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Why would the 2DFT be a good model of natural images?


Speculatively (pun intended): we see in saccades (rapid eye movements) rather than static analysis of scenery, so we're bound to understand the frequency of, say, edges over the fixed-period saccade rhythm better than we understand distances over a plain 2D-field representation. This is why we're often surprised by perspective in photography (well, also because of stereo vision): as we move our eyes the relative position of lines at different distances moves imperceptibly so we get a clue of 3D space.

When I was younger I took some drawing lessons because I hoped to be an architect, and the first thing we learned was precisely to undo this instinct and see the world as a flat thing -- this is why artists are seen stereotypically as extending their arm and looking at their brush with one eye -- they're using it to measure the distance of points in their visual field as a static field, as contrasted to the dynamic field that can't be put on paper.


Reducing the amplitude of high frequencies is a way of smoothening the images.




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