DocumentCode
900666
Title
On global and local convergence of half-quadratic algorithms
Author
Allain, Marc ; Idier, Jérôme ; Goussard, Yves
Author_Institution
Inst. de Recherche en Commun. et en Cybernetique de Nantes, France
Volume
15
Issue
5
fYear
2006
fDate
5/1/2006 12:00:00 AM
Firstpage
1130
Lastpage
1142
Abstract
This paper provides original results on the global and local convergence properties of half-quadratic (HQ) algorithms resulting from the Geman and Yang (GY) and Geman and Reynolds (GR) primal-dual constructions. First, we show that the convergence domain of the GY algorithm can be extended with the benefit of an improved convergence rate. Second, we provide a precise comparison of the convergence rates for both algorithms. This analysis shows that the GR form does not benefit from a better convergence rate in general. Moreover, the GY iterates often take advantage of a low cost implementation. In this case, the GY form is usually faster than the GR form from the CPU time viewpoint.
Keywords
convergence; image reconstruction; iterative methods; convergence analysis; half-quadratic algorithms; image reconstruction; image restoration; Convergence; Costs; Helium; Image analysis; Image reconstruction; Image restoration; Iterative algorithms; Robustness; Statistical analysis; Symmetric matrices; Algorithms; asymptotic rate; convergence analysis; half-quadratic (HQ) iterations; image reconstruction; image restoration; robust statistics; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Models, Statistical;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2005.864173
Filename
1621235
Link To Document