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Image denoising is one of the preliminary steps in image processing methodsin which the presence of noise can deteriorate the image quality. To overcomethis limitation, in this paper a improved two-stage fuzzy filter is proposedfor filtering salt and pepper noise from the images. In the first-stage, thepixels in the image are categorized as good or noisy based on adaptivethresholding using type-2 fuzzy logic with exclusively two different membershipfunctions in the filter window. In the second-stage, the noisy pixels aredenoised using modified ordinary fuzzy logic in the respective filter window.The proposed filter is validated on standard images with various noise levels.The proposed filter removes the noise and preserves useful imagecharacteristics, i.e., edges and corners at higher noise level. The performanceof the proposed filter is compared with the various state-of-the-art methods interms of peak signal-to-noise ratio and computation time. To show theeffectiveness of filter statistical tests, i.e., Friedman test andBonferroni-Dunn (BD) test are also carried out which clearly ascertain that theproposed filter outperforms in comparison of various filtering approaches.

Improved Adaptive Type-2 Fuzzy Filter with Exclusively Two Fuzzy Membership Function for Filtering Salt and Pepper Noise