Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images
نویسندگان
چکیده
منابع مشابه
Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images
The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty function motivated by the recent progress in the statistical literature on high-dimensional variable selection. Using a particular instantiation of the majorization-minimization algorithm, the optimization problem can be ef...
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The Total Variation denoising method, proposed by Rudin, Osher and Fatermi, 92, is a PDE-based algorithm for edge-preserving noise removal. The images resulting from its application are usually piecewise constant, possibly with a staircase eeect at smooth transitions and may contain signiicantly less ne details than the original non-degraded image. In this paper we present some extensions to th...
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Denoising is the problem of removing the inherent noise from an image. The standard noise model is additive white Gaussian noise, where the observed image f is related to the underlying true image u by the degradation model f = u+ η, and η is supposed to be at each pixel independently and identically distributed as a zero-mean Gaussian random variable. Since this is an ill-posed problem, Rudin,...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2010
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2010.03.022