TY - GEN
T1 - Performance comparison of iterative reweighting methods for total variation regularization
AU - Rodríguez, Paul
AU - Wohlberg, Brendt
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/28
Y1 - 2014/1/28
N2 - Iteratively Reweighted Least Squares (IRLS) is a well-established method of optimizing ℓp norm problems such as Total Variation (TV) regularization. Within this general framework, there are several possible ways of constructing the weights and the form of the linear system that is iteratively solved as part of the algorithm. Many of these choices are equally reasonable from a theoretical perspective, and there has, thus far, been no systematic comparison between them. In this paper we provide such a comparison between the main choices in IRLS algorithms for ℓ1- and ℓ2-TV denoising, finding that there is a significant variation in the computational cost and reconstruction quality of the different variants.
AB - Iteratively Reweighted Least Squares (IRLS) is a well-established method of optimizing ℓp norm problems such as Total Variation (TV) regularization. Within this general framework, there are several possible ways of constructing the weights and the form of the linear system that is iteratively solved as part of the algorithm. Many of these choices are equally reasonable from a theoretical perspective, and there has, thus far, been no systematic comparison between them. In this paper we provide such a comparison between the main choices in IRLS algorithms for ℓ1- and ℓ2-TV denoising, finding that there is a significant variation in the computational cost and reconstruction quality of the different variants.
KW - Iteratively Reweighted Least Squares
KW - Iteratively Reweighted Norm
KW - Total Variation
UR - http://www.scopus.com/inward/record.url?scp=84949928272&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025352
DO - 10.1109/ICIP.2014.7025352
M3 - Conference contribution
AN - SCOPUS:84949928272
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 1758
EP - 1762
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -