• 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