{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/nightvision-generating-nighttime-satellite","title":"NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations","arxiv_id":"2011.07017","date":"2020-11-13","proceeding":null,"authors":["Paula Harder","William Jones","Redouane Lguensat","Shahine Bouabid","James Fulton","Dánell Quesada-Chacón","Aris Marcolongo","Sofija Stefanović","Yuhan Rao","Peter Manshausen","Duncan Watson-Parris"],"abstract":"The recent explosion in applications of machine learning to satellite imagery often rely on visible images and therefore suffer from a lack of data during the night. The gap can be filled by employing available infra-red observations to generate visible images. This work presents how deep learning can be applied successfully to create those images by using U-Net based architectures. The proposed methods show promising results, achieving a structural similarity index (SSIM) up to 86\\% on an independent test set and providing visually convincing output images, generated from infra-red observations.","url_abs":"https://arxiv.org/abs/2011.07017v2","url_pdf":"https://arxiv.org/pdf/2011.07017v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"nightvision-generating-nighttime-satellite","repo_url":"https://github.com/paulaharder/hackathon-ci-2020","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"ssim","task_name":"SSIM"}],"methods":[{"method_slug":"concatenated-skip-connection","method_name":"Concatenated Skip Connection"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"u-net","method_name":"U-Net"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}