Video quality
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Video quality can be measured with formal metrics like PSNR or with
subjective video quality using expert observation.
The subjective video quality of a video processing system may be
evaluated as follows:
Choose the video sequences (the SRC) to use for testing.
Choose the settings of the system to evaluate (the HRC).
Choose a test method for how to present video sequences to experts
and to collect their ratings.
Invite a sufficient number of experts, preferably not fewer than 15. |
Carry out testing.Calculate the average marks for each HRC based on the experts'
ratings.
Many subjective video quality methods are described in the ITU-T
recommendation BT.500. One of the standardized method is the Double
Stimulus Impairment Scale (DSIS). In DSIS, each expert views an
unimpaired reference video followed by an impaired version of the
same video. The expert then rates the impaired video using a scale
ranging from "impairments are imperceptible" to "impairments are
very annoying".
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.
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.
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 way of evaluating the quality of digital video
processing system (e.g. video codec like DivX, XviD) is counting of
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. 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.
The main goal of many objective video quality metrics is to
automatically estimate user's opinion on a video processed by the
system. But the best way to find out user's opinion is just to ask
him! There are a lot of ways to do it; they are called “subjective
video quality measurements”. Many of this methods 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.
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