Earlier quoted context omitted.
Well, there is this paper called "Real-time content-aware image resizing" , maybe that describes the method you are curious about? > In this paper, we present a more efficient algorithm for seam based content-aware image resizing, which searches seams through establishing the matching relation between adjacent rows or columns. We give a linear algorithm to find the optimal matches within a weighted bipartite graph co…
That's the one I implemented -- with a bit of low-level hackery, it could run fast enough to resize at ~5-8 fps on mobile back in 2013. But the result didn't look great on most images if you resized by more than ~15%. The technique works by calculating the "importance" field of the image once, and all the seams upfront. Then you can just number the seams from 1-n and remove the first m seams when you resize the image…
I wonder if you could do a kind of quad-tree version where you hone in on the precise seam and minimise recalculations to bubbling new energy up the tree. That might also give a way to weigh global-to-local structure.