• DocumentCode
    3159157
  • Title

    Fuzzy segmentation of SAR images for oil spill recognition

  • Author

    Barni, A. ; Betti, M. ; Mecocci, A.

  • Author_Institution
    Florence Univ., Italy
  • fYear
    1995
  • fDate
    4-6 Jul 1995
  • Firstpage
    534
  • Lastpage
    538
  • Abstract
    A three-step algorithm is developed to segment oil spills from a marine background on Synthetic Aperture Radar (SAR) data. First, filtering is performed to reduce speckle noise. Then fuzzy clustering is carried out to obtain a preliminary partition of the pixels on the basis of their grey level intensities. A very simple cluster validity criterion is tested to determine the optimal number of clusters present in the data. In order to improve segmentation a final step involves a cluster merging procedure using edge information provided by a Sobel operator. The algorithm has been tested on SEASAT images
  • Keywords
    filtering theory; fuzzy set theory; image recognition; image segmentation; radar imaging; speckle; synthetic aperture radar; SAR images; SEASAT images; Sobel operator; cluster merging procedure; cluster validity criterion; edge information; filtering; fuzzy clustering; fuzzy segmentation; grey level intensities; marine background; oil spill recognition; speckle noise reduction; three-step algorithm;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Image Processing and its Applications, 1995., Fifth International Conference on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    0-85296-642-3
  • Type

    conf

  • DOI
    10.1049/cp:19950716
  • Filename
    465506