基于微分进化算法的图像增强方法
首发时间:2009-05-20
摘要:图像增强处理中,Tubbs曾将几种常用的非线性变换函数表示成一个归一化的非完全Beta函数,进行图像增强方而的研究,但确定Beta函数的参数仍是一个复杂的问题。现将微分进化算法应用到图像的增强处理中,利用微分进化算法的快速搜索能力,对给定的测试图像,自适应地变异、搜索、直至最终确定变换函数的最佳参数 , 值,从而实现图像的自适应增强。与穷举法相比,大大节约了求解的时间和计算的复杂度,提供了一个解决图像增强方而问题的途径。通过对视频图像的仿真实验可以看出上述方法的有效性。
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Method of Image Enhancement Based on Differential Evolution Algorithm
Abstract:In image enhancement, Tubbs proposed a normalized incomplete Beta function to represent the four kinds of non-linear transform functions most commonly used. But how to adaptively define the coefficients of the Beta function is still a problem. Applying the Differential Evolution Algorithm in one image enhancement, we utilize the quickly search ability of the algorithm, adaptive variation .search .at last searches the optimal of suboptimal coefficients. It is largely saved time of acquired answer and compute complexity, therefore it is an efficient approach of image enhancement. Compared with the common image adjustment approach, our method is more efficient and powerful.
Keywords: Image enhancement Differential Evolution Algorithm Crossover adaptive mutation
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