Papers › Multiscale structural similarity for image quality assessment

Multiscale structural similarity for image quality assessment

4 May 2004The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers 2004 5archive 2025-07-28

Z. Wang, E.P. Simoncelli, A.C. Bovik

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.

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Tasks

Full reference image quality assessmentImage GenerationImage Quality AssessmentVideo Quality Assessment

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Full reference image quality assessment DRIQ MS-SSIM PLCC 0.7058 #10 of 10 Archive leaderboard report
Full reference image quality assessment DRIQ MS-SSIM SRCC 0.6692 #10 of 10 Archive leaderboard report
Full reference image quality assessment ESPL MS-SSIM PLCC 0.7322 #11 of 11 Archive leaderboard report
Full reference image quality assessment ESPL MS-SSIM SRCC 0.7247 #11 of 11 Archive leaderboard report
Full reference image quality assessment KADID10K MS-SSIM SRCC 0.8020 #9 of 11 Archive leaderboard report
Full reference image quality assessment TID2008 MS-SSIM PLCC 0.8541 #10 of 13 Archive leaderboard report
Full reference image quality assessment TID2008 MS-SSIM SRCC 0.8542 #10 of 13 Archive leaderboard report
Video Quality Assessment MSU FR VQA Database MS-SSIM KLCC 0.7625 #8 of 20 Archive leaderboard report
Video Quality Assessment MSU FR VQA Database MS-SSIM PLCC 0.9375 #8 of 20 Archive leaderboard report
Video Quality Assessment MSU FR VQA Database MS-SSIM SRCC 0.9026 #8 of 20 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Fast KLCC 0.18174 #50 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Fast PLCC 0.21800 #50 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Fast SROCC 0.24422 #50 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Fast Type FR #50 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Precise KLCC 0.17468 #51 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Precise PLCC 0.20935 #51 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Precise SROCC 0.23108 #51 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Precise Type FR #51 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Superfast KLCC 0.16578 #53 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Superfast PLCC 0.30014 #53 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Superfast SROCC 0.21604 #53 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Superfast Type FR #53 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM KLCC 0.07821 #59 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM PLCC 0.16035 #59 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM SROCC 0.11017 #59 of 60 Archive leaderboard report
Video Quality Assessment MSU SR-QA Dataset MS-SSIM Type FR #59 of 60 Archive leaderboard report

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