Thx!
So if I guess correctly, you classify and examine a stack of images to build a tables of how "the world" works. To do the interpolation you assume the target image is a member of "the world" with every 2nd line missing. You then search your table for "a good/best match" and insert the missing lines based on that instance of experience. This should be extensible for general times N upsizing by assuming N-1 of N lines are missing and need insertion.
Also I suspect with a little lateral thinking, the tables of how "the world" works, could be adapted to analyze interlaced images to classify the area that are static (good experience match) from those that have motion (bad experience match).....