Image Denoising by Linear Regression on Non-Local Means Algorithm

Abstract

Non-Local Means (NL-Means) algorithm which removes the noise from the image have been used in the field widely due to its good performance especially for MR images. Its main idea is using all the pixels which are local and non-local in an image and taking weighted averaging of all values. One negative side of this method is that it considers all pixels in the image without looking at their similarity. This paper proposes a NL-Means algorithm with pixel selection by applying linear regression analysis using root mean squared error (RMSE) value. After regression analysis, RMSE of the neighborhoods is used to exclude non-similar pixels during noise removal. Lastly, obtained results are evaluated by quantitative and qualitative methods.