Applied Mathematics & Information Sciences

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Images and pictures are required as sources of information for analysis and interpretation in various fields such as medicine, remote sensing etc., These images are prone to impulse noise as a result of errors in the image acquisition or transmission process. Thus, the output image needs to be enhanced. This work presents a novel fuzzy logic based impulse detector to guide the noise filter to improve their performance and to restore images corrupted by impulse noise. The proposed scheme is based on the sugeno type and its parameters are trained using genetic algorithm. Simulation results show that this proposed detector can be effectively used to improve the performance of the impulse noise filter.

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