  The salt and pepper noise brings a significant challenge to image denoising
technology, i.e. how to removal the noise clearly and retain the details
effectively? In this paper, we propose a patch-based contour prior denoising
approach for salt and pepper noise. First, noisy image is cut into patches as
basic representation unit, a discrete total variation model is designed to
extract contour structures; Second, a weighted Euclidean distance is designed
to search the most similar patches, then, corresponding contour stencils are
extracted from these similar patches; At the last, we build filter from contour
stencils in the framework of regression. Numerical results illustrate that the
proposed method is competitive with the state-of-the-art methods in terms of
the peak signal-to-noise (PSNR) and visual effects.
