Adaptive template filter method for image processing based on immune genetic algorithm  

作　　者：谭冠政 吴建华 范必双 江斌 

机构地区：[1]School of Information Science and Engineering,Central South University

出　　处：《Journal of Central South University》2010年第5期1028-1035,共8页中南大学学报（英文版）

基　　金：Project(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of China;Project (60874070) supported by the National Natural Science Foundation of China

摘　　要：To preserve the original signal as much as possible and filter random noises as many as possible in image processing,a threshold optimization-based adaptive template filtering algorithm was proposed.Unlike conventional filters whose template shapes and coefficients were fixed,multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method.The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods.The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover(IGAE) was used to optimize threshold t of the transformation function,and then combined with wavelet transformation to estimate noise variance.Multi-experiments were performed to test the validity of IGAE.The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods,IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.To preserve the original signal as much as possible and filter random noises as many as possible in image processing, a threshold optimization-based adaptive template filtering algorithm was proposed. Unlike conventional filters whose template shapes and coefficients were fixed, multi-templates were defined and the right template for each pixel could be matched adaptively based on local image characteristics in the proposed method. The superiority of this method was verified by former results concerning the matching experiment of actual image with the comparison of conventional filtering methods. The adaptive search ability of immune genetic algorithm with the elitist selection and elitist crossover （IGAE） was used to optimize threshold t of the transformation function, and then combined with wavelet transformation to estimate noise variance. Multi-experiments were performed to test the validity of IGAE. The results show that the filtered result of t obtained by IGAE is superior to that of t obtained by other methods, IGAE has a faster convergence speed and a higher computational efficiency compared with the canonical genetic algorithm with the elitism and the immune algorithm with the information entropy and elitism by multi-experiments.

关 键 词：image characteristic template match adaptive template filter wavelet transform elitist selection elitist crossover immune genetic algorithm 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]