• DocumentCode
    3088523
  • Title

    A non-supervised method for shoreline extraction using high resolution SAR image

  • Author

    Long Zhao ; Ling Fan ; Chao Wang ; Yixian Tang ; Bo Zhang

  • Author_Institution
    Sch. of Sci., Beijing Jiaotong Univ., Beijing, China
  • fYear
    2012
  • fDate
    16-18 Dec. 2012
  • Firstpage
    317
  • Lastpage
    322
  • Abstract
    This paper presents a non-supervised method for shoreline extraction from high resolution synthetic aperture radar (SAR) image. The proposed technique is based on level set with all the parameters optimized in order to be used with different kinds of SAR data and to find the desired boundary with a minimize number of iterations so as to be fast enough. The preprocessing including Roberts Operator and Histogram adjusting is used to enhance the contrast of the boundary. Then we initial the curve to cover the whole image, and an improved level set method is used to do the segmentation. After that, several post-processing steps are utilized to remove any remaining spurious segments. It´s completely non-supervised and can be applied to different kinds of SAR data. The results confirm that the proposed method can provide a stable and fast solution to the shoreline extraction using SAR data.
  • Keywords
    feature extraction; geophysical image processing; image resolution; oceanographic techniques; radar imaging; radar resolution; synthetic aperture radar; Roberts operator-and=histogram adjusting; high resolution SAR image; level set method; nonsupervised method; shoreline extraction; synthetic aperture radar; Earth; Image resolution; Image segmentation; SAR; Shoreline extraction; level set; non-supervised;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4673-1272-1
  • Type

    conf

  • DOI
    10.1109/CVRS.2012.6421282
  • Filename
    6421282