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Proceedings Paper

Super-resolution restoration of spaceborne HD videos using the UCL MAGiGAN system
Author(s): Y. Tao; J-P. Muller
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Paper Abstract

We developed a novel SRR system, called Multi-Angle Gotcha image restoration with Generative Adversarial Network (MAGiGAN), to produce resolution enhancement of 3-5 times from multi-pass EO images. The MAGiGAN SRR system uses a combination of photogrammetric and machine vision approaches including image segmentation and shadow labelling, feature matching and densification, estimation of an image degradation model, and deep learning approaches, to retrieve image information from distorted features and training networks. We have tested the MAGiGAN SRR using the NVIDIA® Jetson TX-2 GPU card for onboard processing within a smart-satellite capturing high definition satellite videos, which will enable many innovative remote-sensing applications to be implemented in the future. In this paper, we show SRR processing results from a Planet® SkySat HD 70cm spaceborne video using a GPU version of the MAGiGAN system. Image quality and effective resolution enhancement are measured and discussed.

Paper Details

Date Published: 7 October 2019
PDF: 7 pages
Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 1115508 (7 October 2019); doi: 10.1117/12.2532889
Show Author Affiliations
Y. Tao, Mullard Space Science Lab. (United Kingdom)
J-P. Muller, Mullard Space Science Lab. (United Kingdom)

Published in SPIE Proceedings Vol. 11155:
Image and Signal Processing for Remote Sensing XXV
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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