Tao, Y;
Muller, JP;
(2018)
Repeat multiview panchromatic super-resolution restoration using the UCL MAGiGAN system.
In: Bruzzone, L and Bovolo, F, (eds.)
Image and Signal Processing for Remote Sensing XXIV.
SPIE: Berlin, Germany.
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Abstract
High spatial resolution imaging data is always considered desirable in the field of remote sensing, particularly Earth observation. However, given the physical constraints of the imaging instruments themselves, one needs to be able to trade-off spatial resolution against launch mass as well as telecommunications bandwidth for transmitting data back to the Earth. In this paper, we present a newly developed super-resolution restoration system, called MAGiGAN, based on our original GPT-SRR system combined with deep learning image networks to be able to restore up to 4x higher resolution enhancement using multi-angle repeat images as input.
| Type: | Proceedings paper |
|---|---|
| Title: | Repeat multiview panchromatic super-resolution restoration using the UCL MAGiGAN system |
| Event: | SPIE Remote Sensing |
| Location: | Berlin, Germany |
| Dates: | 10 September 2018 - 13 September 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.2500196 |
| Publisher version: | https://doi.org/10.1117/12.2500196 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10062106 |
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