{"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/power-of-tempospatially-unified-spectral","title":"Power of Tempospatially Unified Spectral Density for Perceptual Video Quality Assessment","arxiv_id":"1812.05177","date":"2018-12-12","proceeding":null,"authors":["Mohammed A. Aabed","Gukyeong Kwon","Ghassan AlRegib"],"abstract":"We propose a perceptual video quality assessment (PVQA) metric for distorted\nvideos by analyzing the power spectral density (PSD) of a group of pictures.\nThis is an estimation approach that relies on the changes in video dynamic\ncalculated in the frequency domain and are primarily caused by distortion. We\nobtain a feature map by processing a 3D PSD tensor obtained from a set of\ndistorted frames. This is a full-reference tempospatial approach that considers\nboth temporal and spatial PSD characteristics. This makes it ubiquitously\nsuitable for videos with varying motion patterns and spatial contents. Our\ntechnique does not make any assumptions on the coding conditions, streaming\nconditions or distortion. This approach is also computationally inexpensive\nwhich makes it feasible for real-time and practical implementations. We\nvalidate our proposed metric by testing it on a variety of distorted sequences\nfrom PVQA databases. The results show that our metric estimates the perceptual\nquality at the sequence level accurately. We report the correlation\ncoefficients with the differential mean opinion scores (DMOS) reported in the\ndatabases. The results show high and competitive correlations compared with the\nstate of the art techniques.","url_abs":"http://arxiv.org/abs/1812.05177v1","url_pdf":"http://arxiv.org/pdf/1812.05177v1.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":"power-of-tempospatially-unified-spectral","repo_url":"https://github.com/gukyeongkwon/3DPSD-VQA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"power-of-tempospatially-unified-spectral","repo_url":"https://github.com/olivesgatech/3DPSD-VQA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"video-quality-assessment","task_name":"Video Quality Assessment"}],"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}