A Gradient-based Adaptive Nonlocal Means Algorithm for Image Denoising

In this paper, a modified adaptive nonlocal means (ANLM) filter is investigated for image denoising by introducing the image gradient into the classical nonlocal means filter. The proposed algorithm takes the orientation of matching neighborhood into consideration and can adaptively select the filtering parameter based on image gradient. Moreover, the symmetry or approximate symmetry of some filtered images is also considered. Therefore, comparing with the classical nonlocal means filter, the new method can exploit much more similar pixels. The proposed approach is applied to several real images corrupted by white Gaussian noise with different standard deviation. The comparative experimental results show that the improved ANLM filter obtains superior denoising performance.