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Difference Curvature Multidimensional Network for Hyperspectral Image Super-Resolution
2021
Remote Sensing
In recent years, convolutional-neural-network-based methods have been introduced to the field of hyperspectral image super-resolution following their great success in the field of RGB image super-resolution. However, hyperspectral images appear different from RGB images in that they have high dimensionality, implying a redundancy in the high-dimensional space. Existing approaches struggle in learning the spectral correlation and spatial priors, leading to inferior performance. In this paper, we
doi:10.3390/rs13173455
fatcat:6pbl3l2circ6bbcwnh6lmik564