sharpening,and pattern ***,overlong encoding time is the main difficulty for the application of *** this paper,a new FIC speedup algorithm is proposed with two ***,the simplified statistical variable expressions can speed up encoding twice more than the baseline fractal compression(BFC)without loss of image quality corresponding to ***,based on the fact that the affine self-similarity is equivalent to the absolute value of Pearson’s correlation coefficient,a new block classification strategy with flexible classification sets is proposed to speed up encoding *** experiment results and theoretical analysis show that the proposed scheme achieves high performance in both image quality preservation and encoding efficiency.