Estimation of relative sensor characteristics for hyperspectral super-resolution

To enhance the spatial resolution of hyperspectral data, additional multispectral images of higher resolution can be used. However, to combine the two data sources information about the sensors is needed. In this paper we derive a model to estimate the relative spatial and spectral response of the two sensors. The proposed formulation includes non-negativity, recovers remaining registration (shift) errors, and uses prior information to adjust to the shape of the spectral response with either l1 or l2 norm regularization. The framework is tested both with real data and with simulated data where the ground truth is known.