Adaptive template filter method for image processing based onimmune genetic algorithm

来源期刊：中南大学学报(英文版)2010年第5期

论文作者：谭冠政 吴建华 范必双 江斌

文章页码：1028 - 1035

Key words：image characteristic; template match; adaptive template filter; wavelet transform; elitist selection; elitist crossover; immune genetic algorithm

Abstract: 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.