A generalized vector-valued total variation algorithm

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A generalized vector-valued total variation algorithm
We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional, which includes both the 2 -VTV and 1 -VTV regularizations as special cases, to address the problems of deconvolution and denoising of vector-valued (e.g. color) images with Gaussian or salt-andpepper noise. This algorithm is the vectorial extension of the Iteratively Reweighted Norm (IRN) algorithm [1] originally developed for scalar (grayscale) images. This method offers competitive computational performance for denoising and deconvolving vector-valued images corrupted with Gaussian ( 2 -VTV case) and salt-and-pepper noise ( 1 -VTV case).
Paul Rodriguez, Brendt Wohlberg
Added 19 Feb 2011
Updated 19 Feb 2011
Type Journal
Year 2009
Where ICIP
Authors Paul Rodriguez, Brendt Wohlberg
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