一种基于灰色关联的去椒盐噪声滤波算法

A filter approach for removal of salt and pepper noise based on grey relevance

利用灰色关联理论结合开关滤波策略的思想,提出了一种基于灰色关联的去椒盐噪声算法。算法采用开关策略,对于噪声点,选取3×3滤波窗口内的非噪声像素,利用灰色关联度计算各像素的加权值,将各非噪声像素加权后替换噪声点像素值,得到滤波图像。仿真实验证实,该算法不仅有效抑制了图像中的椒盐噪声,而且较好地保持了图像的边缘细节,滤波效果明显优于传统的滤波算法。

Based on the grey relevance theory and the idea of switching filter,an algorithm for removing salt and pepper noise based on grey relation is proposed. The algorithm uses switching strategy,for the noise point,selects the non-noise pixels in the filtering window with size of 3 X3,calculated the weighting coefficient of each pixel by grey value,and used the non-noise pixel weighted to replace the noise pixels.The simulation results show that the algorithm not only suppresses the salt and pepper noise in the image,but also maintains the edge detail of the image,and the filtering effect is better than the traditional filtering algorithms.