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Cite Details

Brendt Wohlberg and Paul Rodríguez, "An Iteratively Reweighted Norm Algorithm for Minimization of Total Variation Functionals", IEEE Signal Processing Letters, vol. 14, no. 12, doi:10.1109/LSP.2007.906221, pp. 948--951, Dec 2007

Abstract

Total Variation (TV) regularization has become a popular method for a wide variety of image restoration problems, including denoising and deconvolution. A number of authors have recently noted the advantages of replacing the standard l2 data fidelity term with an l1 norm. We propose a simple but very flexible method for solving a generalized TV functional which includes both the l2-TV and and l1-TV problems as special cases. This method offers competitive computational performance for l2-TV, and is comparable to or faster than any other l1-TV algorithms of which we are aware.

BibTeX Entry

@article{wohlberg-2007-iteratively,
author = {Brendt Wohlberg and Paul Rodr\'{i}guez},
title = {An Iteratively Reweighted Norm Algorithm for Minimization of Total Variation Functionals},
year = {2007},
month = Dec,
urlpdf = {http://math.lanl.gov/~brendt/Publications/Docs/wohlberg-2007-iteratively.pdf},
journal = {IEEE Signal Processing Letters},
volume = {14},
number = {12},
doi = {10.1109/LSP.2007.906221},
pages = {948--951}
}