There are probably little-to-no applications of Hilbert SFCs to image compression (in the sense of increasing compression ratio or something). The main benefit

There are probably little-to-no applications of Hilbert SFCs to image compression (in the sense of increasing compression ratio or something). The main benefit of using something like the Hilbert SFC is (2D) locality. That is, "close" points in D where D = [ d0,d1,d2,d3,d4,d5, ... dn] will also be "close" in D2, where D2 = [(x0,y0),(x0,y1)(x0,y2),...(xn,yn)]. NOTE: The converse does not hold. Closeness of points in the D2 plane does NOT guarantee closeness of points in D. Usually this has applications when dealing with things like file systems and databases. I've seen some people that argue that using something like Hilbert curves in compression algorithms will yield less compression-induced artifacts because the artifacts, as you can probably already guess, will "snake around" the image, being much harder to detect visually.