Repeat multiview panchromatic super-resolution restoration using the UCL MAGiGAN system

Y. Tao; J.-P. Muller

doi:10.1117/12.2500196

9 October 2018 Repeat multiview panchromatic super-resolution restoration using the UCL MAGiGAN system

Y. Tao, J.-P. Muller

Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 1078903 (2018) https://doi.org/10.1117/12.2500196
Event: SPIE Remote Sensing, 2018, Berlin, Germany

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.

Conference Presentation

Citation Download Citation

Y. Tao and J.-P. Muller "Repeat multiview panchromatic super-resolution restoration using the UCL MAGiGAN system", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 1078903 (9 October 2018); https://doi.org/10.1117/12.2500196

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