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Video quality is a characteristic of video passed through a video processing system. Since the time when the first video sequence was recorded, lots of video processing systems have been designed. Different systems may have different influence on a video sequence, so video quality evaluation is a very important task.
From analog to digital video In the ages of analog video systems it was possible to evaluate the quality of video processing system by calculating the frequency response of some traditional test signal (for example, a collection of color bars and circles). Nowadays digital video systems are replacing analog ones, and evaluation methods must be changed. Performance of digital video processing system can vary powerfully and depends on dynamic characteristics of input video signal (e.g. motion, level of spatial details). That's why digital video quality must be evaluated on video sequences that can be actually received by users. Objective video quality The objective evaluation techniques are mathematical models that successfully emulate the subjective quality assessment results, based on criteria and metrics that can be measured objectively. The objective methods are classified, according to the availability of the original video signal, which is considered to be in high quality. Therefore, they can be classified as Full Reference Methods, Reduced Reference Methods and No-Reference Methods. The most traditional ways of evaluating the quality of digital video processing system (e.g. video codec like DivX, XviD) are counting of the Signal-to-noise ratio(SNR) and peak signal-to-noise ratio (PSNR) between source signal and video passed through this system. PSNR is one of objective video quality metrics - metrics that can be automatically computed by a computer program.But good PSNR does not always guarantee a good visual quality due to non-linear behaviour of human visual system. Recently a number of more complicated and precise metrics were developed, for example VQM and SSIM. All the aforementioned post-encoding objective methods may require repeating post-encoding tests in order to determine the encoding parameters that satisfy a specific level of user satisfaction, making them time consuming, complex and impractical for implementation on real commercial applications. For this reason, a lot of research has been focused on developing novel objective evaluation methods, which enable the prediction of the perceived quality level of an encoded video at a pre-encoding stage. Subjective video quality Main article: Subjective video quality The main goal of many objective video quality metrics is to automatically estimate general user's opinion on a video processed by the system. But the best way to find out a user's opinion is just to ask them! Sometimes however, 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 averaged to evaluate the quality of each video sequence, but details of testing may vary greatly. See also | ||||||||
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