A novel fuzzy color median filter based on an adaptive cascade of fuzzy inference systems
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
On the design of neighboring fuzzy median filter for removal of impulse noises
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
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Median filter was once the most popular nonlinear filter for removing impulse noise because of its good denoising power. In this paper, we present a novel adaptive fuzzy median filter to the restoration of salt & pepper impulse noise-corrupted image, which is particularly effective at removing highly impulsive noise. First we estimate noise level based on fussy set theory, then process the corrupted pixel or extend the size of filtering window, at last get the appropriate median value to replace the noisy pixel. The proposed filter has the benefits that it is simple and it assumes no a priori knowledge of specific input image. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement problems. Experimental results have shown that the proposed algorithm works very well not only for images with lower percentage of impulse noises but also with higher percentage of impulse noise.