• DocumentCode
    2481518
  • Title

    Edge-preserving unscented Kalman filter for speckle reduction

  • Author

    Subrahmanyam, G.R.K. ; Rajagopalan, A.N. ; Aravind, R. ; Rigoll, Gerhard

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol. Madras, Chennai
  • fYear
    2008
  • fDate
    8-11 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We propose a recursive spatial-domain speckle reduction algorithm for synthetic aperture radar (SAR) imagery based on the unscented Kalman filter (UKF) with a discontinuity-adaptive Markov random field (DAMRF) prior. The capability of the UKF in handling speckle noise and the feature preservation ability of the DAMRF model are explored within a unified framework through importance sampling.
  • Keywords
    Kalman filters; Markov processes; edge detection; importance sampling; radar imaging; synthetic aperture radar; discontinuity-adaptive Markov random field; edge-preserving unscented Kalman filter; feature preservation ability; importance sampling; speckle noise handling; speckle reduction; synthetic aperture radar imagery; Adaptive filters; Degradation; Image texture; Markov random fields; Monte Carlo methods; Nonlinear filters; Random variables; Speckle; Statistics; Wavelet domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-2174-9
  • Electronic_ISBN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2008.4761408
  • Filename
    4761408
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2481518