ABSTRACT In this paper, a new switch median filter is presented for suppression of impulsive noise in image. The proposed filter is Modified Adaptive Center Weighted Median (MACWM) filter with an adjustable central weight obtained by partitioning the observation vector space. Dominant points of the proposed approach are partitioning of observation vector space using clustering method, training procedure using LMS algorithm then freezing weights in each block are applied to test image. The proposed method includes fuzzy clustering part for clustering the observed vector of each pixel into one of M mutually exclusive blocks. In the training phase, Least Mean Square (LMS) algorithm use to train center weight in each block then obtained weights used in testing phase. Final results shows better performance in the impulse noise reduction over standard images relative the median (MED) filter, the switching scheme I (SWM-I) filter, the signal dependent rank order mean (SD-ROM) filter, the tristate median (TSM) filter, the fast peer group filter (FPGF), the fuzzy median (FM) filter, the PFM filter and the adaptive center weighted median (ACWM) filter.

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