Filtering images contaminated with pep and salt type noise with pulse-coupled neural networks  

作　　者：ZHANGJunying LUZhijun SHILin DONGJiyang SHIMeihong 

机构地区：[1]SchoolofComputerScienceandEngineering,XidianUniversity,Xi'an710071,China [3]InstituteofElectronicsEngineering,XidianUniversity,Xi'an710071,China [4]SchoolofComputerScience,Xi'anScienceandTechnologyUniversity,Xi'an710048,China [5]SchoolofComputerScienceandEngineering,XidianUniversity,Xi'an710071,China//InstituteofElectronicsEngineering,XidianUniversity,Xi'an710071,China

出　　处：《Science in China(Series F)》2005年第3期322-334,共13页中国科学（F辑英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.60371044,60071026);the National Visiting Scholar Fund

摘　　要：Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron can capture its adjacent neurons to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a very good mechanism for image filtering when the image is damaged with pep and salt (PAS) type noise. An adaptive filtering method, in which the noisy pixels are first located and then filtered based on the output of the PCNN, is presented. The threshold function of a neuron in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise contaminated image respectively. The filtered image has no distortion for noisy pixels and only less mistiness for non-noisy pixels, compared with the conventional window-based filtering method. Excellent experimental results show great effectiveness and efficiency of the proposed method, especially for heavy-noise contaminated images.

关 键 词：image filtering pulse coupled neural networks fire of a neuron firing instant. 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]