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10

ICIP
2009
IEEE

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A generalized vector-valued total variation algorithm

13 years 2 months ago

A generalized vector-valued total variation algorithm

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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

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-VTV Case | Competitive Computational Performance | Generalized Vector-valued Tv | ICIP 2009 | Image Processing |

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Added	19 Feb 2011
Updated	19 Feb 2011
Type	Journal
Year	2009
Where	ICIP
Authors	Paul Rodriguez, Brendt Wohlberg

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