Spatially Adaptive Total Variation Image Denoising Under Salt and Pepper Noise

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Automated selection of the regularization parameter for Total Variation restoration has shown to give very accurate reconstruction results. Most of the literature is devoted to the '2-TV case (images corrupted with Gaussian noise), whereas for the '1-TV case (images corrupted with salt-and-pepper noise) there are only a couple of published algorithms. In this paper the authors present a computationally efficient algorithm for '1-TV denoising of gray scale and color images, which spatially adapts its regularization parameter.