• DocumentCode
    2538129
  • Title

    Local blur estimation and super-resolution

  • Author

    Chiang, Ming-Chao ; Boult, Terrance E.

  • Author_Institution
    Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
  • fYear
    1997
  • fDate
    17-19 Jun 1997
  • Firstpage
    821
  • Lastpage
    826
  • Abstract
    Until now, all super-resolution algorithms have presumed that the images were taken under the same illumination conditions. This paper introduces a new approach to super-resolution, based on edge models and a local blur estimate, which circumvents these difficulties. The paper presents the theory and the experimental results using the new approach
  • Keywords
    edge detection; image resolution; blur estimation; edge models; local blur estimate; super-resolution; Computer science; Frequency; High-resolution imaging; Image edge detection; Image resolution; Image restoration; Image sequences; Lighting control; Sensor phenomena and characterization; US Department of Defense;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
  • Conference_Location
    San Juan
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7822-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1997.609422
  • Filename
    609422
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2538129