Abstract
Median filtering computation for noise removal is often used in impulse noise
removal techniques, but the difficulties in removing high-density noise aspect restrict
its development. In this paper, we propose a very efficient method to restore image
corrupted by high-density impulse noise. First, the proposed method detects both the
number and position of the noise-free pixels in the image. Next, the dilatation
operation of the noise-free pixels based on morphological image processing is
iteratively executed to replace the neighbor noise pixels until convergence. By doing
so, the proposed method is capable to remove high-density noise and therefore
reconstruct the noise-free image. Experimental results indicate that the proposed method
more effectively removes high-density impulse noise in corrupted images in comparison
with the other tested state-of-the-art methods. Additionally, the proposed method only
requires moderate execution time to achieve optimal impulse noise removal.
© 2015 IEEE
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