A Variational Formulation for Hyperspectral and Multispectral Image Fusion

We propose a new convex variational model for hyperspectral and multispectral image fusion. Our approach introduces nonlocal regularization conditioned to the geometry of the multispectral image and incorporates a constraint forcing the fusion product and the multispectral data to share modulated high frequencies. The proposed method is compared with state-of-the-art fusion techniques, showing competitive results for several quality metrics on different data.