A method for estimation and filtering of Gaussian noise in images

A new approach to the restoration of images corrupted by Gaussian noise is presented. The proposed method combines a nonlinear algorithm for detail preserving smoothing of noisy data and a technique for automatic parameter tuning based on noise estimation. As a key feature, the method does not require any "a priori" knowledge about the amount of noise corruption. Experimental results show that the filtering performance of the proposed approach is very satisfactory.