Morphological Filtering Algorithm for Restoring Images Contaminated by Impulse Noise

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 antiex- tensive morphological transformations. The proposal is compared with the rank ordered mean filter (ROM) and other morphological transformations reported in the current literature.