Iterative Edge-Preserving Adaptive Wiener Filter for Image Denoising

In this paper, an image denoising method for noisy image corrupted by additive white noise is proposed. It is well known that the Adaptive Wiener Filter (AWF) is suitable for such denoising. However, some noises remain in the image processed by AWF. In order to improve the performance of the AWF, an iterative algorithm is derived. To prevent original image signal loss, a weighting parameter is used for the noise variance estimate and a technique adjusting the filter kernel is employed. Compared to the conventional AWF, the proposed filter provides better edge performance.