Efficient impulse noise reduction via local directional gradients and fuzzy logic
Fuzzy Sets and Systems
Recent Literature Collected by Didier DUBOIS, Henri PRADE and Salvatore SESSA
Fuzzy Sets and Systems
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Switching-based filter based on Dempster's combination rule for image processing
Information Sciences: an International Journal
Efficient distortion reduction of mixed noise filters by neuro-fuzzy processing
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
An effective 2-stage method for removing impulse noise in images
Journal of Visual Communication and Image Representation
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A new impulse noise detector based on neuro-fuzzy methods is presented. The proposed detector comprises two identical neuro-fuzzy subdetectors combined with a decision maker. The internal parameters of the subdetectors are adaptively adjusted by training. Training of the subdetectors is accomplished by using a simple computer generated artificial image. The detector can be combined with any impulse noise removal operator. The operation of the detector is completely independent of the noise removal operator and it has no influence on the filtering behavior of the operator. Experimental results show that the proposed detector significantly reduces the distortion effects of any impulse noise removal operator even if the operator already has its own noise detector.