That's not the same as fabricating information, though. A blurry image still contains a whole bunch of information and correlation data that just isn't present in a handful of pixels.

This is not super-resolution, but something different entirely. Super-resolution would mean to produce a readable license plate from just a handful of pixels. That is an impossible task, since the pixels alone would necessarily match more than one plate.

The algorithm would therefore have to "guess" and the result will match something that is has been trained on (read: plausible), but by no means the correct one, no matter how many checks you run on a database.

To illustrate the point, I took an image of a random license plate, and scaled it down to 12x6 pixels. 4x super-resolution would bring it to 48x24 pixels and should produce perfectly readable results.

Here's how it looks (original, down-scaled to 48x24, and down-scaled to 12x6 pixels): https://pasteboard.co/JSu3WDU.png

The 48x24 pixel version could easily be upscaled to even make the state perfectly readable. A 4x super-resolution upscale of the 12x6 version, however, would be doomed to fail no matter what.

That's what I'm getting at.

Just for shits and giggles, here's the AI 4x super-resolution result: https://pasteboard.co/JSu7jkP.png

Edit: while I'm having fun with super-resolution, here's the upscaled result from the 48x24 pixel version: https://pasteboard.co/JSu9Qh6.png