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://brendt.wohlberg.net/publications/pdf/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}
}
