{"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/joint-enhancement-and-denoising-method-via","title":"Joint Enhancement and Denoising Method via Sequential Decomposition","arxiv_id":"1804.08468","date":"2018-04-23","proceeding":null,"authors":["Xutong Ren","Mading Li","Wen-Huang Cheng","Jiaying Liu"],"abstract":"Many low-light enhancement methods ignore intensive noise in original images.\nAs a result, they often simultaneously enhance the noise as well. Furthermore,\nextra denoising procedures adopted by most methods ruin the details. In this\npaper, we introduce a joint low-light enhancement and denoising strategy, aimed\nat obtaining well-enhanced low-light images while getting rid of the inherent\nnoise issue simultaneously. The proposed method performs Retinex model based\ndecomposition in a successive sequence, which sequentially estimates a\npiece-wise smoothed illumination and a noise-suppressed reflectance. After\ngetting the illumination and reflectance map, we adjust the illumination layer\nand generate our enhancement result. In this noise-suppressed sequential\ndecomposition process we enforce the spatial smoothness on each component and\nskillfully make use of weight matrices to suppress the noise and improve the\ncontrast. Results of extensive experiments demonstrate the effectiveness and\npracticability of our method. It performs well for a wide variety of images,\nand achieves better or comparable quality compared with the state-of-the-art\nmethods.","url_abs":"http://arxiv.org/abs/1804.08468v3","url_pdf":"http://arxiv.org/pdf/1804.08468v3.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":"joint-enhancement-and-denoising-method-via","repo_url":"https://github.com/tonghelen/JED-Method","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1804.08468","atlas_url":"https://app.syntology.ai/?focus=1804.08468","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}