{"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/a-brief-review-of-real-world-color-image","title":"A Brief Review of Real-World Color Image Denoising","arxiv_id":"1809.03298","date":"2018-09-10","proceeding":null,"authors":["Zhaoming Kong","Xiaowei Yang"],"abstract":"Filtering real-world color images is challenging due to the complexity of\nnoise that can not be formulated as a certain distribution. However, the rapid\ndevelopment of camera lens pos- es greater demands on image denoising in terms\nof both efficiency and effectiveness. Currently, the most widely accepted\nframework employs the combination of transform domain techniques and nonlocal\nsimilarity characteristics of natural images. Based on this framework, many\ncompetitive methods model the correlation of R, G, B channels with pre-defined\nor adaptively learned transforms. In this chapter, a brief review of related\nmethods and publicly available datasets is presented, moreover, a new dataset\nthat includes more natural outdoor scenes is introduced. Extensive experiments\nare performed and discussion on visual effect enhancement is included.","url_abs":"http://arxiv.org/abs/1809.03298v1","url_pdf":"http://arxiv.org/pdf/1809.03298v1.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":"a-brief-review-of-real-world-color-image","repo_url":"https://github.com/ZhaomingKong/color_image_denoising","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"color-image-denoising","task_name":"Color Image Denoising"},{"task_slug":"denoising","task_name":"Denoising"},{"task_slug":"image-denoising","task_name":"Image Denoising"},{"task_slug":"pos","task_name":"POS"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}