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Proceedings Paper

Detection of facilities in satellite imagery using semi-supervized image classification and auxiliary contextual observables
Author(s): Neal R. Harvey; C. Ruggiero; N. H. Pawley; B. MacDonald; A. Oyer; L. Balick; S. P. Brumby
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Paper Abstract

Detecting complex targets, such as facilities, in commercially available satellite imagery is a difficult problem that human analysts try to solve by applying world knowledge. Often there are known observables that can be extracted by pixel-level feature detectors that can assist in the facility detection process. Individually, each of these observables is not sufficient for an accurate and reliable detection, but in combination, these auxiliary observables may provide sufficient context for detection by a machine learning algorithm. We describe an approach for automatic detection of facilities that uses an automated feature extraction algorithm to extract auxiliary observables, and a semi-supervised assisted target recognition algorithm to then identify facilities of interest. We illustrate the approach using an example of finding schools in Quickbird image data of Albuquerque, New Mexico. We use Los Alamos National Laboratory's Genie Pro automated feature extraction algorithm to find a set of auxiliary features that should be useful in the search for schools, such as parking lots, large buildings, sports fields and residential areas and then combine these features using Genie Pro's assisted target recognition algorithm to learn a classifier that finds schools in the image data.

Paper Details

Date Published: 28 April 2009
PDF: 12 pages
Proc. SPIE 7341, Visual Information Processing XVIII, 73410Q (28 April 2009); doi: 10.1117/12.819330
Show Author Affiliations
Neal R. Harvey, Los Alamos National Lab. (United States)
C. Ruggiero, Los Alamos National Lab. (United States)
N. H. Pawley, Los Alamos National Lab. (United States)
B. MacDonald, Los Alamos National Lab. (United States)
A. Oyer, Los Alamos National Lab. (United States)
L. Balick, Los Alamos National Lab. (United States)
S. P. Brumby, Los Alamos National Lab. (United States)


Published in SPIE Proceedings Vol. 7341:
Visual Information Processing XVIII
Zia-Ur Rahman; Stephen E. Reichenbach; Mark Allen Neifeld, Editor(s)

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