  This article suggests an algorithm of impulse noise filtration, based on the
community detection in graphs. The image is representing as non-oriented
weighted graph. Each pixel of an image is corresponding to a vertex of the
graph. Community detection algorithm is running on the given graph. Assumed
that communities that contain only one pixel are corresponding to noised pixels
of an image. Suggested method was tested with help of computer experiment. This
experiment was conducted on grayscale, and on colored images, on artificial
images and on photos. It is shown that the suggested method is better than
median filter by 20% regardless of noise percent. Higher efficiency is
justified by the fact that most of filters are changing all of image pixels,
but suggested method is finding and restoring only noised pixels. The
dependence of the effectiveness of the proposed method on the percentage of
noise in the image is shown.
