Handbook of Image and Video Processing
Handbook of Image and Video Processing
An Effective Filtering Algorithm for Image Salt-Pepper Noises Based on Cellular Automata
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 3 - Volume 03
Image processing using 3-state cellular automata
Computer Vision and Image Understanding
Additive noise removal using a novel fuzzy-based filter
Computers and Electrical Engineering
Structure and reversibility of 2D hexagonal cellular automata
Computers & Mathematics with Applications
Denoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filter
Pattern Recognition Letters
Efficient removal of impulse noise from digital images
IEEE Transactions on Consumer Electronics
Salt-and-pepper noise detection and reduction using fuzzy switching median filter
IEEE Transactions on Consumer Electronics
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Selective removal of impulse noise based on homogeneity level information
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization
IEEE Transactions on Image Processing
Training cellular automata for image processing
IEEE Transactions on Image Processing
Adaptive median filters: new algorithms and results
IEEE Transactions on Image Processing
Direction based adaptive weighted switching median filter for removing high density impulse noise
Computers and Electrical Engineering
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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.