This reminds me of how a lot of older TV shows and movies had an 'enhance' button that could somehow magically take a tiny, blurred image and blow it up to a level of detail where even the most minor things could be seen again. Like a suspect's eyes in the reflection of a window that looked like it was maybe 4 pixels in size in the original image.

The AI examples and reasoning in the article are exactly why this can't work, and is so unrealistic. The info isn't just hidden away in the info in a way some tool can figure out what it is with another effort, it's simply not present entirely. Any tool that tries to enhance a low quality image or video is just going to be making up the missing data.

> Any tool that tries to enhance a low quality image or video is just going to be making up the missing data.

So there is some things that instinctively don't sound correct here.

A frame may not contain the info to enhance, maybe it's too blurry... but a series of frames can (I'm pretty sure) between them have enough info to deblur an object in the background, it really helps to know the focal length, and distance maps...

My only point is information in a video is more than the sum of the information of it's frames, it also captures delta, not just from frame to frame, but relevant frame to relevant frame. That's a fair bit to work off of.

I do agree with our general point when information is 'absent'. I disagree how much absent information is in a video which can't be reconstructed by this delta. It certainly isn't zero, or 100%.

Inventing colors from a grayscale is a good example of absent information and of where this goes awry. Deblurring/blurring operations, less so.