计算机工程与应用2011，Vol.47Issue(18)：191-194,4.DOI:10.3778/j.issn.1002-8331.2011.18.056
基于改进简化PCNN模型的椒盐噪声滤波方法
Filtering algorithm for salt and pepper nosie based on modified simplified PCNN model
摘要
Abstract
An adaptive median filter algorithm is proposed to slove the problem of the simplified Pulse Coupled Neural Network(PCNN) model in image filtering.At first, the simplified model is proved to fail to detect pepper noise using reductio Ad absurdum,then the model is improved by using the method of dividing and rule,finally the adaptive median filter algorithm is acheieved by detecting the pollution level, ascertaining the specific locations of noise points and determining the size of the median filtering window adaptively.Experimental results show that this algorithm improves the accuracy of noise detection and the fidelity of image filtering,and has a better performance on different noise densities.关键词
自适应中值滤波/脉冲耦合神经网络/椒盐噪声Key words
adaptive median filter/Pulse Coupled Neural Network(PCNN)/salt and pepper noise分类
信息技术与安全科学引用本文复制引用
蒋加伏,申静,朱德正..基于改进简化PCNN模型的椒盐噪声滤波方法[J].计算机工程与应用,2011,47(18):191-194,4.基金项目
湖南省自然科学基金(the Natural Science Foundation of Hunan Province of China under Grant No.10jj2050). （the Natural Science Foundation of Hunan Province of China under Grant No.10jj2050）
