Priority-based trimmed median filter for removal of high density salt and pepper noise

Abstract

This paper proposes an efficient and less complex priority-based trimmed median filter algorithm for restoring images corrupted by high density salt and pepper noise. Noisy pixel is replaced by trimmed median value of the horizontal and vertical adjacent four pixels, through this algorithm. If these four are 0 s and 255 s, then the next priority diagonal adjacent four pixels are used to calculate trimmed median for replacing noisy pixels. If these four are also found as 0 s and 255 s, then the noisy pixel is left unchanged until the next iteration. Experimental results on different greyscale and colour images show that the proposed algorithm outperforms the standard median filter, adaptive median filter, decision-based algorithm, modified progressive switching median filter and modified decision-based unsymmetric trimmed median filter.