Objective quality metrics benchmarks provide exceptionally useful data for any producer wanting to substitute fact for untested opinions.
By Jan Ozer
Every compressed file involves dozens of configuration-related decisions, including resolution, data rate, H.264 profile, VBR or CBR, entropy coding technique, x.264 preset, b-frames, reference frames—the list goes on and on. Most encoding professionals simply use configurations gleaned from presets supplied with their encoding tools, or perhaps from recipes found on the web. But how can you be sure that you’re squeezing the last bit of quality out of the selected data rate, or that your videos are optimally bandwidth-efficient? How can you tell how much additional quality a 1080p@ 7.5Mbps stream delivers over the 5.5Mbps stream?
Basically, you have three options: ignore the issue and hope for the best, implement time-consuming and expensive subjective testing, or use objective quality metrics, which are less expensive and consume less time, but still require investments of both money and effort. Over the past 18 months, I’ve adopted the last alternative. In this article, I’ll introduce you to two objective quality measurement tools, and describe how I use them to make better-informed compression-related decisions. But let’s start with a brief description of what objective quality benchmarks actually are.
What Are Quality Metrics?
Without question, the gold standard for assessing video quality is a controlled subjective test, which, as previously mentioned, can be time-consuming and expensive to run. Objective quality benchmarks are algorithms that compare the compressed video with the source and render a value that predicts how the compressed file would fare in subjective tests. There are multiple algorithms, all rated according to how well they correspond with actual subjective evaluations. None are perfect, but some perform better than others.
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