A normalisation framework for (hyper-)spectral imagery

Surface temperatures above 300 K are detected and are very similar to a reference method. The proposed method, however, seems more robust in case of absorptions visible in the reflectance spectrum near 2000 nm. By introducing a low-pass into the computation of the reflectance parameters, the reflectance behaviour of the surfaces may be derived at different scales. This allows for an iterative refinement of the local surface topography using shape from shading and the computation reflectance parameters. The inferred parameters are derived from all available co-registered images and do not show significant influence of the local surface topography. The results of the empirical correction show that both proposed methods greatly reduce the influence of different phase angles or sensor temperatures.