The accuracy of PSNR in predicting video quality for different video scenes and frame rates

Peak Signal-to-Noise Ratio (PSNR) is widely used as a video quality metric or performance indicator. Some studies have indicated that it correlates poorly with subjective quality, whilst others have used it on the basis that it provides a good correlation with subjective data. Existing literature se...

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Bibliographic Details
Published in:Telecommunication systems 2012-01, Vol.49 (1), p.35-48
Main Authors: Huynh-Thu, Quan, Ghanbari, Mohammed
Format: Article
Language:English
Subjects:
Accuracy
Analysis
Artificial Intelligence
Business and Management
Business metrics
Computer Communication Networks
Correlation analysis
Design engineering
Experiments
Frames
IT in Business
Mathematical models
Multimedia communications
Probability Theory and Stochastic Processes
Quality
Quality standards
Signal to noise ratio
Streaming media
Studies
Telecommunications systems
Temporal logic
Tradeoffs
Unions
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Summary:Peak Signal-to-Noise Ratio (PSNR) is widely used as a video quality metric or performance indicator. Some studies have indicated that it correlates poorly with subjective quality, whilst others have used it on the basis that it provides a good correlation with subjective data. Existing literature seems to provide conflicting evidence of the accuracy of PSNR as a video quality metric. Based on experimental results, we explain a scenario where PSNR provides a reliable indication of the variation of subjective video quality and scenarios where PSNR is not a reliable video quality metric. We show that PSNR follows a monotonic relationship with subjective quality in the case of full frame rate encoding when the video content and codec are fixed. We provide evidence that PSNR becomes an unreliable and inaccurate quality metric when several videos with different content are jointly assessed. Furthermore, PSNR is inaccurate in measuring video quality of a video content encoded at different frame rates because it is not capable of assessing the perceptual trade-off between the spatial and temporal qualities. Finally, where PSNR is not a reliable video quality metric across different video contents and frame rates, we show that a perceptual video model recently approved by the International Telecommunication Union (ITU) provides quality predictions highly correlating with subjective scores even if different video scenes coded at different frame rates are considered in the test set.
ISSN:1018-4864
1572-9451
DOI:10.1007/s11235-010-9351-x