• DocumentCode
    1791393
  • Title

    Oil spill detection in SAR images using minimum cross-entropy thresholding

  • Author

    Alattas, Reem

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Bridgeport, Bridgeport, CT, USA
  • fYear
    2014
  • fDate
    14-16 Oct. 2014
  • Firstpage
    709
  • Lastpage
    713
  • Abstract
    Oil spill detection becomes very important nowadays, due to the importance of oil and to prevent pollution caused by oil leakage. Synthetic Aperture Radar (SAR) images show oil spill boundaries clearly. An oil spill appears as an obscure spot in SAR images. Therefore, thresholding is considered the best method to extract this patch and define its boundaries clearly. This paper proposes a novel thresholding method for detecting oil spill in SAR images that minimizes cross-entropy between images and their segmented versions using gamma Distribution. Moreover, this paper demonstrates applying the new proposed method results on artificial images as well as various SAR images. Gamma Distribution was chosen over other distributions because it has a general shape, and it showed excellent results in modeling images´ data.
  • Keywords
    entropy; gamma distribution; geophysical image processing; image segmentation; oceanographic techniques; oil pollution; radar imaging; synthetic aperture radar; SAR images; artificial images; gamma distribution; image data; minimum cross-entropy thresholding; oil leakage; oil spill boundaries; oil spill detection; segmented images; synthetic aperture radar images; Entropy; Histograms; Image segmentation; Materials; Radar imaging; Shape; Synthetic aperture radar; Oil spill detection; gamma distribution; minimum cross-entropy; thresholding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2014 7th International Congress on
  • Conference_Location
    Dalian
  • Type

    conf

  • DOI
    10.1109/CISP.2014.7003870
  • Filename
    7003870