Image Denoising Based on Non-local Means with Wiener Filtering in Wavelet Domain
Lin Li, Kong Lingfu · 2009
Image denoising is a significant inverse problem of image processing and an important image pretreatment. The performance of image denoising is improved by using some statistic characteristics of natural image. In this paper, we combine the extensive self-similarity of images in non-local means algorithm with the minimum mean square error of Wiener filtering in wavelet domain, and then propose an image denoising algorithm based on the non-local means with Wiener filtering in wavelet domain. The experimental results demonstrate that one can get denoised image with higher subjective visual quality and peak signal to noise ratio based on the proposed algorithm.