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Impulsive noise cleaning by smoothing of images using fast median method (FMM)

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The objective of this paper is to propose new approaches FMM for removing impulsive noise in images so as to smooth the image for further processing. The various methods like Laplacian filter. Gaussian filter. Mean filter, Mode filter, Maximum filter, Minimum filter, Hybrid filter, Adaptive filter, Low pass filter, High pass filter, Hybrid filter and Uniform filter are discussed. In this paper, a new approach is proposed to use the FMM, which is obtained by computing median in each row, again median is calculated for medians of each row of a convolution mask. In this method, for example, for a 3 x 3 mask, left and right gray values are loaded along with center pixel of each row or each column and these values are sorted in order. The new center value is considered as median value, with this new value, smoothing of an image is achieved. In this method, a smoothed image is computed by employing just an auxiliary function swap, which yields less computation time.
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bwmeta1.element.baztech-article-BAT5-0037-0002
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