• DocumentCode
    2162678
  • Title

    Finding curves in SAR CCD images

  • Author

    Cha, Miriam ; Phillips, Rhonda ; Yee, Michael

  • Author_Institution
    MIT Lincoln Lab., Lexington, MA, USA
  • fYear
    2011
  • fDate
    22-27 May 2011
  • Firstpage
    2024
  • Lastpage
    2027
  • Abstract
    This paper introduces a pattern recognition and computer vision approach to mitigating false alarms in synthetic aperture radar (SAR) coherence change detection (CCD) images. In this paper, we perform an automatic detection of roads in SAR CCD images. The approach is based on a curve tracing algorithm originally proposed by Steger with modifications to better suit the goal of curve detection in SAR CCD images. In our technique, the traditional Steger´s method is used to detect curve points, and cubic splines are used to approximate the original curve. To detect roads more accurately, preprocessing and outlier removal techniques are performed along with the curve detection.
  • Keywords
    computer vision; image recognition; radar detection; radar imaging; splines (mathematics); synthetic aperture radar; SAR CCD images; Steger method; coherence change detection images; computer vision approach; cubic splines; curve point detection; curve tracing algorithm; pattern recognition; road automatic detection; synthetic aperture radar; Charge coupled devices; Coherence; Pixel; Roads; Spline; Synthetic aperture radar; CCD; SAR; change detection; curve detection; regression splines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • Conference_Location
    Prague
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5946909
  • Filename
    5946909