• DocumentCode
    1154552
  • Title

    Oil Spill Detection in Radarsat and Envisat SAR Images

  • Author

    Solberg, Anne H S ; Brekke, Camilla ; Husøy, Per Ove

  • Volume
    45
  • Issue
    3
  • fYear
    2007
  • fDate
    3/1/2007 12:00:00 AM
  • Firstpage
    746
  • Lastpage
    755
  • Abstract
    We present algorithms for automatic detection of oil spills in synthetic aperture radar (SAR) images. The algorithms consist of three main parts, namely: 1) detection of dark spots; 2) feature extraction from the dark spot candidates; and 3) classification of dark spots as oil spills or look-alikes. The algorithms have been trained on a large number of Radarsat and Envisat Advanced Synthetic Aperture Radar (ASAR) images. The performance of the algorithm is compared to manual and semiautomatic approaches in a benchmark study using 59 Radarsat and Envisat images. The algorithms can be considered to be a good alternative to manual inspection when large ocean areas are to be inspected
  • Keywords
    feature extraction; image classification; marine pollution; oil pollution; radar imaging; synthetic aperture radar; water pollution measurement; Envisat SAR images; Radarsat SAR images; automatic detection; dark spot classification; dark spot detection; feature extraction; ocean pollution; oil spill detection; synthetic aperture radar; Aircraft; Cleaning; Clustering algorithms; Feature extraction; Oceans; Petroleum; Pollution; Radar detection; Sea surface; Synthetic aperture radar; Classification; feature extraction; oil spill detection; synthetic aperture radar (SAR);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2006.887019
  • Filename
    4106067