Proceedings Paper
Simulation framework for spatio-spectral anomalous change detection| Format | Member Price | Non-Member Price |
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Paper Abstract
We describe the development of a simulation framework for anomalous change detection that considers both the
spatial and spectral aspects of the imagery. A purely spectral framework has previously been introduced, but
the extension to spatio-spectral requires attention to a variety of new issues, and requires more careful modeling
of the anomalous changes. Using this extended framework, we evaluate the utility of spatial image processing
operators to enhance change detection sensitivity in (simulated) remote sensing imagery.
Paper Details
Date Published: 27 April 2009
PDF: 12 pages
Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73340P (27 April 2009); doi: 10.1117/12.818632
Published in SPIE Proceedings Vol. 7334:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV
Sylvia S. Shen; Paul E. Lewis, Editor(s)
PDF: 12 pages
Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73340P (27 April 2009); doi: 10.1117/12.818632
Show Author Affiliations
James Theiler, Los Alamos National Lab. (United States)
Neal R. Harvey, Los Alamos National Lab. (United States)
Neal R. Harvey, Los Alamos National Lab. (United States)
Reid Porter, Los Alamos National Lab. (United States)
Brendt Wohlberg, Los Alamos National Lab. (United States)
Brendt Wohlberg, Los Alamos National Lab. (United States)
Published in SPIE Proceedings Vol. 7334:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV
Sylvia S. Shen; Paul E. Lewis, Editor(s)
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