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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Editor: Stephen A. Burns
  • Vol. 24, Iss. 4 — Apr. 1, 2007
  • pp: 957–966

Reflectance recovery for airborne sensor images of 3D scenes

Kartik Chandra and Glenn Healey  »View Author Affiliations

JOSA A, Vol. 24, Issue 4, pp. 957-966 (2007)

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An airborne sensor measures the radiance spectrum, which is dependent on the spectral reflectance of the ground material, the orientation of the material surface, and the atmospheric and illumination conditions. We present an algorithm to estimate the surface spectral reflectance, given the sensor radiance spectrum corresponding to a single pixel. The algorithm uses a nonlinear physics-based image formation model. A low-dimensional linear subspace model is used for the reflectance spectra. The solar radiance, sky radiance, and path-scattered radiance are dependent on the environmental conditions and viewing geometry, and this interdependence is considered by using a coupled-subspace model for these spectra. The algorithm uses the Levenberg–Marquardt method to estimate the subspace model parameters. We have applied the algorithm to a large set of synthetic and real data.

© 2007 Optical Society of America

OCIS Codes
(150.0150) Machine vision : Machine vision
(150.2950) Machine vision : Illumination

ToC Category:
Machine Vision

Original Manuscript: August 14, 2006
Manuscript Accepted: September 23, 2006
Published: March 14, 2007

Kartik Chandra and Glenn Healey, "Reflectance recovery for airborne sensor images of 3D scenes," J. Opt. Soc. Am. A 24, 957-966 (2007)

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