A new model for impulse noise reduction with a recursive and noise-exclusive fuzzy switching median filter is proposed. The filter uses a S-type membership function for fuzzifying the noisy input variable and then estimates a correction label for it that aims at canceling the noisy effect. The fuzzification process provides better smoothing and generalization that improve the performance of the filter. The recursive and noise-exclusive operations further enhance the noise reduction capability of the filter. The recursive operation replaces the current pixel with the filtered pixel(s) and the noise-exclusive filtering uses only noise-free pixel(s) of the working window. The net effect of the filtering process thus preserves the sharp edges and fine details of the image in a more effective manner. The superiority of the proposed model to others in removing high density noise is established both quantitatively and qualitatively with various benchmarks and real-time test data sets. With the incorporation of the functionalities like fuzzy reasoning and noise-exclusive operations in the filtering process, the model becomes more efficient and fast. The applicability of the model thus opens ample scopes for hardware implementation in many electronics products that deal with images and videos.
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