Stochastic Image Denoising using Minimum Mean Squared Error (Wiener) Filtering

Digital images and video used for various tasks is often subject to distortion and noise. When information is known about the distortions and noise introduced into the image, their effects can be at least partially negated through image restoration techniques. In this paper, we explore the derivation of the inverse filter and the Wiener filter. We look and their efficacy in restoring images corrupted by various types of degradation and noise. We have also investigated the ability to estimate the parameters of unknown noise by analyzing the histograms of uniform regions of interest in the degraded image.