• DocumentCode
    998833
  • Title

    Slicks detection on the sea surface based upon polarimetric SAR data

  • Author

    Bandiera, Francesco ; Ricci, Giuseppe

  • Author_Institution
    Dipt. di Ingegneria dell´´Innovazione, Univ. degli Studi di Lecce, Italy
  • Volume
    2
  • Issue
    3
  • fYear
    2005
  • fDate
    7/1/2005 12:00:00 AM
  • Firstpage
    342
  • Lastpage
    346
  • Abstract
    This letter proposes a generalized-likelihood ratio test-based edge detector to be fed by possibly polarimetric synthetic aperture radar (SAR) data. It can be used to detect dark spots on the sea surface and, hence, as the first stage of a system for identification and monitoring of oil spills. The proposed constant false alarm rate (CFAR) detector does not require secondary data (namely pixels from a slick-free area); remarkably, a preliminary performance assessment, carried out by resorting to real SAR recordings, shows that it guarantees detection capabilities comparable to those of previously proposed polarimetric CFAR detectors (which though make use of secondary data). The preliminary performance assessment also seems to indicate that processing polarimetric data does not ensure improved detection capabilities.
  • Keywords
    marine pollution; oil pollution; radar polarimetry; remote sensing by radar; synthetic aperture radar; water pollution measurement; constant false alarm rate detector; dark spots; detection capabilities; generalized-likelihood ratio test-based edge detector; identification; monitoring; oil slick detection; oil spills; performance assessment; polarimetric SAR data; sea surface; synthetic aperture radar; Detectors; Image edge detection; Monitoring; Petroleum; Polarimetric synthetic aperture radar; Radar detection; Sea surface; Surface waves; Synthetic aperture radar; Testing; Constant false alarm rate (CFAR) detection; generalized-likelihood ratio test (GLRT); oil slicks; polarimetric synthetic aperture radar (SAR) data;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2005.847753
  • Filename
    1468095