What is Super Resolution in the Context of Windowing?
The term super-resolution is used very loosely nowadays. But I think the following problem was the original idea, or at least, the one that made the term famous.
Suppose you have a scene and several observations of that scene, i.e. several frames of a video with slight camera motion between them. Super-resolution algorithms combine those several observation into one highly resolved image. This is possible because each observation might contain unique information not present in the others.
If you consider a certain frame as the key frame, this process can be interpreted as a MAP estimation since a priori (or extra) information is present in others frames.
Additionally, we can use natural image statistics as extra information to regularize the solution. Total variation regularization is a broadly used technique.
I suggest the paper Sung Cheol Park - Super Resolution Image Reconstruction: A Technical Overview.