Recovering surface properties for hyperspectral scenes

Kartik Chandra; Glenn Healey

doi:10.1117/12.668216

4 May 2006 Recovering surface properties for hyperspectral scenes

Kartik Chandra, Glenn Healey

Proceedings Volume 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII; 62331H (2006) https://doi.org/10.1117/12.668216
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

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.

Citation Download Citation

Kartik Chandra and Glenn Healey "Recovering surface properties for hyperspectral scenes", Proc. SPIE 6233, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XII, 62331H (4 May 2006); https://doi.org/10.1117/12.668216

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