Reflectance/illumination separation for 3D scenes

The spectral radiance measured by an airborne sensor is dependent on the spectral reflectance of the ground material, the orientation of the material surface, and the atmospheric and illumination conditions. We present a non-linear algorithm to estimate the surface spectral reflectance given the sensor radiance spectrum corresponding to a single pixel. The algorithm uses a low-dimensional subspace model for the reflectance spectra. The solar radiance, sky radiance, and path-scattered radiance are dependent on the environmental condition and viewing geometry and this inter-dependence is considered by using a coupled subspace model for these spectra. The algorithm uses the Levenberg-Marquardt method to estimate the subspace model parameters which are used to determine the reflectance spectrum. We have applied the algorithm to a large set of 0.42-1.74 micron sensor radiance spectra simulated for different atmospheric conditions, materials, and surface orientations. We have also examined the utility of the algorithm for reflectance recovery in digital imaging and remote sensing image generation (DIRSIG) scenes that contain 3D objects.