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The perceptual loss is added to the loss function, and a large-scale dataset is constructed for boosting the performance of GEU-Net. Experimental results show that the proposed GEU-Net can achieve superior fusion performance than some state-of-the-art methods in both human visual quality, objective assessment and network complexity.Traditional tensor decomposition methods, e.g., two dimensional principal component analysis and two dimensional singular value decomposition, that minimize mean square errors, are sensitive to outliers. To o
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