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Mars Image Super-Resolution Based on Generative Adversarial Network
2021
IEEE Access
High-resolution (HR) Mars images have great significance for studying the landform features of Mars and analyzing the climate on Mars. Nowadays, the mainstream image super-resolution methods are based on deep learning or CNNs, which are better than traditional methods. However, these deep learning based methods obtain low-resolution(LR) images usually by using an ideal down-sampling method (e.g. bicubic interpolation). There are two limitations in the existing SR methods: 1) The paired LR-HR
doi:10.1109/access.2021.3101858
fatcat:2mikt3gehfhwfecd7w6lg2ty5i