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Proceedings Paper

Characterization of clutter in SAR imagery using extended self-similar (ESS) processes
Author(s): Lance M. Kaplan; Romain Murenzi
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Paper Abstract

The utility of multiscale Hurst features are determined for segmentation of clutter in SAR imagery. These multiscale Hurst features represent a generalization of the Hurst parameter for fractional Brownian motion (fBm) where these new features measure texture roughness at various scales. A clutter segmentation algorithm is described using only these new Hurst parameters as features. The performance of the algorithm was tested on measured one foot resolution SAR data, and the results are comparable to other algorithms proposed in the literature. The advantage of the multiscale Hurst features is that they can be computed quickly and they can discriminate clutter well in unprocessed single polarization magnitude detected SAR imagery.

Paper Details

Date Published: 20 June 1997
PDF: 12 pages
Proc. SPIE 3062, Targets and Backgrounds: Characterization and Representation III, (20 June 1997); doi: 10.1117/12.276697
Show Author Affiliations
Lance M. Kaplan, Clark Atlanta Univ. (United States)
Romain Murenzi, Clark Atlanta Univ. (United States)

Published in SPIE Proceedings Vol. 3062:
Targets and Backgrounds: Characterization and Representation III
Wendell R. Watkins; Dieter Clement, Editor(s)

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