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Fusing a low-resolution hyperspectral image (HSI) and a high-resolutionmultispectral image (MSI) of the same scene leads to a super-resolution image(SRI), which is information rich spatially and spectrally. In this paper, wesuper-resolve the HSI using the graph Laplacian defined on the MSI. Unlike manyexisting works, we don't assume prior knowledge about the spatial degradationfrom SRI to HSI, nor a perfectly aligned HSI and MSI pair. Our algorithmprogressively alternates between finding the blur kernel and fusing HSI withMSI, generating accurate estimations of the blur kernel and the SRI atconvergence. Experiments on various datasets demonstrate the advantages of theproposed algorithm in the quality of fusion and its capability in dealing withunknown spatial degradation.

Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization