Representation of digital image by fuzzy neural network
Fuzzy Sets and Systems
Support vector regression based image denoising
Image and Vision Computing
Efficient impulse noise reduction via local directional gradients and fuzzy logic
Fuzzy Sets and Systems
A novel evolutionary approach to image enhancement filter design: method and applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Generating fuzzy edge images from gradient magnitudes
Computer Vision and Image Understanding
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This paper presents a new fuzzy-logic-control based filter with the ability to remove impulsive noise and smooth Gaussian noise, while, simultaneously, preserving edges and image details efficiently. To achieve these three image enhancement goals, we first develop filters that have excellent edge-preserving capability but do not perform well in smoothing Gaussian noise. Next, we modify the filters so that they perform all three image enhancement tasks. These filters are based on the idea that individual pixels should not be uniformly fired by each of the fuzzy rules. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement problems. These experimental results demonstrate the speed, filtering quality, and image sharpening ability of the new filter