DiriNet: A network to estimate the spatial and spectral degradation functions. (arXiv:2201.12346v1 [cs.CV])

The spatial and spectral degradation functions are critical to hyper- and
multi-spectral image fusion. However, few work has been payed on the estimation
of the degradation functions. To learn the spatial response function and the
point spread function from the image pairs to be fused, we propose a Dirichlet
network, where both functions are properly constrained. Specifically, the
spatial response function is constrained with positivity, while the Dirichlet
distribution along with a total variation is imposed on the point spread
function. To the best of our knowledge, the neural netwrok and the Dirichlet
regularization are exclusively investigated, for the first time, to estimate
the degradation functions. Both image degradation and fusion experiments
demonstrate the effectiveness and superiority of the proposed Dirichlet
network.

Source: https://arxiv.org/abs/2201.12346

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