At this point, some might argue that PSNR is not a good indicator for the perceived quality of a video. For that purpose, we will use the peak-signal-to-noise-ratio (PSNR). Now that we have finished our 84 test encodes, we want analyze the output and determine its quality compared to our input video. The ffmpeg command for these types of encodes is pretty straight forward: ffmpeg -i input.mp4 -y -vcodec libx264 -filter:v scale=w=1280:h=720 -crf 30 output.mp4įor each of the 84 different settings, we tell ffmpeg to encode in H.264 at our target CRF value and scale the output to our target resolution. Seven target resolutions with 12 different CRF values lead to a total of 84 test encodes. In my tests, I used 1080p videos as an input. These test encodes will help us in determining the optimal bitrate/resolution pairs later. To start off, we need to perform multiple test encodes. So how can we actually determine the complexity of an asset and come up with individual encoding settings? For that purpose, Netflix more or less uses a brute force approach. Consequently, some of the movie trailers are easier to encode and less complex than others. While some of the assets achieve a “good” PSNR value of 40-45 at bitrates of 1Mbit – 2Mbit, other input files require around 3Mbit – 6Mbit. The chart shows the resulting PSNR and bitrate values at a resolution of 1080p. In this case, different movie trailers have been encoded with the same Constant Rate Factor (CRF) values. To illustrate these findings, consider the figure below:

In addition, movies or sport streams, which contain a lot of movement, are streamed with lower resolutions to avoid a bad quality of experience for the viewer. Easy-to-encode videos can be delivered with much lower bitrates while improving the perceptual quality. Compared to classic approaches, in which the same, predefined encoding ladder is applied for all types of content, per-title encoding has the potential to significantly decrease the storage and delivery costs of video streams.

Per-title encoding is based on the fact that different types of video content require different bitrates and encoding settings to achieve a certain quality. In this blog post, I would like to describe my understanding of per-title encoding and how to reproduce the results of Netflix using ffmpeg. In a very interesting blog post and a detailed paper, Netflix described their findings and how the results can be interpreted. In 2016, Netflix introduced the concept of per-title-encoding.

Ffmpeg crf setting