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The most median-based de noising methods works fine for restoring the imagescorrupted by Randomn Valued Impulse Noise with low noise level but very poorwith highly corrupted images. In this paper a directional weighted minimumdeviation (DWMD) based filter has been proposed for removal of high randomvalued impulse noise (RVIN). The proposed approach based on Standard Deviation(SD) works in two phases. The first phase detects the contaminated pixels bydifferencing between the test pixel and its neighbor pixels aligned with fourmain directions. The second phase filters only those pixels keeping othersintact. The filtering scheme is based on minimum standard deviation of the fourdirectional pixels. Extensive simulations show that the proposed filter notonly provide better performance of de noising RVIN but can preserve moredetails features even thin lines or dots. This technique shows betterperformance in terms of PSNR, Image Fidelity and Computational Cost compared tothe existing filters.

A Novel Directional Weighted Minimum Deviation (DWMD) Based Filter for Removal of Random Valued Impulse Noise