计算机科学 ›› 2011, Vol. 38 ›› Issue (1): 256-258.

• 人工智能 • 上一篇    下一篇

结合遗传优化的多结构多尺度形态学消噪

王媛妮,葛非   

  1. (中国地质大学计算机学院 武汉430074);(华中师范大学计算机系 武汉430079)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(No. 40802082),中央高校基本科研业务费专项资金(No.CUG100707)资助。

Multi-structure, Multi-scale Morphology De-noising Combination of Genetic Optimization

WANG Yuan-ni,GE Fei   

  • Online:2018-11-16 Published:2018-11-16

摘要: 传统的形态滤波以及广义形态滤波、自适应加权广义滤波、基于多结构元素的广义形态滤波、基于多方向的广义滤波和基于多尺度的广义滤波在考虑形态学滤波时基本上只兼顾到某一方面或者说只对某一方面的不足进行了改进,不论哪一种滤波方式都没有完全消除噪声。提出了一种基于自适应遗传算法的多结构多尺度形态学滤波方法,主要考虑了滤波窗口的大小、结构元素的种类和方向以及结构元素的优化选择问题,采用遗传算法对结构元素进行优化,并考虑到遗传算法自身的收敛性,采用了保留精英的策略,另外考虑到遗传算法参数的选择问题采用了自适应策略。同时,结合自适应加权广义形态滤波的思想构建基于遗传优化的多结构多尺度自适应加权形态滤波器,滤波效果比传统的形态滤波、广义形态滤波及在此基础上改进的滤波方法效果均好。

关键词: 形态学,去噪,遗传算法,自适应

Abstract: The traditional morphological filter, generalized morphological filter, adaptive weighted generalized filtering,generalized morphological filter of the multi structure elements or multi-directional or multi scale, all basically considering only one aspect, or improving the lack of only one aspect, regardless of what kind of filtering method that does not completely eliminate the noise. This paper presented a genetic algorithm based on adaptive multi scale multi structural morphological filtering method,the main consideration of the filtering window size,type and orientation of structural elements, as well as structural elements of the optimization of selection, using genetic algorithms to optimize the structural elements, and taking into account the convergence of genetic algorithm itself, using a strategy to retain the elite, while considering the choice of genetic algorithm parameters using adaptive strategies. At the same time, combined with the ideas of adaptive weighted generalized morphological filter to build the structure based on genetic optimization of multistructure,multi-scale adaptive weighted morphological filter,filter effects are better than the traditional morphological filter, the generalized morphological filter and others filters improved based on it.

Key words: Morphology,De-noising,Genetic algorithm,Adaptive strategy

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