{"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/no-reference-quality-assessment-of-contrast","title":"No-Reference Quality Assessment of Contrast-Distorted Images using Contrast Enhancement","arxiv_id":"1904.08879","date":"2019-04-18","proceeding":null,"authors":["Jia Yan","Jie Li","Xin Fu"],"abstract":"No-reference image quality assessment (NR-IQA) aims to measure the image\nquality without reference image. However, contrast distortion has been\noverlooked in the current research of NR-IQA. In this paper, we propose a very\nsimple but effective metric for predicting quality of contrast-altered images\nbased on the fact that a high-contrast image is often more similar to its\ncontrast enhanced image. Specifically, we first generate an enhanced image\nthrough histogram equalization. We then calculate the similarity of the\noriginal image and the enhanced one by using structural-similarity index (SSIM)\nas the first feature. Further, we calculate the histogram based entropy and\ncross entropy between the original image and the enhanced one respectively, to\ngain a sum of 4 features. Finally, we learn a regression module to fuse the\naforementioned 5 features for inferring the quality score. Experiments on four\npublicly available databases validate the superiority and efficiency of the\nproposed technique.","url_abs":"http://arxiv.org/abs/1904.08879v1","url_pdf":"http://arxiv.org/pdf/1904.08879v1.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":"no-reference-quality-assessment-of-contrast","repo_url":"https://github.com/mtobeiyf/CEIQ","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"no-reference-quality-assessment-of-contrast","repo_url":"https://github.com/steffensbola/blind_iqa_contrast","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"image-quality-assessment","task_name":"Image Quality Assessment"},{"task_slug":"no-reference-image-quality-assessment","task_name":"No-Reference Image Quality Assessment"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1904.08879","atlas_url":"https://app.syntology.ai/?focus=1904.08879","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}