Edge-preserving nonnegative deconvolution of hyperspectral fluorescence microscopy images
Résumé
In many hyperspectral image restoration problems, some prior information is available, such as the spatial and/or spectral regularity of the solution. Additionally, a nonnegativ-ity constraint must often be imposed to provide a physically meaningful estimate. The restored image is then obtained as the constrained minimizer of a penalized convex criterion. In this paper, we propose a fast algorithm for edge-preserving hyperspectral image restoration.
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