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Proceedings Paper

Spectral/spatial annealing of hyperspectral imagery initialized by a supervised classification method
Author(s): Robert S. Rand
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Paper Abstract

A simulated annealing method of partitioning hyperspectral imagery, initialized by a supervised classification method, is investigated to provide spatially smooth class labeling for terrain mapping applications. The method is used to obtain an estimate of the mode a Gibbs distribution defined over a symmetric spatial neighborhood system that is based on an energy function characterizing spectral disparities in Euclidean distance and spectral angle. Experiments are conducted on a 210-band HYDICE scene that contains a diverse range of terrain features and that is supported with ground truth. Both visual and quantitative results demonstrate a clear benefit of this method as compared to spectral-only supervised classification or unsupervised annealing that has been initialized randomly.

Paper Details

Date Published: 2 August 2002
PDF: 12 pages
Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); doi: 10.1117/12.478757
Show Author Affiliations
Robert S. Rand, Engineering Research and Development Ctr./U.S. Army Corps of Engineers (United States)


Published in SPIE Proceedings Vol. 4725:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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