4 research outputs found
Fast restoration of natural images corrupted by high-density impulse noise
In this paper, we suggest a general model for the fixed-valued impulse noise
and propose a two-stage method for high density noise suppression while
preserving the image details. In the first stage, we apply an iterative impulse
detector, exploiting the image entropy, to identify the corrupted pixels and
then employ an Adaptive Iterative Mean filter to restore them. The filter is
adaptive in terms of the number of iterations, which is different for each
noisy pixel, according to the Euclidean distance from the nearest uncorrupted
pixel. Experimental results show that the proposed filter is fast and
outperforms the best existing techniques in both objective and subjective
performance measures