The Mechanics

Ideally, to complete an accurate measurement of video quality, you need access to both the processed and source frame information.

Figure 1 – Example of Source and Processed Video

These measurements are called full reference metrics. In the past, measurements of television quality were done using a calculation called Peak Signal to Noise Ratio (PSNR). This measurement was only for images where the signal got processed entirely in the analogue domain. The calculation uses information in the luminance data of the processed video frame, and then compares that to the original. It’s essentially a ratio between the maximum power of a signal and the power of the degrading noise that will affect the quality of the image representation. For a full definition of PSNR you can go to Wikipedia http://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio and look at the calculation formula. The higher the PSNR value the better the image quality, or so the theory goes.

Once the industry migrated to mixed environments using digital and analogue processing, the measurement tools had to evolve as well. New tools were developed by several companies and institutions, and you can find a lot of the research and technologies among the links provided by the Video Quality Experts Group website http://www.its.bldrdoc.gov/vqeg/links/links.php Once standards bodies like the International Telecommunications Unit (ITU) tested these new tools to determine which would be standardized, full reference methods fell from favor.

The DHCAT was designed to translate performance of a media PC into simple, experiential terms that anyone can understand without extensive interpretation. When we started out, there were already tools in the industry for codec quality, where the primary degradation in the video is image compression artifacts. But there weren’t any that translated this into an expected end-user experience that would include things like the effect of dropped or repeated frames. So, our design team approached this from two perspectives: compression and experience.

Compression Perspective: Since technologies existed in the industry that were standardized, Intel worked with Psytechnics* and implemented their technology to measure recorded video quality. The technology that was implemented for this is described at http://www.psytechnics.com/site/sections/products/pva.php. We test a platform’s capabilities to record video, a Live TV program is recorded over a virtual tuner card created on the system under test and is written to disk using mpeg2, wmv, and DivX formats. More information on video formats can be found here http://www.xilisoft.com/multimedia-glossary/3GP-AVI-MPEG-MOV-RM-WMV-DivX-XviD.html The recorded video is compared to the source using the Psytechnics software and the results are published from the integrated module.

Here is the Psytechnics Video Agent tool inaction, comparing the reference video on the left with the one recorded on the platform being tested on the right.

Imperfections or flaws in video are called artifacts, and these artifacts can range from subtle to very noticeable. Here are some examples.

There are a few classes of artifacts that can impact visual quality that can be measured with objective tools.

Figure 2 Susie – compressed to 2Mbs showing fine grain blocking artifacts.

Figure 3 – Visible artifacts measurable with tools like Psytechnics*