You seem to have misunderstood what the article is about. It's not about turning a shitty image to a nice a clean one. It's about turning a lowres image into a

You seem to have misunderstood what the article is about. It's not about turning a shitty image to a nice a clean one. It's about turning a lowres image into a hires version, i.e. you start with 100 x 100 pixels (doesn't matter how you obtained them - could be a section of a much bigger image, for example) and try to extrapolate a 1k x 1k pixel version from it. The pixelation you see in the examples is just a representation of what little information you have to work with. It's NOT in any way shape or form related to where you get these pixels in from in the first place. Just to give you a different context here: imagine this upscaling being used to "enhance" a single face in an image like this [1] - there's no way "Gaussian blur" or whatever filter you'd like gets you more information out of that. In the example image I created, I applied a Gaussian blur to the "pixelated" (i.e. enlarged) version of the marked image section. As you can see, enlarging the same section using super-sampling (i.e. similar to what you proposed), doesn't change the information content and one version can basically be transformed into the other. [1] https://imgur.com/a/m23u6Xx https://imgur.com/a/m23u6Xx