严重椒盐噪声污染图像的非线性滤波算法

针对灰度图像的椒盐噪声滤波问题，提出一种保细节的非线性滤波算法。利用局部统计信息，首先将图像像素点粗分为信号点、可能的正噪声点和可能的负噪声点3类，建立噪声标矩阵；然后再根据噪声标记矩阵的局部统计信息，将可能的噪声点细分为信号点、噪声点和不确定点3种类别，并分别采用不同的方法进行滤波，以保留更多的图像细节。结果表明，本文算法在去噪能力、自适应性以及保留细节等方面都明显比其它4种算法强，尤其是对于噪声高度污染图像的情况。

A Nonlinear Algorithm for the Removal of Salt and Pepper Noise from Highly Corrupted Images

A nonlinear filtering algorithm was presented to remove salt and pepper noise from gray-scale image while preserving details.Utilizing the statistical information in a local window of the image,each pixel is classified roughly to be signal pixel,possible positive noise pixel and possible negative noise pixel,and the noise labeling matrix is built.Then the possible noise pixels are subdivided into signal pixels,noise pixels and uncertain pixels according to the statistical information of the noise labeling matrix.Different filtering schemes are employed for different kind of pixels to preserve the image details.Comparing experiments are also done for five different filtering algorithms include the algorithm presented in this paper.The simulation results show that our algorithm outperforms the other four algorithms in the aspects of filtering ability,adaptability and details preserving ability,especially for highly corrupted cases.