The original contains artifacts that tend to arise after compression, as the other poster notes (posterization and such). I wonder if you'll get better results if you make the original go through a gaussian to smooth those artifacts, and then feed it to the enhancer.
There’s no reason that you wouldn’t be able to go directly from compression artefacts to a decent output with a correctly trained network. It’s slightly erroneous to call them artefacts as they do hold information, just in a not readily reversible way with conventional upscaling techniques.
Yes. Well, kinda. You can maintain the resolution, but you'll be losing information regardless.
But that's what's needed here. The current image contains a lot of compression artifacts, which are extraneous information, and that's what the upscaler seems to want to enhance. Wipe that information out and you're left with the rough structure, which is what we actually want enhanced.
AI is gonna introduce new information to input new resolution from nowhere either which way, so we're just priming and massaging and optimizing our input so as to remove any obstructions that might trip up the AI enhancer. But yes you're right, ideally the enhancer should know how to take into account compression artifacts but this one doesn't.
