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Proceedings Paper

Building detection in SAR imagery
Author(s): Ryan M. Steinbach; Mark W. Koch; Mary M. Moya; Jeremy Goold
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Paper Abstract

Current techniques for building detection in Synthetic Aperture Radar (SAR) imagery can be computationally expensive and/or enforce stringent requirements for data acquisition. We present a technique that is effective and efficient at determining an approximate building location from multi-pass single-pol SAR imagery. This approximate location provides focus-of-attention to specific image regions for subsequent processing. The proposed technique assumes that for the desired image, a preprocessing algorithm has detected and labeled bright lines and shadows. Because we observe that buildings produce bright lines and shadows with predetermined relationships, our algorithm uses a graph clustering technique to find groups of bright lines and shadows that create a building. The nodes of the graph represent bright line and shadow regions, while the arcs represent the relationships between the bright lines and shadow. Constraints based on angle of depression and the relationship between connected bright lines and shadows are applied to remove unrelated arcs. Once the related bright lines and shadows are grouped, their locations are combined to provide an approximate building location. Experimental results are presented to demonstrate the outcome of this technique.

Paper Details

Date Published: 21 May 2015
PDF: 10 pages
Proc. SPIE 9461, Radar Sensor Technology XIX; and Active and Passive Signatures VI, 94610E (21 May 2015); doi: 10.1117/12.2177037
Show Author Affiliations
Ryan M. Steinbach, Sandia National Labs. (United States)
Mark W. Koch, Sandia National Labs. (United States)
Mary M. Moya, Sandia National Labs. (United States)
Jeremy Goold, Sandia National Labs. (United States)


Published in SPIE Proceedings Vol. 9461:
Radar Sensor Technology XIX; and Active and Passive Signatures VI
G. Charmaine Gilbreath; Kenneth I. Ranney; Armin Doerry; Chadwick Todd Hawley, Editor(s)

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