• DocumentCode
    3495910
  • Title

    Joint image registration and super-resolution reconstruction based on regularized total least norm

  • Author

    Wang, Qing ; Song, Xiaoli

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2009
  • fDate
    7-10 Nov. 2009
  • Firstpage
    1537
  • Lastpage
    1540
  • Abstract
    Accurate registration of the low resolution (LR) images is a critical step in image super resolution reconstruction (SRR). Conventional algorithms always use invariable motion parameters derived from registration algorithms, and carry on SRR without considering the registration errors in the disjointed method. In this paper we propose a new method that performs joint image registration and SRR based on regularized total least norm (RTLN), updating the motion parameters and HR image simultaneously. Not only translation but also rotation motion are considered, which makes the motion model more universal. Experimental results have shown that our approach is more effective and efficient than traditional ones.
  • Keywords
    image motion analysis; image reconstruction; image registration; image resolution; least squares approximations; HR image; image registration; image super-resolution reconstruction; low resolution image; motion model; motion parameter; regularized total least norm; rotation motion; Atmospheric modeling; Cost function; Image reconstruction; Image registration; Image resolution; Iterative algorithms; Least squares methods; Motion estimation; Space technology; Vectors; Image registration; Regularized total least norm (RTLN); Super resolution reconstruction (SRR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2009 16th IEEE International Conference on
  • Conference_Location
    Cairo
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-5653-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2009.5414518
  • Filename
    5414518