Validation of forward modeling target detection approach on a new hyperspectral data set featuring an urban scenario and variable illumination conditions

An experimental study is presented with the goal of investigating application of the forward modeling (FM) approach to target detection to hyperspectral images acquired over an urban scenario, where the effects of variability and uncertainty of atmospheric and illumination conditions are enhanced. The study exploits the availability of a new hyperspectral data set acquired in May 2013 over the city of Viareggio, Italy. A physics-based model is assumed for radiation transfer in the atmosphere and variability around nominal acquisition conditions is accounted for by means of multiple executions of a radiative transfer code and a subspace-based target detection framework. Experimental results featuring several ground-truthed targets in an urban scenario confirm the effectiveness of the FM target detection approach.