This project proposes to apply super-resolution algorithm for multi-spectral or hyperspectral remote sensing images. The underlying idea implicit prior from a set of high-resolution training examples to model the relation between LR and HR images. The matrix-based implicit prior is learned as a regression operator using conjugate decent method. The direct relation between LR and HR image is obtained from the regression operator and it is used to super-resolve low-resolution multi-spectral ad hyperspectral remote sensing images.
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