There’s a lot of interest in superresolution imaging in quantitative microscopy, where this is definitely a huge limitation

I am afraid these methods ("learn the typical detail and "re"-apply it") on the said context ("obtain telling detail where we miss it") would be "dreaming" the detail.

There methods are for "beauty", not to "induce real facts": what is "probable" is not what is "real".

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Edit: I have an example for you. Check

https://github.com/Janspiry/Image-Super-Resolution-via-Itera...

and notice the black spot under the iris of the right eye, on the left: does the actual person really have it? It is not in the blurred source image, https://github.com/Janspiry/Image-Super-Resolution-via-Itera... . Now think of an "empiricist" perceptive instrument returning that kind of "noise"...

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I understand you work on the topic (ANN for assessment), so you surely meant something different that what contextually appears.

And the pupils are not round which is a common telltale of some generators.