• DocumentCode
    684887
  • Title

    Marine oil spill detection method research based on Envisat ASAR images

  • Author

    Ping Wang ; Guoqing Yu ; Yi Ding ; Ying Li ; Wenjing Yang ; Yaoxin Song

  • Author_Institution
    Key Lab. of Marine Surveying & Mapping in Univ. of Shandong, Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Now, as an increasing number of marine oil spill accidents, marine oil spill detection research has received national attention. This paper describes the method of the Envisat ASAR SAR data detection oil spill information, the preprocessing and post-processing of Envisat ASAR date. In the pre-processing, we have achieved absolute calibration processing; geometric precision correction based on ground control points and enhanced LEE filter processing. In the oil spill information extraction phase we use manual threshold segmentation, automatic threshold segmentation and CFAR detection method for extraction of oil spills area. Test results show that the methods used to achieve good extraction effect.
  • Keywords
    environmental science computing; geophysical image processing; marine pollution; oil pollution; radar signal processing; remote sensing by radar; synthetic aperture radar; water pollution measurement; CFAR detection method; Envisat ASAR data post processing; Envisat ASAR data preprocessing; Envisat ASAR images; absolute calibration processing; automatic threshold segmentation; enhanced LEE filter processing; geometric precision correction; ground control points; manual threshold segmentation; marine oil spill accidents; marine oil spill detection method; oil spill area extraction; oil spill information extraction phase; CFAR; filter processing; information extraction; marine oil spill; threshold segmentation;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
  • Conference_Location
    Shenzhen
  • Electronic_ISBN
    978-1-84919-641-3
  • Type

    conf

  • DOI
    10.1049/cp.2012.2473
  • Filename
    6755852