{"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/high-dynamic-range-imaging-for-cloud","title":"High-Dynamic-Range Imaging for Cloud Segmentation","arxiv_id":"1803.01071","date":"2018-03-02","proceeding":null,"authors":["Soumyabrata Dev","Florian M. Savoy","Yee Hui Lee","Stefan Winkler"],"abstract":"Sky/cloud images obtained from ground-based sky-cameras are usually captured\nusing a fish-eye lens with a wide field of view. However, the sky exhibits a\nlarge dynamic range in terms of luminance, more than a conventional camera can\ncapture. It is thus difficult to capture the details of an entire scene with a\nregular camera in a single shot. In most cases, the circumsolar region is\nover-exposed, and the regions near the horizon are under-exposed. This renders\ncloud segmentation for such images difficult. In this paper, we propose\nHDRCloudSeg -- an effective method for cloud segmentation using\nHigh-Dynamic-Range (HDR) imaging based on multi-exposure fusion. We describe\nthe HDR image generation process and release a new database to the community\nfor benchmarking. Our proposed approach is the first using HDR radiance maps\nfor cloud segmentation and achieves very good results.","url_abs":"http://arxiv.org/abs/1803.01071v1","url_pdf":"http://arxiv.org/pdf/1803.01071v1.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":"high-dynamic-range-imaging-for-cloud","repo_url":"https://github.com/Soumyabrata/HDR-cloud-segmentation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"benchmarking","task_name":"Benchmarking"},{"task_slug":"image-generation","task_name":"Image Generation"},{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"high","task_name":"Vocal Bursts Intensity Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}