Guessing I think is too strong of a way to phrase what super resolution does. The broader concept of, for example, regularized solving of inverse problems is used widely in things like CT and MRI where the reconstructed imagery is used for analysis. The regularization is effectively the part you’re saying is guessing, but I would phrase it as enforcing assumptions about the data. Neural network-based approaches are similarly learning the distribution of the output data.