• DocumentCode
    3088486
  • Title

    Statistical modeling of sea clutter in high-resolution SAR images using generalized gamma distribution

  • Author

    Xianxiang Qin ; Shilin Zhou ; Huanxin Zou ; Gui Gao

  • Author_Institution
    Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2012
  • fDate
    16-18 Dec. 2012
  • Firstpage
    306
  • Lastpage
    310
  • Abstract
    Statistical modeling of sea clutter in synthetic aperture radar (SAR) imagery is fundamental for SAR image interpretation. In this paper, we adopt a recently proposed generalized gamma distribution (GrD) for modeling sea clutter in high-resolution SAR images. Based on parameter decoupling, an estimator of GrD, named as scale-independent scale estimation (SISE), is derived, which only refers to several basic operations and can be easily realized. Modeling experiments are carried out over the L-band polarimetric SAR images acquired by JPL/AIRSAR and a VV-polarized C-band TerraSAR-X SAR image. Experimental results show that the advantage of GrD for modeling sea clutter in high-resolution SAR images is evident comparing to the classic distributions of sea clutter in SAR images including the Weibull, Log-normal and K distributions.
  • Keywords
    gamma distribution; image resolution; radar clutter; radar imaging; synthetic aperture radar; GrD; JPL-AIRSAR; K distribution; L-band polarimetric SAR image; SISE; VV-polarized C-band TerraSAR-X SAR image; Weibull distribution; generalized gamma distribution; high-resolution SAR image; log-normal distribution; parameter decoupling; scale-independent scale estimation; sea clutter; statistical modeling; Atmospheric modeling; Histograms; Image resolution; generalized gamma distribution (GΓD); scale-independent shape estimation (SISE); sea clutter; statistical modeling; synthetic aperture radar (SAR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4673-1272-1
  • Type

    conf

  • DOI
    10.1109/CVRS.2012.6421280
  • Filename
    6421280