An Effective Filtering Algorithm for Image Salt-Pepper Noises Based on Cellular Automata

For filtering image salt-pepper noises, a novel denoising algorithm based on cellular automata is proposed. First, the concept of cellular automata is introduced, then according to the salt-pepper noises´ feature, local transition function based on moore neighborhood is designed for denoising, finally, the denoising effect is evaluated by hamming distance. Compared with classical median filtering, the experimental results show that the new algorithm has better denoising effects, especially when noises density is bigger than 0.4, its hamming distance is 30% lower than that of classical algorithm.