基于阿尔法均值算法和马氏距离的图像自适应滤波

Filter of the optical image based on alpha-trimmed mean filter and Mahalanobis distance

针对数字图像容易感染噪声的问题,提出一种基于阿尔法均值滤波算法和马氏距离的图像自适应滤波算法。该算法充分结合了阿尔法均值滤波器的优点和马氏距离的特性,首先利用阿尔法均值滤波器确定参考序列,然后计算参考序列与滤波窗口内比较序列之间的马氏距离,并根据距离的大小确定滤波窗口内各像素点的权系数,最后将加权结果作为滤波输出。实验结果表明:该算法对受到高斯噪声、椒盐噪声以及混合噪声感染的图像具有较好的滤波效果,同时可以较好地保持原始图像的细节信息。

It is easy for digital image to contain noise.To overcome this problem,an adaptive filter algorithm based on Alpha-trimmed mean filter and Mahalanobis distance is proposed.This algorithm combines the advantages of the Alpha-trimmed mean filter and the feature of the Mahalanobis distance.First,the reference sequence is obtained by the Alpha-trimmed mean filter.Then,the Mahalanobis distance between the reference sequence and the comparing sequence is calculated,which is used to determine the weight coefficient of the pixels in the filter window.Finally,the weighted result is taken as the filter output.The experiment results show that the filtering effect of the proposed algorithm is very high for the image containing Gaussian noise,salt and pepper noise or mixed noise,and can keep the details of the original image.