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Proceedings Paper

Using coupled subspace models for reflectance/illumination separation
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Paper Abstract

We present a nonlinear algorithm for estimating surface spectral reflectance from the spectral radiance measured by an airborne sensor. Estimation of surface reflectance is of importance since it is independent of the atmospheric and illumination conditions. The nonlinear separation algorithm uses a low-dimensional subspace model for the reflectance spectra. The algorithm also considers the inter-dependence of the path radiance and illumination spectra by using a coupled subspace model. We have applied the algorithm to a large set of simulated 0.4-1.74 micron sensor radiance spectra. A database of reflectance vectors and MODTRAN illumination, path radiance, and upward transmittance vectors for different atmospheric conditions were used to generate the sensor radiance spectra. We have examined the use of the recovered reflectance vectors for material identification over a database of materials.

Paper Details

Date Published: 12 August 2004
PDF: 11 pages
Proc. SPIE 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, (12 August 2004); doi: 10.1117/12.542759
Show Author Affiliations
Kartik Chandra, Univ. of California/Irvine (United States)
Glenn E. Healey, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 5425:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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