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Proceedings Paper

Comparing target information in voxel and pixel ultra-wideband radar images
Author(s): Matthew S. Wilson; Shawn M. Wilder
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Paper Abstract

In this article we discuss the differences and similarities in useful information, extracted from images, between several features that operate on pixel imagery and their analogues which act on voxel imagery. First we train voxel and, separately, pixel feature-based classifiers to distinguish targets from clutter using a probabilistic classification algorithm. The relative usefulness of information of these features is then measured by comparing the performance of the classifiers. Our experiments utilize voxel imagery constructed from ultra-wideband synthetic aperture radar; the pixel images analyzed are two-dimensional (2D) subimages of the voxel images. The work primarily uses features commonly employed, such as image intensity statistics, elements of an images fourier decomposition and various energy measures. The cost of different features is also discussed.

Paper Details

Date Published: 10 May 2019
PDF: 8 pages
Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 1101208 (10 May 2019); doi: 10.1117/12.2519143
Show Author Affiliations
Matthew S. Wilson, Naval Surface Warfare Ctr. (United States)
Shawn M. Wilder, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 11012:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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