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Proceedings Paper

Subpixel object detection and fraction estimation in hyperspectral imagery
Author(s): A. Evan Iverson
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Paper Abstract

The detection of objects of subpixel size in high-spectral- resolution imagery is a subject of much current interest. In this paper, we discuss this subject from a practical perspective and then develop a mathematical foundation for the detection of subpixel objects for which the spectral signature is either known or unknown. We capitalize on techniques from linear algebra that theoretically allow the projection of each pixel in the image onto a subspace orthogonal to the subspace defined by the interfering spectra. Using the properties of projection operators, a technique is developed for estimating an orthogonal-subspace projection operator using the singular value decomposition when interfering background spectra are unknown. We then show how a vector operator of interest. Finally, we discuss algorithm performance characterization and present some preliminary results based on Monte Carlo simulations.

Paper Details

Date Published: 4 August 1997
PDF: 12 pages
Proc. SPIE 3071, Algorithms for Multispectral and Hyperspectral Imagery III, (4 August 1997); doi: 10.1117/12.280585
Show Author Affiliations
A. Evan Iverson, Science Applications International Corp. (United States)


Published in SPIE Proceedings Vol. 3071:
Algorithms for Multispectral and Hyperspectral Imagery III
A. Evan Iverson; Sylvia S. Shen, Editor(s)

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