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Proceedings Paper

Pose estimation in SAR using an information theoretic criterion
Author(s): Jose C. Principe; Dongxin Xu; John W. Fisher
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Paper Abstract

In this paper we formulate pose estimation statistically and show that pose can be estimated from a low dimensional feature space obtained by maximizing the mutual information between the aspect angle and the output of a nonlinear mapper. We use the Havrda-Charvat definition of entropy to implement a nonparametric estimator based on the Parzen window method. Results in the MSTAR data set are presented and show the performance of the methodology.

Paper Details

Date Published: 15 September 1998
PDF: 12 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321826
Show Author Affiliations
Jose C. Principe, Univ. of Florida (United States)
Dongxin Xu, Univ. of Florida (United States)
John W. Fisher, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 3370:
Algorithms for Synthetic Aperture Radar Imagery V
Edmund G. Zelnio, Editor(s)

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