Variational image fusion approach based on TGV and local information

In this study, the authors propose a variational approach based on total generalised variation (TGV) and local gradient information to fuse multi-focus images as well as medical images of computed tomography and magnetic resonance. They use the second-order TGV as the regularisation term and local gradient information as the fusion weight to extract image features. To compute the new model effectively, the primal-dual algorithm is carried out. Various experiments are made to verify the effectiveness of the proposed methods.

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