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Proceedings Paper

Recognizing 3D objects in hyperspectral images under unknown conditions
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Paper Abstract

We present models and algorithms for recognizing 3D objects in airborne 0.4-2.5 micron hyperspectral images acquired under unknown conditions. Objects of interest exhibit complex geometries with surfaces of different materials. The DIRSIG image generation software is used to build spatial/spectral surfaces of different materials. The DIRSIG image generation software is used to build spatial/spectral subspace models for the objects that capture a range of atmospheric and illumination conditions and viewing geometries. Since we consider scales for which multiple materials will mix in a pixel, the object subspace models also account for spectral mixing. An important aspect of the work is the use of methods for partitioning object subspaces to optimize performance. The new algorithms have been evaluated using hyperspectral data that has been synthesized for a range of conditions.

Paper Details

Date Published: 20 August 2001
PDF: 11 pages
Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437048
Show Author Affiliations
Zhihong Pan, Univ. of California/Irvine (United States)
Glenn Healey, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 4381:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII
Sylvia S. Shen; Michael R. Descour, Editor(s)

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