I'm working on a project where I need to apply different filters to a source video, adjusting its resolution, and then uploading it to YouTube. The goal is to minimize artifacting and pixelation that occurs after YouTube processes the video. Currently, I have a setup that randomly tweaks various parameters, but it's very inefficient and could take years with my current computing resources. I'm looking for advice on how to streamline this process and optimize the filter application more effectively.
3 Answers
Brute forcing this approach is going to be a pain because the possibilities are just too vast. I recommend narrowing it down to a few main factors like bitrate, scaling method, and sharpening techniques. Also, simulate YouTube compression on your machine instead of uploading each time; it really speeds things up! I made progress by testing variations locally before doing final comparisons.
You might save a lot of time by skipping the YouTube upload altogether. Instead, use ffmpeg on your own system to apply the compression. It can give you a close approximation of what YouTube would do without the long upload times.
Rather than randomizing everything, try breaking down the problem. Look at specific elements like sharpening, noise reduction, or bitrate settings separately. YouTube's compression is somewhat predictable, particularly in terms of high-frequency detail loss and chroma subsampling, so focus on those areas to improve your results.
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