A MOS model for video QoE: H.264 / MPEG-2

1. v.Cortex ®
H.264 / MPEG-2
Perceptual Quality Analyzer (MOSp)
Path 1 is a division of IPVN
© 2011 IP Video Networks, Inc.

2. MOSp
human visual system (hvs)
no reference vs. full reference model
profiles as a calibration method
OUTLINE
1.

3. The human visual system (hvs) is sophisticated. In fact, the hvs detects digital visual
artifacts in video without prior knowledge of “good”, or original/source video.
Moreover, the hvs can make value judgments on whether quality is artificially
impaired a little, or a lot.
With this theory as the basis for modeling the perceived quality of distribution video,
a properly trained software analysis engine should provide accurate measurement of
video without source formats.
v.Cortex works like the hvs:
It knows MPEG impairments and video.
It knows quality.
It does not rely on the original video.
It is a powerful No Reference Model1.
hvs
1. Model licensed by BT
2.

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vs.
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Perceptual quality video models attempt to achieve a perfect correlation
between Mean Opinion Scores(MOS) and Perceived Mean Opinion
Scores(MOSp).
In a full reference model, the source material image). Within the bit stream, v.Cortex focuses
must be available to the analyzer. A popular, and on the Quantizer Step-size. This parameter is
simple, calculation is PSNR; though, this significant in an MPEG encoder’s capacity to
measurement provides little information reduce picture data.
regarding viewer perception. It serves a industry
accepted quantitative difference that does not Also of concern, the human visual system may
take encoder type into consideration. not see significant impairments if the video
content masks these impaired regions. To ensure
Other full reference models seek to determine proper interpretation of MPEG impairment,
impairment types between source and encoded v.Cortex applies pixel domain methods to assess
material. Models weight these impairment types the levels of masking and combines these
to provide a prediction of viewer quality estimates with its bit stream calculations.
assessment.
continued…
v.Cortex utilizes a no reference model that
full reference vs.
takes advantage of the MPEG (H.264 and
MPEG-2) bit stream and pixel domain (decoded
3. no reference

5. MOSp
MOS
Figure 1 | MOS vs. MOSp
continued from p.3
v.Cortex produces a MOSp that is closely While v.Cortex accurately and quickly assesses the
correlated, at .91, to MOS (fig. 2). The model quality of MPEG video, network operators
objectively provides consistent and accurate require methods, or filters, to quickly provide
results. In fig.1, the data indicates the close pass/fail status to videos that have been
relationship between v.Cortex’s MOSp and actual evaluated. The next section evaluates the use of
MOS values for a variety of quality levels. It is filters with MOSp to save significant time in
important to emphasize that this data reflects video quality assurance.
distribution quality MPEG video via standard
consumer TV, as perceived by consumers. ITU MOS
5 Excellent
The research also indicates that future v.Cortex
analyzers may be calibrated to closely predicate 4 Good
MOS values of H.264 video delivered to mobile 3 Fair
devices, such as iPad, Blackberry and Android
2 Poor
handheld machines. Some test metrics suggest
that the high resolution and small screens of 1 Bad
mobile devices may cause a near linear upshift of Figure 2 | ITU MOS
MOS performance. Simply stated, a 2Mbps
full reference vs.
standard definition video may appear of higher
quality on a smaller, but full resolution, screen.
4. no reference

6. v.Cortex produces accurate MOS results. Operators can calibrate v.Cortex by analyzing a
However, video network operators must few good and bad files from their libraries, then
calibrate their customer perceptions with their apply profiles that meet these expectations.
network capabilities and transport delivery v.Cortex compliments an operator’s perspective
model. Many cable operators seek to deliver and identifies quality problems without an
three MPEG-2 HD videos per 6Mhz 256-QAM operator viewing each video.
channel. However, with an average of 12Mbps
per video, this may be insufficient to reach For example, broadcast graphics, which are
desired quality levels. Operators must have a difficult to encode, may create a trough, which
method to easily find adverse MPEG effects to can be identified by v.Cortex, and either ignored
make a subjective decision about quality. or caught for closer review. In another case, an
operator may tolerate movies at an average
v.Cortex incorporates operator-controlled filters MOSp of 3.2, but will want to ensure that no
for: bad scenes, troughs, and black/white more than 5% of the scenes are below 2.5. With
intensity detection. Each combination of filters a calibrated profile, the operator can ensure that
can be saved as a profile, and applied to different all movies are of an appropriate MOS value and
video types (sports, news, movies, etc.). Bad operator quality standard, without viewing each
scenes are collections of frames that result in video. Finally, v.Cortex can be customized to
undesirable MOSp results over a specified ensure operator intervention is minimized while
duration. Troughs are extreme, but short, low customer quality is achieved.
points in MOSp. Black and white intensity
identifies areas where video may be missing due
to improper production problems. calibration
5. through profiles

7. In short, Path 1’s v.Cortex offers
operators a consistent, accurate, time-
saving tool that ensures quality video for
their customers.
For an evaluation copy of v.Cortex,
please contact us.
sales@path1.com
© 2011 IP Video Networks, Inc.