Deep Spatial-Spectral Information Exploitation for Rapid Hyperspectral Image Super-Resolution

Limited by existing electromagnetic sensors, the hyperspectral image (HSI) is characterized by having a high spectral resolution but a low spatial resolution. The super-resolution (SR) technique, which aims at enhancing the spatial resolution of the input image, is a hot topic in computer vision. This paper presents a rapid HSI SR method based on a deep information distillation network (IDN) and an intra-fusion operation to fully utilize the spatial-spectral information. Specifically, some bands are firstly selected and super-resolved by utilizing their spatial information through IDN. Non-selected bands are super-resolved by spectral interpolation. Moreover, to take a full advantage of the information these non-selected bands conveys, intra-fusion is operated on the input HSI and the spectrally-interpolated high resolution HSI. Contrary to most existed fusion methods which require multiple observations of the same scene, this intra-fusion is more flexible, and makes further utilization of the information the input HSI conveys simultaneously. In addition, this method requires less computation and is more suitable for practical applications. Experimental data and comparative analysis have demonstrated the effectiveness this method.