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Proceedings Paper

Stochastic clutter characterization in NASA/JPL AIRSAR imagery
Author(s): George W. Rogers; Rick D. Roberts; Houra Rais
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Paper Abstract

The background or clutter in SAR imagery has a significant stochastic component. It is often desirable to be able to rapidly characterize the clutter distribution and/or classify the background type based on the clutter distribution. We model the stochastic clutter as a piecewise stationary random field. The individual stationary subregions of homogeneity in the field can then be characterized by marginal density functions. This level of characterization is often sufficient for determination of clutter type on a local basis. We present a technique for the simultaneous characterization of the subregions of a random field based on semiparametric density estimation on the entire random field. This technique is based on a borrowed strength methodology that allows the use of observation from potentially dissimilar subregions to improve local density estimation and hence random process characterization. This approach is demonstrated on a set of NASA/JPL AIRSAR images, including an example of clutter dependent crash site detection.

Paper Details

Date Published: 23 June 1997
PDF: 8 pages
Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); doi: 10.1117/12.277102
Show Author Affiliations
George W. Rogers, Naval Surface Warfare Ctr. (United States)
Rick D. Roberts, Analytic Solutions Inc. (United States)
Houra Rais, McDonnell Douglas Aerospace (United States)

Published in SPIE Proceedings Vol. 3069:
Automatic Target Recognition VII
Firooz A. Sadjadi, Editor(s)

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