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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 19, Iss. 3 — Mar. 1, 2002
  • pp: 549–557

Invariant identification of material mixtures in airborne spectrometer data

Pei-hsiu Suen and Glenn Healey  »View Author Affiliations


JOSA A, Vol. 19, Issue 3, pp. 549-557 (2002)
http://dx.doi.org/10.1364/JOSAA.19.000549


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Abstract

We present an algorithm for identifying linear mixtures of a specified set of materials in 0.4–2.5 µm airborne imaging spectrometer data. The algorithm is invariant to the illumination and atmospheric conditions and the relative amounts of the specified materials within a pixel. Only the spectral reflectance functions for the specified materials are required by the algorithm. Invariance over illumination and atmospheric conditions is achieved by incorporating a physical model for scene variability in the constrained optimization formulation. The algorithm also computes estimates of the amounts of the specified materials in identified mixtures. We demonstrate the effectiveness of the algorithm by using real and synthetic Hyperspectral Digital Imaging Collection Experiment imagery acquired over a range of conditions and altitudes.

© 2002 Optical Society of America

OCIS Codes
(150.0150) Machine vision : Machine vision
(280.0280) Remote sensing and sensors : Remote sensing and sensors

History
Original Manuscript: March 6, 2001
Revised Manuscript: July 11, 2001
Manuscript Accepted: April 19, 2001
Published: March 1, 2002

Citation
Pei-hsiu Suen and Glenn Healey, "Invariant identification of material mixtures in airborne spectrometer data," J. Opt. Soc. Am. A 19, 549-557 (2002)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-19-3-549

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