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Cite Details

Paul Rodríguez and Brendt Wohlberg, "A generalized vector-valued total variation algorithm", in Proceedings of IEEE International Conference on Image Processing (ICIP), (Cairo, Egypt), doi:10.1109/ICIP.2009.5413587 , pp. 1309--1312, Nov 2009

Abstract

We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional, which includes both the l2-VTV and l1-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 originally developed for scalar (grayscale) images. This method offers competitive computational performance for denoising and deconvolving vector-valued images corrupted with Gaussian (l2-VTV case) and salt-and-pepper noise (l1-VTV case).

BibTeX Entry

@inproceedings{rodriguez-2009-generalized,
author = {Paul Rodr\'{i}guez and Brendt Wohlberg},
title = {A generalized vector-valued total variation algorithm},
year = {2009},
month = Nov,
urlpdf = {http://math.lanl.gov/~brendt/Publications/Docs/rodriguez-2009-generalized.pdf},
booktitle = {Proceedings of IEEE International Conference on Image Processing (ICIP)},
address = {Cairo, Egypt},
doi = {10.1109/ICIP.2009.5413587 },
pages = {1309--1312}
}