Nowadays digital video systems are replacing analog ones, and evaluation methods have changed. Performance of a digital video processing system can vary significantly and depends on dynamic characteristics of input video signal (e.g. amount of motion or spatial details). That's why digital video quality should be evaluated on diverse video sequences, often from user's database.
The most traditional ways of evaluating quality of digital video processing system (e.g. video codec like DivX, XviD) are calculation of the signal-to-noise ratio (SNR) and peak signal-to-noise ratio (PSNR) between the original video signal and signal passed through this system. PSNR is the most widely used objective video quality metric. However, PSNR values do not perfectly correlate with a perceived visual quality due to non-linear behavior of human visual system. Recently a number of more complicated and precise metrics were developed, for example UQI, VQM, PEVQ, SSIM and CZD. Based on a benchmark by the Video Quality Experts Group (VQEG) in the course of the Multimedia Test Phase 2007-2008 some metrics were standardized as ITU-T Rec. J.246 (RR) and J.247 (FR) in 2008.
The performances of an objective video quality metric are evaluated by computing the correlation between the objective scores and the subjective tests results. The latters are called mean opinion score (MOS). The most frequently used correlation coefficients are : linear correlation coefficient, Spearman's rank correlation coefficient, kurtosis, kappa coefficient and outliers ratio.
When estimating quality of a video codec, all the mentioned objective methods may require repeating post-encoding tests in order to determine the encoding parameters that satisfy a required level of visual quality, making them time consuming, complex and impractical for implementation in real commercial applications. For this reason, a lot of research has been focused on developing novel objective evaluation methods which enable prediction of the perceived quality level of the encoded video before the actual encoding is performed
The main goal of many objective video quality metrics is to automatically estimate average user (viewer) opinion on a quality of video processed by the system. Sometimes however, measurement of subjective video quality can also be challenging because it may require a trained expert to judge it. Many “subjective video quality measurements” are described in ITU-T recommendation BT.500. Their main idea is the same as in Mean Opinion Score for audio: video sequences are shown to the group of viewers and then their opinion is recorded and averaged to evaluate the quality of each video sequence. However details of testing may vary greatly.
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