Impulse Noise Removal Based on Adaptive Multi-directional Weighted Mean Filter

In this paper, a new adaptive multi-directional weighted mean filter for removing salt-and-pepper noise is proposed. The new filter firstly introduces a variance parameter to judge the gray level difference between the current pixel and its neighborhood pixels and then designs the noise detector by combining the variance parameter and the gray level extreme. After noise detection, the new filter restores the noise corrupted pixels based on the multi-directional image information, which firstly adaptively selects the optimal filtering window and direction template and then replaces the gray level of each noise corrupted pixel by the weighted mean gray level of the pixels on the optimal template. Experimental results show that the proposed filter outperforms many existing main filters in terms of image denoising and detail preservation.