Are there well known non-frequency-domain compression techniques (lossy or lossless) that exploit information sparsity? Like the first image could be segmented as in the second image, and only the 4 non-empty rectangles stored. That sort of approach.
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I tried to replicate a lossless compression paper from like fifteen years ago that looked for "motifs" in non-frequency-domain. Not a well known technique but there's stuff out there, fwiw. Not sure about well known.
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Heh I implemented the segmentation approach sketched above to store maps lossily for some robot path planning stuff 15y ago. Could get really extreme compressions (like 95%) on some maps, but the tradeoff is the path planning got more inefficient
(the robots move on a graph connecting the centroids of the open rectangles so you get weird artifacts)
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