Adaptive filtering method for images based on pulse-coupled neural network

Abstract

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An adaptive filter was proposed to detect and remove pepper and salt noise in an image based on Pulse Coupled Neural Network(PCNN) firing matrix.The PCNN was simplified and a unidirectional decaying threshold was proposed to avoid complex parameter selection and improve processing speed.The noise-polluted pixels were detected through analyzing the PCNN firing matrix,and then only the noisy pixels were filtered by a median filter while protecting image edges and details.The window size of the filter and the filtering time were adaptively determined by calculating the noise intensity of the contaminated image.The experimental results show that the proposed method performs better in removing noise while conserving detailed information than traditional filters do.