An effective image noise filtering algorithm using cellular automata

Cellular Automata is a methodology that uses discrete space to represent the state of each element of a domain and this state can be changed according to a transition rule. Image noise is unwanted information of an image and is translated into values which are getting added or subtracted to the true grey-level values. Noise can occur during image capture, transmission or processing and it may depend or may not depend on image content. CA can be successfully applied in image processing. This paper presents image noise filtering based on cellular automata, which can remove impulsive noise from corrupted image. Non-Uniform cellular automata rules are constructed to filter noise from both general images and medical images and the comparison shows that the filter based on cellular automata shows significant improvements over the traditional methods of filtering. First the concept of cellular automata is introduced, and then accordingly to the structure of the neighborhoods and the proposed model followed by the results.