Abstract

A new adaptive weight algorithm is developed for the removal of salt and pepper noise. It consists of two major steps, first to detect noise pixels according to the correlations between image pixels, then use different methods based on the various noise levels. For the low noise level, neighborhood signal pixels mean method is adopted to remove the noise, and for the high noise level, an adaptive weight algorithm is used. Experiments show the proposed algorithm has advantages over regularizing methods in terms of both edge preservation and noise removal, even for heavily contaminated image with noise level as high as 90%, it still can get a significant performance.

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