Isolating impulsive noise pixels in color images by peer group techniques

A new method for removing impulsive noise in color images is presented. The fuzzy metric peer group concept is used to build novel switching vector filters. In the proposed filtering procedure, a set of noise-free pixels of high reliability is determined by applying a highly restrictive condition based on the peer group concept. Afterwards, an iterative detection process is used to refine the initial findings by detecting additional noise-free pixels. Finally, noisy pixels are filtered by maximizing the employed fuzzy distance criterion between the pixels inside the filter window. Comparisons are provided to show that our approach suppresses impulsive noise, while preserving image details. In addition, the method is analyzed in order to justify the necessity of the iterative process and demonstrate the computational efficiency of the proposed approach.

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