A noise-exclusive adaptive filtering framework for removing impulse noise in digital images

Abstract

A class of noise-exclusive adaptive filters for removing impulse noise from digital images is developed and analyzed in this brief. The filtering scheme is based on noise detection using a self-organizing neural network and noise excluding estimation. These filters suppress impulse noise effectively while preserving fine image details. Applications of the filters to several images show that their properties of efficient impulse noise suppression, edges and fine detail preservation, minimum signal distortion, or minimum mean square error are better than those of the traditional median-type filters.