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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 43, Iss. 2 — Jan. 10, 2004
  • pp: 227–236

Feature Reduction and Morphological Processing for Hyperspectral Image Data

David Casasent and Xue-Wen Chen  »View Author Affiliations


Applied Optics, Vol. 43, Issue 2, pp. 227-236 (2004)
http://dx.doi.org/10.1364/AO.43.000227


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Abstract

An automatic target detection system that uses hyperspectral (HS) imagery is proposed. HS images contain both spatial and spectral response information that provides detailed descriptions of an object. These new, to our knowledge, sensor data are useful in automatic target recognition applications. To provide discrimination information from the HS images and to select features that generalize well, we describe a new, to our knowledge, high-dimensional generalized discriminant feature-extraction algorithm and compare its performance with that of other feature-reduction methods for two HS target detection applications (mine and vehicle detection) by using a nearest-neighbor classifier. We also advance an approach to simultaneously optimize both spatial and spectral responses.

© 2004 Optical Society of America

OCIS Codes
(040.1880) Detectors : Detection
(100.2000) Image processing : Digital image processing
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition

Citation
David Casasent and Xue-Wen Chen, "Feature Reduction and Morphological Processing for Hyperspectral Image Data," Appl. Opt. 43, 227-236 (2004)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-43-2-227


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