{"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/multimodal-sensor-fusion-in-single-thermal","title":"Multimodal Sensor Fusion In Single Thermal image Super-Resolution","arxiv_id":"1812.09276","date":"2018-12-21","proceeding":null,"authors":["Feras Almasri","Olivier Debeir"],"abstract":"With the fast growth in the visual surveillance and security sectors, thermal\ninfrared images have become increasingly necessary ina large variety of\nindustrial applications. This is true even though IR sensors are still more\nexpensive than their RGB counterpart having the same resolution. In this paper,\nwe propose a deep learning solution to enhance the thermal image resolution.\nThe following results are given:(I) Introduction of a multimodal,\nvisual-thermal fusion model that ad-dresses thermal image super-resolution, via\nintegrating high-frequency information from the visual image. (II)\nInvestigation of different net-work architecture schemes in the literature,\ntheir up-sampling methods,learning procedures, and their optimization functions\nby showing their beneficial contribution to the super-resolution problem. (III)\nA bench-mark ULB17-VT dataset that contains thermal images and their visual\nimages counterpart is presented. (IV) Presentation of a qualitative evaluation\nof a large test set with 58 samples and 22 raters which shows that our proposed\nmodel performs better against state-of-the-arts.","url_abs":"http://arxiv.org/abs/1812.09276v1","url_pdf":"http://arxiv.org/pdf/1812.09276v1.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":"multimodal-sensor-fusion-in-single-thermal","repo_url":"https://github.com/fsalmasri/MSF-STI-SR","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"image-super-resolution","task_name":"Image Super-Resolution"},{"task_slug":"sensor-fusion","task_name":"Sensor Fusion"},{"task_slug":"super-resolution","task_name":"Super-Resolution"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1812.09276","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}