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Diffusion Scheme for Noise Reduction Using Cellular Automata

Cellular automata is a methodology that uses a discrete space to represents the state of each element of a domain, and this states can be changed according to a transition rule. In this work we use cellular automata to represent a digital image and to develop new diffusion scheme in a way to reduce the noise of the image. Then, the processed image will be converted in a binary one to perform segmentation. The main contribution is the fact that the proposed diffusion method works well in images with high noise intensity and the computational cost is small. We apply the methodology for medical images segmentations.