  In this paper, we propose a method for real-time high density impulse noise
suppression from images. In our method, we first apply an impulse detector to
identify the corrupted pixels and then employ an innovative weighted-average
filter to restore them. The filter takes the nearest neighboring interpolated
image as the initial image and computes the weights according to the relative
positions of the corrupted and uncorrupted pixels. Experimental results show
that the proposed method outperforms the best existing methods in both PSNR
measure and visual quality and is quite suitable for real-time applications.
