
Proceedings Paper
Hyperspectral imagery transformations using real and imaginary features for improved classificationFormat | Member Price | Non-Member Price |
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Paper Abstract
Several studies have reported that the use of derived spectral features, in addition to the original hyperspectral data, can
facilitate the separation of similar classes. Linear and nonlinear transformations are employed to project data into
mathematical spaces with the expectation that the decision surfaces separating similar classes become well defined.
Therefore, the problem of discerning similar classes in expanded space becomes more tractable. Recent work presented
by one of the authors discusses a dimension expansion technique based on generating real and imaginary complex
features from the original hyperspectral signatures. A complex spectral angle mapper was employed to classify the data.
In this paper, we extend this method to include other approaches that generate derivative-like and wavelet-based spectral
features from the original data. These methods were tested with several supervised classification methods with two
Hyperspectral Image (HSI) cubes.
Paper Details
Date Published: 7 May 2007
PDF: 10 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65651B (7 May 2007); doi: 10.1117/12.718932
Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)
PDF: 10 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65651B (7 May 2007); doi: 10.1117/12.718932
Show Author Affiliations
Alexey Castrodad, National Geospatial-Intelligence Agency (United States)
Edward H. Bosch, National Geospatial-Intelligence Agency (United States)
Edward H. Bosch, National Geospatial-Intelligence Agency (United States)
Ronald Resmini, National Geospatial-Intelligence Agency (United States)
Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)
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