Spectral imaging sensors often suffer from low spatial resolution, as there exists an essential tradeoff between the spectral and spatial resolutions that can be simultaneously achieved, especially when the temporal resolution needs to be ...
In recent years, deep convolutional neural networks (CNNs) have been widely exploited for the hyperspectral image (HSI) super-resolution and obtained remarkable performance. However, most of the existing CNN-based methods have two main ...
Recently, single hyperspectral image super-resolution (SR) methods based on deep learning have been extensively studied. However, there has been limited technical development focusing on single hyperspectral image super-resolution due to the high-...
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