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- W4312477775 abstract "Single-frame super-resolution (SFSR) is a well-researched issue in inverse imaging with the latest developments in the field of hyperspectral remote sensing. Paucity of open-source very high-resolution benchmark datasets restricts these algorithms from being applied to real-world scenes captured by hyperspectral sensors and the users have to contain with the outputs of the simulated trials. We attempt to narrow down this void by generating 15 m spatial resolution datasets from the 30 m spatial resolution Hyperion dataset of Ahmedabad, India through two classic SFSR algorithms: iterative back projection (IBP) and sparse representation (VSR). Visually inspecting land cover features and their spectral profiles in the super-resolved results against open-source panchromatic data shows the successful preservation of the spectral and spatial content of the original Hyperion data by VSR. No-reference image quality metrics confirm this finding although the processing time remains quite high compared to IBP." @default.
- W4312477775 created "2023-01-05" @default.
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- W4312477775 date "2022-09-13" @default.
- W4312477775 modified "2023-10-16" @default.
- W4312477775 title "Single-Frame Super-Resolution Of Real-World Spaceborne Hyperspectral Data" @default.
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- W4312477775 doi "https://doi.org/10.1109/whispers56178.2022.9955121" @default.
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