Characterization of clutter in SAR imagery using extended self-similar (ESS) processes

Lance M. Kaplan; Romain Murenzi

doi:10.1117/12.276697

20 June 1997 Characterization of clutter in SAR imagery using extended self-similar (ESS) processes

Lance M. Kaplan, Romain Murenzi

Proceedings Volume 3062, Targets and Backgrounds: Characterization and Representation III; (1997) https://doi.org/10.1117/12.276697
Event: AeroSense '97, 1997, Orlando, FL, United States

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.

Citation Download Citation

Lance M. Kaplan and Romain Murenzi "Characterization of clutter in SAR imagery using extended self-similar (ESS) processes", Proc. SPIE 3062, Targets and Backgrounds: Characterization and Representation III, (20 June 1997); https://doi.org/10.1117/12.276697

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