• DocumentCode
    1359623
  • Title

    Multidimensional image reconstruction in astronomy

  • Author

    Kamalabadi, Farzad

  • Author_Institution
    Univ. of Illinois, Urbana, IL, USA
  • Volume
    27
  • Issue
    1
  • fYear
    2010
  • Firstpage
    86
  • Lastpage
    96
  • Abstract
    The goal of this article is to describe a unified approach based on the assumption of additive Gaussian noise and regularization theory that illustrates the flavor of such multidimensional image reconstruction problems and the associated challenges. Efficient iterative methods are described for the solution of these problems. Indeed, a crucial point in the solution to the problems considered in this article is the size of the data set and the need for efficient algorithms.
  • Keywords
    AWGN; astronomical image processing; image reconstruction; iterative methods; additive Gaussian noise; astronomical image reconstruction; data set size; image formation problems; image reconstruction problems; iterative methods; multidimensional image reconstruction; regularisation theory; Astronomy; Atmosphere; Extraterrestrial measurements; Image reconstruction; Inverse problems; Multidimensional systems; Optical imaging; Plasma density; Plasma measurements; Space technology;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2009.934717
  • Filename
    5355499