自适应遗传优化在图像增强中的应用  

Application of Adaptive Genetic Algorithms in Image Fuzzy Enhancement

作　　者：李国[1,2] 龚志辉[1] 许宁 张一平[1] 王勃[1] 靳克强[1,3] 

机构地区：[1]解放军信息工程大学测绘学院 [2]解放军65015部队 [3]解放军96633部队

出　　处：《遥感信息》2011年第4期54-58,共5页Remote Sensing Information

摘　　要：本文以一种改进的模糊熵做遗传算法中个体进化的驱动力,利用Fibonacci数列对遗传算法的交叉概率及变异概率进行了自适应改进,达到了在模糊域中利用遗传算法增强图像的目的。实验结果表明该方法能有效改善图像的视觉效果,比传统增强方法具有更好的适应性。In this paper we apply the theory of fuzzy set in the image processing for image enhancement.Considering that the selecting optimum fuzzy parameter manually in the image enhancement can＇t satisfy the application＇s requirement,so in this paper the optimum fuzzy parameter is selected automatically by using genetic algorithms.Finally,a contrast experiment was made between the methods of linear enhancement and histogram equalization with the proposed one in the paper.The results show that the proposed method can improve the vision effect of image and more adaptive than traditional image enhancement methods.

关 键 词：图像增强 遗传算法 模糊熵 FIBONACCI数列 GRAY码 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]