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模糊形态联想记忆网络抗随机噪声研究及应用
引用本文:吴锡生,王宇辉,王士同.模糊形态联想记忆网络抗随机噪声研究及应用[J].计算机工程与应用,2007,43(12):66-68,201.
作者姓名:吴锡生  王宇辉  王士同
作者单位:江南大学,信息工程学院,江苏,无锡,214122
摘    要:利用灰度图像分解的思想,结合模糊形态联想记忆网络的方法,提高了模糊形态联想记忆网络对随机噪声的抗噪能力。成功地解决了灰度图像在含有随机噪声时的模糊联想记忆问题,并把该方法推广到对彩色图像的处理,从而给出了一种较好地恢复含噪灰度图像和彩色图像的途径。通过实验,验证了该方法的良好性能,取得了较理想的结果。

关 键 词:动态核  模糊形态联想记忆  灰度图分解  彩色图像  随机噪声
文章编号:1002-8331(2007)12-0068-03
修稿时间:2006-09

Research on fuzzy morphological associative memories against random noise
WU Xi-shen,WANG Yu-hui,WANG Shi-tong.Research on fuzzy morphological associative memories against random noise[J].Computer Engineering and Applications,2007,43(12):66-68,201.
Authors:WU Xi-shen  WANG Yu-hui  WANG Shi-tong
Affiliation:School of Information Engineering, Southern Yangtze University,Wuxi, Jiangsu 214122, China
Abstract:A method to improve the competence of fuzzy morphological associative memories against random noise is presented, through the decomposition of gray-scale images,combining the method of fuzzy morphological associative memories.With the method,the auto-association and recognition of gray-scale images with random noise is settled.Meanwhile,this method has been extended to the settlement of the case of color image.Accordingly,a better way to resume gray-scale images and color images with noise is offered.Our experimental results here demonstrate the effectiveness of this approach.
Keywords:dynamic kernel  fuzzy morphological associative memories  decomposition gray-scale images  color images  random noise
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