The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
A survey of hybrid MC/DPCM/DCT video coding distortions
Signal Processing - Special issue on image and video quality metrics
An objective measurement tool for MPEG video quality
Signal Processing - Special issue on image and video quality metrics
User-oriented QoS analysis in MPEG-2 video delivery
Real-Time Imaging - Special issue on real-time digital video over multimedia
Digital Video Image Quality and Perceptual Coding (Signal Processing and Communications)
Digital Video Image Quality and Perceptual Coding (Signal Processing and Communications)
Motion tuned spatio-temporal quality assessment of natural videos
IEEE Transactions on Image Processing
Foveated mean squared error--a novel video quality metric
Multimedia Tools and Applications
Study of subjective and objective quality assessment of video
IEEE Transactions on Image Processing
Foveated video quality assessment
IEEE Transactions on Multimedia
Modeling packet-loss visibility in MPEG-2 video
IEEE Transactions on Multimedia
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image information and visual quality
IEEE Transactions on Image Processing
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images
IEEE Transactions on Image Processing
A multi-metric objective picture-quality measurement model for MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
A scalable wavelet-based video distortion metric and applications
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Wireless Video Quality Assessment: A Study of Subjective Scores and Objective Algorithms
IEEE Transactions on Circuits and Systems for Video Technology
No-Reference Quality Assessment of H.264/AVC Encoded Video
IEEE Transactions on Circuits and Systems for Video Technology
No-Reference Quality Assessment for Networked Video via Primary Analysis of Bit Stream
IEEE Transactions on Circuits and Systems for Video Technology
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The use of video-based applications has increased in recent years owing to the development of video technology as well as the widespread use of the Internet. Thus the evaluation of perceptual video quality has become very important and numerous video quality assessment (VQA) metrics have been developed over the past years. In this paper, we give a classification and a short review of objective VQA metrics, with a focus on the full reference metrics. With the aim of conducting a reliable test of the VQA metrics performances, we made two databases, each of them including 90 distorted video sequences. We carried out a subjective quality evaluation on these databases and the data were made available to the research community. Furthermore, we compared the performance of nine different, freely available, objective VQA metrics by using three different databases in different resolutions: LIVE Video Quality Database (768x432 resolution) and our two newly created databases for progressively scanned videos, i.e. ETFOS CIF Video Quality (ECVQ) database and ETFOS VGA Video Quality (EVVQ) database. Five different distortion types were used and the total number of 330 video sequences was evaluated. A comparison of metrics was done with respect to accuracy, monotonicity, stability, as well as complexity vs. accuracy criteria. The results show that the resolution, the content of the sequence and the distortion type have a significant influence on the performances of VQA metrics. Metrics that generally achieve a high correlation with subjective results for all databases and all distortion types are MOtion-based Video Integrity Evaluation (MOVIE) and Foveated Mean Squared Error (FMSE), but MOVIE has significantly higher complexity than FMSE. An exception is the distortion caused by IP transmission for which none of the analyzed metrics has shown satisfying accuracy and stability.