{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T02:08:03Z","timestamp":1773713283272,"version":"3.50.1"},"reference-count":33,"publisher":"American Institute of Aeronautics and Astronautics (AIAA)","issue":"8","content-domain":{"domain":["arc.aiaa.org"],"crossmark-restriction":true},"short-container-title":["Journal of Aerospace Information Systems"],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p> Many onboard vision tasks for spacecraft navigation require high-quality remote-sensing images with clearly decipherable features. However, design constraints and the operational and environmental conditions limit their quality. Enhancing images through postprocessing is a cost-efficient solution. Current deep learning methods that enhance low-resolution images through super-resolution do not quantify network uncertainty of predictions and are trained at a single scale, which hinders practical integration in image-acquisition pipelines. This work proposes performing multiscale super-resolution using a deep normalizing flow network for uncertainty-quantified and Monte Carlo estimates so that image enhancement for spacecraft vision tasks may be more robust and predictable. The proposed network architecture outperforms state-of-the-art super-resolution models on in-orbit lunar imagery data. Simulations demonstrate its viability on task-based evaluations for landmark identification. <\/jats:p>","DOI":"10.2514\/1.i011089","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T09:47:23Z","timestamp":1683107243000},"page":"473-488","update-policy":"https:\/\/doi.org\/10.2514\/aiaa_crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Multiscale Super-Resolution Remote Imaging via Deep Conditional Normalizing Flows"],"prefix":"10.2514","volume":"20","author":[{"given":"Aneesh M.","family":"Heintz","sequence":"first","affiliation":[{"name":"Cornell University, Ithaca, New York 14850"}]},{"given":"Mason","family":"Peck","sequence":"additional","affiliation":[{"name":"Cornell University, Ithaca, New York 14850"}]},{"given":"Ian","family":"Mackey","sequence":"additional","affiliation":[{"name":"Cornell University, Ithaca, New York 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