Abstract
A peer region determination (PRD) algorithm for impulsive noise detection in digital images is proposed; it removes random-valued impulsive noise while preserving very fine image details. This algorithm determines the peer region for each pixel adaptively by finding the variation of pixel values in a 5/spl times/5 filter window. If the number of member pixels in the peer region is very small, the pixel being processed is thought to be isolated from other pixels and thus considered as impulsive noise. In addition, this noise detector can be easily modified to perform feature selective filtering. Experimental results show that the proposed noise detection algorithm outperforms other existing non-linear filters and adaptive noise detection based filters in noise removal and image detail preservation. Finally, the concept of the PRD algorithm applied to other image processing applications is discussed.
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