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Proceedings Paper

Feature extraction using attributed scattering center models on SAR imagery
Author(s): Michael A. Koets; Randolph L. Moses
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Paper Abstract

We present algorithms for feature extraction from complex SAR imagery. The features parameterize an attributed scattering center model that describes both frequency and aspect dependence of scattering centers on the target. The scattering attributes extend the widely-used point scattering model, and characterize physical properties of the scattering object. We present two feature extraction algorithms, an approximate maximum likelihood method that relies on minimization of a nonlinear cost function, and a computationally faster method that avoids the nonlinear minimization step. We present results of applying both algorithms on synthetic model data, on XPatch scattering predictions of the SLICY test target, and on measured X-band SAR imagery.

Paper Details

Date Published: 13 August 1999
PDF: 12 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357628
Show Author Affiliations
Michael A. Koets, The Ohio State Univ. (United States)
Randolph L. Moses, The Ohio State Univ. (United States)


Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

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