# A Metric for Visual Quality of Digital Video 

### This metric is based partly on human visual processing and is computationally efficient. 

#### *Ames Research Center, Moffett Field, California*

DVQ (which stands for \"digital video quality\") is a metric for
evaluating the visual quality of digitized video images. Other
video-quality metrics have been proposed, but it appears that each of
them (1) may be based on mathematical models that are not related
closely enough to the characteristics of human perception, in which case
it may not measure visual quality accurately; or (2) may entail such
large amounts of memory or computation that the contexts in which it can
be applied are restricted. In contrast, DVQ was developed in an effort
to incorporate mathematical models of human visual processing while
maintaining computational efficiency so that accurate metrics can be
computed in real time by use of modest computational resources.

DVQ incorporates aspects of early visual processing, including dynamic
adaptation to changing brightness, luminance and chromatic channels,
spatial and temporal filtering, spatial-frequency channels, dynamic
contrast masking, and summation of probabilities. Among the most complex
and time-consuming elements of other proposed metrics are
spatial-filtering operations that implement multiple-band-pass spatial
filters characteristic of human vision. In DVQ, spatial filtering is
accelerated by use of the discrete cosine transform (DCT); this
provision affords a powerful advantage because efficient computational
hardware and software for the DCT are available and because in many
potential applications, DCTs may have already been generated in
image-data-compression processing.

DVQ is defined by, and computed in, the process illustrated in the
figure. The input to the process is a pair of color video image
sequences, of which one is denoted the reference sequence and the other
is denoted the test sequence. The first step of the process consists of
various sampling, cropping, and color transformations that serve to
restrict processing to a region of interest and to represent colors in
the sequences in a perceptual color space \[e.g., in terms of *L* (a
standard measure of brightness) and chromaticity coordinates (standard
measures of hue and saturation) specified by the Commission
Internationale de l\'Eclairage (CIE)\].

The sequences are then subjected to blocking and DCT, the results of
which are transformed to local contrast (the ratio between the DCT
amplitude and the mean amplitude in the affected block). The next step
is a temporal-filtering operation, in which the temporal part of a
contrast-sensitivity function (CSF) is implemented in a recursive
discrete second-order filter. The outputs from the temporal-filtering
operation are converted to just-noticeable differences by dividing each
DCT coefficient by its respective visual threshold; this implements the
spatial part of the CSF.

In the next step, the two sequences are subtracted. The resulting
difference sequence is subjected to a contrast-masking operation, which
also depends upon the reference sequence.

Finally, the masked differences can be pooled in various ways to
illustrate the perceptual error over various dimensions. As used here,
\"pooling\" signifies summing over one or more of six dimensions that
represent, specifically, image frames, color channels, rows of blocks,
columns of blocks, horizontal spatial frequencies, and vertical spatial
frequencies. The pooled error can be converted to a measure of visual
quality.

 

![](media/image1.jpeg){width="5.750694444444444in"
height="1.0944444444444446in"}\
**Test and Reference Sequences** of digitized video images are processed
to generate a measure of the visual quality of the test sequence
relative to the reference sequence.

 

*This work was done by Andrew B. Watson, James Hu, and John F. McGowan
III of* **Ames Research Center***. For further information, access the
Technical Support Package (TSP)* **free on-line at**
**[www.nasatech.com](http://www.nasatech.com/)** *under the
**[Information Sciences
category](http://www.nasatech.com/TSP/mis.html).***

*This invention is owned by NASA, and a patent application has been
filed. Inquiries concerning nonexclusive or exclusive license for its
commercial development should be addressed to the Patent Counsel, Ames
Research Center, (650) 604-5104. Refer to ARC-14236.*

*Tech Briefs article published April 2001.*