基于像素点聚类分离的滤波算法

为了提高受随机值脉冲噪声污染的图像的滤波效果，提出了一种新的滤波算法。对噪声图像进行初步滤波，分辨出图像中比较明显的噪声；根据图像局部像素点的相似性和噪声点的孤立性，计算出噪声图像的相关矩阵；运用模糊C均值聚类算法对所求相关矩阵进行迭代聚类，分离出噪声点和正常像素点；对噪声点进行中值滤波。实验结果表明，与传统算法相比，该算法能更好地滤除噪声点，保护了更多的图像细节，具有良好的滤波效果。

Filtering algorithm based on pixel clustering separation

In order to improve the filtering effect of noise images, a new filtering algorithm is proposed. The obvious noise of the noise image is distinguished in the preliminary filtering. The correlation matrix of the noise image is calculated according to the similarities of the local pixels and the isolations of the noise points, and then noise points and normal pixel are separated by using the fuzzy c-means algorithm to cluster the correlation matrix iteratively. The noise points are filtered with median filter algorithm. Simulation results indicate that this algorithm can not only accurately filter more noise points and protect more image details, but also get better filtering effect than traditional algorithms mentioned in this paper.