{"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/rough-set-based-color-channel-selection","title":"Rough Set Based Color Channel Selection","arxiv_id":"1611.00931","date":"2016-11-03","proceeding":null,"authors":["Soumyabrata Dev","Florian M. Savoy","Yee Hui Lee","Stefan Winkler"],"abstract":"Color channel selection is essential for accurate segmentation of sky and\nclouds in images obtained from ground-based sky cameras. Most prior works in\ncloud segmentation use threshold based methods on color channels selected in an\nad-hoc manner. In this letter, we propose the use of rough sets for color\nchannel selection in visible-light images. Our proposed approach assesses color\nchannels with respect to their contribution for segmentation, and identifies\nthe most effective ones.","url_abs":"http://arxiv.org/abs/1611.00931v1","url_pdf":"http://arxiv.org/pdf/1611.00931v1.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":"rough-set-based-color-channel-selection","repo_url":"https://github.com/Soumyabrata/rough-sets","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"segmentation","task_name":"Segmentation"},{"task_slug":"channel-selection","task_name":"channel selection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}