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://brendt.wohlberg.net/publications/pdf/wohlberg-2007-iteratively.pdf},
journal = {IEEE Signal Processing Letters},
volume = {14},
number = {12},
doi = {10.1109/LSP.2007.906221},
pages = {948--951}
}
