提出了一种基于噪声邻域结构分析的脉冲噪声去除方法。对脉冲耦合神经网络点火形式进行修改,通过对含噪图像进行点火,获得点火级别图像并定位噪声。对噪声点邻域结构进行分析,对不同邻域结构的噪声点进行分类。对邻域结构简单的噪声点采用中值滤波进行去噪;对邻域结构复杂的噪声点提出了一种基于区域隶属度的去噪方法。实验结果表明所提出的算法可以有效抑制图像中的脉冲噪声,并可以保留图像的边缘细节。
A new method is proposed for impulse noise denoising which is based on Pulse Coupled Neural Network(PCNN)and the analysis of the neighborhood structure of the noise point. PCNN is used to ignite the noise image to obtain a firing grade image. Noise points are classified according to the difference of their neighborhood structure in the firing grade image. Median Filter is applied to the noise with simply neighborhood structure. To eliminate the noises with complex neighborhood structure, an approach is introduced based on regional membership. The results show the new method can restrains noise effectively and keep the edges detail as well.