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Proceedings Paper

Recovering surface properties for hyperspectral scenes
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Paper Abstract

We present an algorithm to estimate the orientation of a ground material corresponding to a pixel in a hyperspectral image acquired by an airborne sensor under unknown atmospheric conditions. A physics-based image formation model is used in which the spectral reflectance of the ground material, orientation of the material surface, and the atmospheric and illumination conditions determine the sensor radiance of a pixel. The algorithm uses a low-dimensional coupled subspace model for the solar radiance, sky radiance, and path-scattered radiance. The common inter-dependence of these spectra on the environmental condition and viewing geometry is considered by using the coupled subspace model. The physics-based image formation model used by the algorithm uses two orientation parameters which are used to determine the surface orientation. A constrained nonlinear optimization method is used to estimate the orientation and the coupled-subspace model parameters. We have tested the utility of our algorithm using a large set of 0.42-1.74 micron sensor radiance spectra simulated for varying surface orientations of different materials.

Paper Details

Date Published: 4 May 2006
PDF: 9 pages
Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331H (4 May 2006); doi: 10.1117/12.668216
Show Author Affiliations
Kartik Chandra, Univ. of California/Irvine (United States)
Glenn Healey, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 6233:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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