• DocumentCode
    1188873
  • Title

    Image deblurring: I can see clearly now

  • Author

    Nagy, James G. ; O´Leary, Dianne P.

  • Author_Institution
    Dept. of Math. & Comput. Sci., Emory Univ., Atlanta, GA, USA
  • Volume
    5
  • Issue
    3
  • fYear
    2003
  • Firstpage
    82
  • Lastpage
    84
  • Abstract
    Inverse problems are among the most challenging computations in science and engineering because they involve determining the parameters of a system that is only observed indirectly. For example, we might have a spectrum and want to determine the species that produced it as well as their relative proportions, or we may have sonar measurements of a containment tank and want to know whether it has an internal crack. Given a blurred image and a linear model for the blurring, the original image is reconstructed. This linear inverse problem illustrates the impact of ill-conditioning on the choice of algorithms.
  • Keywords
    image restoration; inverse problems; blurred image; ill-conditioning; image deblurring; image reconstruction; linear inverse problem; linear model; Educational programs; Eigenvalues and eigenfunctions; Home computing; Image restoration; Knowledge engineering; Matrix decomposition; Numerical analysis; Partial differential equations; Scientific computing; Singular value decomposition;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCISE.2003.1196312
  • Filename
    1196312