The effect does not only need to be deterministic, but also invertible.
A low-res image has multiple "inverses" (yikes), supposedly each with an associated probability (if you would model it that way). So it would be more honest if the algorithm shows them all.
> I love this cliché. I've seen it thousands of times, and probably written it myself a few times. We all repeat stuff like that ad nauseam, without ever thinking.
It is not a cliche it is an absolute truth. Information not present cannot be retrieved. There may be more information present than is immediately obvious.
> Neural Nets are excellent in squeezing all the information out noisy data
Maybe but they are also good at overfitting onto noisy data (the original article is an example of such overfitting).
Yes, a low-res image has lots of information. You can process that information in many ways. Missing data can't just be magically blinked into existence though.
Copy/pasting bits of guessed data is NOT getting back information that has been destroyed or never captured. Obscured data is very different from non-existent data. Could the software recreate a destroyed painting of mine based on a simple sketch? Of course not, because it would have to invent details it knows nothing about.
I think it's almost dangerous to call this line of thinking cliché. It should be celebrated, not ridiculed.
I love this cliché. I've seen it thousands of times, and probably written it myself a few times. We all repeat stuff like that ad nauseam, without ever thinking.
Because it's fundamentally flawed, especially in the context that it has usually been applied to, namely criticising the CSI:XYZ trope of "enhancing images".
The truth is that there is a lot more information in a low-res image than meets the eye.
Even if you can't read the letters on a license plate, it can be recovered by an algorithm. If the Empire State Building is in the background, it's likely to be a US license plate. Maybe only some letters would result in the photo's low-res pattern. If you only see part of a letter, knowing the font may allow you to rule out many letters or numbers etc...
It's similar to that guy who used Photoshop's swirl effect to hide his face, not knowing that the effect is deterministic, and can easily be undone.
The error mostly appears to be in assuming that the information has been destroyed, when in reality it's often just obscured. And Neural Nets are excellent in squeezing all the information out noisy data.