Non-Linear Low-Level Image Processing Improvement by a Purposely Injection of Noise

Abstract

It is progressively realized that noise can play a constructive role in nonlinear formation processes. The starting point of the investigation of such useful noise effect has been the study of the Stochastic Resonance (SR) effect. The goal of this article is to propose a direct application of SR phenomenon in image processing, for the interest of SR in that domain is growing-up. As a prolongation of previous work already presented in the literature by author, we propose to quantitatively show that a purposely injection of a gaussian noise in a classical nonlinear image process, as image binarization, can play a constructive action. This work can also be interpreted as a first step for a better understanding of SR in image processing relating it to classical results obtained in a nonlinear signal processing framework for classical low-level image processing tool.