DEM construction and calibration of hyperspectral image data using pairs of radiance images

In lunar remote sensing, the analysis of the spectral reflectance of iron-bearing minerals is a widely used method. For an accurate calibration, elevation information about the surface has to be known. In this paper we present a framework for the reconstruction of digital elevation maps (DEM) from hyperspectral imagery and preexisting elevation data of lower lateral resolution. The reconstruction algorithm consists of a combined photoclinometry and shape from shading scheme, which is extended towards photometric stereo using multiple images. In order to register images of the same surface region acquired under different illumination conditions, an image registration approach is derived from the DEM construction methods. Image registration is performed in the illumination-invariant surface gradient space and is therefore able to cope with images taken under different illumination conditions. Finally, the calibration of hyperspectral imagery based on the DEM is demonstrated by the analysis of extracted spectral features.