{"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/multiscale-structural-similarity-for-image","title":"Multiscale structural similarity for image quality assessment","arxiv_id":null,"date":"2004-05-04","proceeding":"The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers 2004 5","authors":["Z. Wang","E.P. Simoncelli","A.C. Bovik"],"abstract":"The structural similarity image quality paradigm is based on the assumption that the human visual system is highly adapted for extracting structural information from the scene, and therefore a measure of structural similarity can provide a good approximation to perceived image quality. This paper proposes a multiscale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions. We develop an image synthesis method to calibrate the parameters that define the relative importance of different scales. Experimental comparisons demonstrate the effectiveness of the proposed method.","url_abs":"https://ieeexplore.ieee.org/document/1292216","url_pdf":"https://www.live.ece.utexas.edu/publications/2003/zw_asil2003_msssim.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":"multiscale-structural-similarity-for-image","repo_url":"https://github.com/VainF/pytorch-msssim","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"multiscale-structural-similarity-for-image","repo_url":"https://github.com/francois-rozet/piqa","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"full-reference-image-quality-assessment","task_name":"Full reference image quality assessment"},{"task_slug":"image-generation","task_name":"Image Generation"},{"task_slug":"image-quality-assessment","task_name":"Image Quality Assessment"},{"task_slug":"video-quality-assessment","task_name":"Video Quality Assessment"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/full-reference-image-quality-assessment-on-4","task":"Full reference image quality assessment","dataset":"DRIQ","model":"MS-SSIM","rank_in_archive_order":10,"of":10,"metrics":{"PLCC":"0.7058","SRCC":"0.6692"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on-3","task":"Full reference image quality assessment","dataset":"ESPL","model":"MS-SSIM","rank_in_archive_order":11,"of":11,"metrics":{"PLCC":"0.7322","SRCC":"0.7247"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on-2","task":"Full reference image quality assessment","dataset":"KADID10K","model":"MS-SSIM","rank_in_archive_order":9,"of":11,"metrics":{"SRCC":"0.8020"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on","task":"Full reference image quality assessment","dataset":"TID2008","model":"MS-SSIM","rank_in_archive_order":10,"of":13,"metrics":{"PLCC":"0.8541","SRCC":"0.8542"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-video-quality-1","task":"Video Quality Assessment","dataset":"MSU FR VQA Database","model":"MS-SSIM","rank_in_archive_order":8,"of":20,"metrics":{"KLCC":"0.7625","PLCC":"0.9375","SRCC":"0.9026"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-sr-qa-dataset","task":"Video Quality Assessment","dataset":"MSU SR-QA Dataset","model":"MS-SSIM Fast","rank_in_archive_order":50,"of":60,"metrics":{"KLCC":"0.18174","PLCC":"0.21800","SROCC":"0.24422","Type":"FR"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-sr-qa-dataset","task":"Video Quality Assessment","dataset":"MSU SR-QA Dataset","model":"MS-SSIM Precise","rank_in_archive_order":51,"of":60,"metrics":{"KLCC":"0.17468","PLCC":"0.20935","SROCC":"0.23108","Type":"FR"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-sr-qa-dataset","task":"Video Quality Assessment","dataset":"MSU SR-QA Dataset","model":"MS-SSIM Superfast","rank_in_archive_order":53,"of":60,"metrics":{"KLCC":"0.16578","PLCC":"0.30014","SROCC":"0.21604","Type":"FR"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-sr-qa-dataset","task":"Video Quality Assessment","dataset":"MSU SR-QA Dataset","model":"MS-SSIM","rank_in_archive_order":59,"of":60,"metrics":{"KLCC":"0.07821","PLCC":"0.16035","SROCC":"0.11017","Type":"FR"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}