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Proceedings Paper

Model-based SAR ATR system
Author(s): Katsushi Ikeuchi; Mark D. Wheeler; Taku Yamazaki; Takeshi Shakunaga
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Paper Abstract

Recognizing a target in SAR images is an important, yet challenging application of model-based vision. This paper describes a model-based SAR recognition system based on invariant histograms and deformable template matching techniques. An invariant histogram is a histogram of invariant values defined by geometric features such as points and lines in SAR images. Although a few invariances are sufficient to recognize a target, we histogram all invariant values given by all possible target feature pairs. This redundant representation enables robust recognition under severe occlusions typical of SAR recognition scenarios. Multi-step deformable template matching examines the existence of an object by superimposing templates over potential energy field generated from images or primitive features. It determines the template configuration which has the minimum deformation and the best alignment of the template with features. The deformability of the template absorbs the instability of SAR features. We have implemented the system and evaluated the system performance using hybrid SAR images, generated from synthetic model signatures and real SAR background signatures.

Paper Details

Date Published: 10 June 1996
PDF: 12 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242040
Show Author Affiliations
Katsushi Ikeuchi, Carnegie Mellon Univ. (United States)
Mark D. Wheeler, Carnegie Mellon Univ. (United States)
Taku Yamazaki, Carnegie Mellon Univ. (United States)
Takeshi Shakunaga, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

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