To improve the spatial resolution of a hyperspectral (HS) observation of a scene with the aid of an auxiliary multispectral (MS) observation, a new spectral unmixing-based HS and MS image fusion approach is presented in this paper. In the proposed fusion approach, linear spectral unmixing with sparsity constraint is employed, by taking the impact of linear observation model on linear mixing model into consideration. Simulative experiment is employed for verification and comparison. It is illustrated that the proposed approach would be more promising for practical utilization compared to some state-of-the-art approaches, due to its good balance between fusion performance and calculation cost.
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