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Impulse noise corrupts the image when it is sensing from a malfunctioning camera, storing in a fault memory or sending through a
noisy channel. As images are giving useful information in every field, image denoising plays a key role in image processing. Median filters
are preferred for removal of impulse noise. Existing methods suppress noise randomly without considering whether the pixel is â€œnoisyâ€ or not.
This paper proposes a method for effective noise suppression by understanding uncertainties in noisy image. There are two stages in this
method. First stage identifies the corrupted pixels via uncertainty based detector where as second stage suppresses the noise candidates by
using weighted fuzzy mean filter compared with the traditional switched hashing filters. The proposed method provides good results
subjectively and objectively. As the proposed filter can restore the image with good detail preservation at a high noise level, great
improvement results in image denoising.
keywords: Cloud model (CM), image denoising, impulse noise, median filter, weighted fuzzy mean filter, uncertainties, peak signal to
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