LAUSR

The fusion of hyperspectral image (HSI) and multispectral image (MSI) refers to enhance the spatial resolution of HSI with the help of a corresponding MSI that has a high spatial resolution to finally obtain an HSI with high resolution in both spatial and spectral domains. In this letter, we propose a variational tensor subspace decomposition-based fusion method to fully explore the differences and correlations among three modes of the HSI tensor. Experimental results on two HSI datasets show that the proposed method can achieve superior performance compared with existing state-of-the-art fusion methods with high computational efficiency.