计算机应用 ›› 2005, Vol. 25 ›› Issue (10): 2336-2338.

• 图形图像处理 • 上一篇    下一篇

基于模糊粗神经网络的图像脉冲噪声滤除

张东波1,2，王耀南1   

  1. 1.湖南大学电气与信息工程学院； 2.湘潭大学信息工程学院
  • 收稿日期:1900-01-01 修回日期:1900-01-01 发布日期:2005-10-01 出版日期:2005-10-01
  • 基金资助:

    国家自然科学基金资助项目(60375001);;高等学校博士点基金资助项目(20030532004)

Filtering image impulse noise based on fuzzy rough neural network

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  1. 1.College of Electrical and Information Engineering,Hunan University,Changsha Hunan 410082,China;2.Institute of Information Engineering,Xiangtan University,Xiangtan Hunan 411105,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2005-10-01 Published:2005-10-01

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摘要： 为了获得在图像噪声滤除和细节保留两方面更好的兼顾与平衡，提出了一种兼有模糊化神经元和不可微粗神经元的模糊粗神经网络。采用融合了爬山法的遗传学习算法，增强了网络在学习过程中，特别是进化后期阶段对最优解的局部搜索能力。仿真表明，融合了模糊信息和粗糙集信息处理能力的模糊粗神经网络在图像融合滤波方面比BP网络和粗集神经网络具有更好的性能，是一种性能很好的混合智能神经网络。

关键词: 模糊粗神经网络, 图像融合, 遗传算法, 滤波

Abstract: A FRNN(Fuzzy Rough Neural Network) was introduced to keep up trade-off between noise attenuation and detail preservation in image processing.The FRNN is composed of fuzzy neurons and indifferentiable rough neurons.GA(Genetic Algorithm) which integrate mountain climbing is applied to tune the weight of the FRNN.The local search ability for optimum solution is improved in the later period of the learning process.The result of simulation indicates that the FRNN which integrate the ability to deal with fuzzy information and rough set information has better performance than BP network and RNN(Rough Neural Network) in image fusion for filtering.The FRNN is a sort of hybrid intelligent neural network which has good performance.

Key words: Fuzzy Rough Neural Network(FRNN), image fusion, genetic algorithm, filtering

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