What are the possible ways to find spots with most concentrated contrast on an image? I'm thinking of pixelize + threshold, but I need a more formalized way of finding the darkest spots on the photo, with tweakable parameters.
Something I can think of is the parts with lowest spatial frequency and least luminous pixels together, i.e. the spots with darkest pixels spread over a largest area (on average) should win but small black dots should be considered too, with some sort of adaptive weighing.
desired result; left image transformed to right image:

UPD: The required result is, in fact, a metric. Which should be a ratio of locally cumulated contrast over a known area.
Local points of negligibly small size should not count, no matter how contrast they are; bigger areas with mediocre contrast features should win [because their cumulative luminosity power is higher]. The closest thing I can think of is a 2D probability distribution function; kernelized, smoothed out, spatially-oriented.
Pass a sliding window of eg 100x100 pixels over the image stepped 1 pixel at a time in each dimension. Note the maximum and the minimum pixel value. The local contrast is now the local_max/local_min.
A more robust method might be to use a tapered window (eg Gaussian) and a sliding histogram, using eg the 10-percentile and 90-percentile to avoid salt and pepper noise corrupting results.
If (as stated in your update) you are interested in contrast of features larger than a pixel, downsample your image first.
-k