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Detecting Small Features in SAR Images by an ANN

  • I. Finch
  • D. F. Yates
  • L. M. Delves
Conference paper

Abstract

Synthetic aperture radar (SAR) images are intrinsically noisy, and processing them attracts a high computational overhead. This paper relates to developments, involving the use of an ANN to reduce the overhead, in respect of earlier work by the authors on the identification of small objects. It describes how the ANN is utilised, and how it was trained using an artificially created training set.

Keywords

False Alarm Synthetic Aperture Radar Synthetic Aperture Radar Image Artificial Data Contextual Knowledge 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J. C. Curlander and R. N. McDonough. Synthetic Aperture Radar: Systems and Signal Processing. John Wiley and Sons, New York, 1991.MATHGoogle Scholar
  2. [2]
    I. Finch, D. Yates, and M. Delves. Detecting lines of pylons in sar images. In Proceedings Third International Conference on Satellite Remote Sensing, volume 2958, pages 152–163, Washington, 1996. SPIE.Google Scholar
  3. [3]
    K. Morrison and J. C. Bennett. Development of a ground-based synthetic aperture radar remote sensing facility. In Polarimetric SAR Workshop. SCEOS, Sheffield, 1994.Google Scholar
  4. [4]
    C.J. Oliver. Information from SAR images. J. Phys. D: Appl Phys., 24:1493–1514, 1991.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • I. Finch
    • 1
  • D. F. Yates
    • 1
  • L. M. Delves
    • 1
  1. 1.Department of Computer ScienceUniversity of LiverpoolLiverpoolUK

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