Salt and pepper noise filtering with fuzzy-cellular automata

• A new image denoising algorithm is proposed to restore digital images corrupted by impulse noise.
• It is based on two dimensional cellular automata (CA) with the help of fuzzy logic theory.
• The algorithm describes a local fuzzy transition rule to filter image salt and pepper noises effectively.
• The proposed method removes the noise effectively even at noise level as high as 90%.

A new image denoising algorithm is proposed to restore digital images corrupted by impulse noise. It is based on two dimensional cellular automata (CA) with the help of fuzzy logic theory. The algorithm describes a local fuzzy transition rule which gives a membership value to the corrupted pixel neighborhood and assigns next state value as a central pixel value. The proposed method removes the noise effectively even at noise level as high as 90%. Extensive simulations show that the proposed algorithm provides better performance than many of the existing filters in terms of noise suppression and detail preservation. Also, qualitative and quantitative measures of the image produce better results on different images compared with the other algorithms.

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