| 用遗传算法确定马尔柯夫随机场的最佳参数 |
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| 引用本文： | 郑肇葆,郑宏.用遗传算法确定马尔柯夫随机场的最佳参数[J].武汉大学学报(信息科学版),2000,25(3):221-225. |
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| 作者姓名： | 郑肇葆 郑宏 |
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| 作者单位： | 1. 武汉测绘科技大学信息工程学院,武汉市珞喻路129号,430079
2. 武汉测绘科技大学光电工程学院,武汉市珞喻路129号,430079 |
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| 基金项目： | 国家自然科学基金资助项目 !编号 498710 67 |
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| 摘 要： | 对现有马尔柯夫随机场 (MRF)参数的解求方法作了详细分析。针对现有方法存在的缺点 ,提出基于遗传算法的MRF参数解求方法 ;分析讨论了求解的稳定性 ;并利用解的稳定性作为纹理分类的判据 ,作了航空影像纹理的分类实验。实验结果表明 ,求解的方法是正确的。用解的稳定性作为判据的纹理分类效果 ,通过对比实验证明是有效的。
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| 关 键 词： | 遗传算法 马尔柯夫随机场 最佳参数 纹理分类 |
| 修稿时间： | 1999-10-12 |
The Decision of the Optimal Parameters in Markov Random Fields of Images by Genetic Algorithm |
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| ZHENG Zhaobao,ZHENG Hong.The Decision of the Optimal Parameters in Markov Random Fields of Images by Genetic Algorithm[J].Geomatics and Information Science of Wuhan University,2000,25(3):221-225. |
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| Authors: | ZHENG Zhaobao ZHENG Hong |
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| Abstract: | This paper introduces the principle of genetic algorithm and the basic method for solving Markov random field parameters.The study in the past twenty years showed that Markov random field (MRF) is a powerful tool to discribe image features.Now MRF is often used in image texture classification.This is because image feature can be described quantificationally by a group of MRF parameters,and different MRF parameters represent different image textures.So the key problem of applying MRF to image texture classification is how to decide the optimal MRF parameters.Many Scientists have been studying the problem.They attempt to configure two or three pixels around a central pixel as group,which is called cliques.They think that image textures are configurations of these cliques,and each clique corresponds to a parameter.The value of the parameter reflects the attribute of the cliques corresponding to the parameter.The larger the value is,the more cliques an image texture contains.If the value is negative,it means that the cliques will restrain image textures.Virtually,the decision of the optimal parameters is to decide the optimal configuration of cliques.For a 256 level gray image,the number of configures may be 256 8(two_order MRF).The number is so large that it is difficult to find the optimal configuration.In addition,the textures of aerial images are too complex to be described by simple cliques.According to our study,they should be described by five_order MRF.In this case,the number of neighbors is 24,and each neighbor pixel corresponds to a parameter whose value reflects the relation between the neighbor and its central pixel.The relation can be expressed as a relation function about central pixels and their neighbors.Theoretically,parameter can be computed from the function by the least square method.But,for a 256 level gray image,because the gray values corresponding to two or three parameters in the function may be same or close,the function may have no solution.In order to solve the problem,this paper presents the genetic algorithm to decide optimal neighbors.Genetic algorithm is a global optimal algorithm.It has robust,fast and parallel features.This paper regards the sum of square of residuals as fitting function and discusses the detailed produce to solve MRF parameters by genetic algorithm,which includes encoding,decoding,crossover and mutation,etc.Experimental results are given to show the classification effectiveness of the method proposed in the paper. |
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| Keywords: | genetic algorithm Markov random field optimum parameter texture classification |
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