• DocumentCode
    291749
  • Title

    Comparison of segmentation methodologies applied to ERS-1 SAR images

  • Author

    Caves, R.G. ; Quegan, S. ; White, R.G. ; Cook, R.

  • Author_Institution
    Centre for Earth Obs. Sci., Sheffield Univ., UK
  • Volume
    3
  • fYear
    1994
  • fDate
    8-12 Aug 1994
  • Firstpage
    1618
  • Abstract
    The performance of three segmentation methods, developed for high resolution airborne synthetic aperture radar (SAR) data, on lower resolution spaceborne data is assessed using two ERS-1 images. Methods based on a cartoon model for the underlying image are shown to be able to successfully segment regions bounded by abrupt edges, but to be unable to represent gradual changes in intensity and linear features. These problem are overcome at the expense of greatly increased cpu time using MAP reconstruction which models the underlying image as a semi-continuous surface
  • Keywords
    geophysical signal processing; geophysical techniques; image classification; image segmentation; radar applications; radar imaging; remote sensing by radar; spaceborne radar; synthetic aperture radar; ERS-1; MAP reconstruction; SAR imagery; abrupt edge; airborne synthetic aperture radar; cartoon model; geophysical measurement technique; gradual change; high resolution; image classification; image processing; image segmentation; land surface terrain mapping; linear feature; radar remote sensing; semi-continuous surface; spaceborne; Image edge detection; Image reconstruction; Image resolution; Image segmentation; Layout; Merging; Robust stability; Simulated annealing; Spaceborne radar; Synthetic aperture radar;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
  • Conference_Location
    Pasadena, CA
  • Print_ISBN
    0-7803-1497-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.1994.399517
  • Filename
    399517