Morphological Filtering Algorithm for Restoring Images Contaminated by Impulse Noise

Abstract

In this paper a methodology to restore gray scale images with pixels polluted by random impulsive noise is presented. Noise is discovered using a criterion based on the white top-hat by reconstruction. Pixels detected as corrupted are restored using an iterative morphological algorithm built with extensive and antiextensive morphological transformations. The proposal is compared with the rank ordered mean filter (ROM) and other morphological transformations reported in the current literature.