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。
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.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第12期66-68,201,共4页
Computer Engineering and Applications
基金
江苏省自然科学基金(the Natural Science Foundation of Jiangsu Province of China under Grant No.BK2003017)。
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
dynamic kernel
fuzzy morphological associative memories
decomposition gray-scale images
color images
random noise
