To Giles Laurent, re cuttlefish camouflage algorithms

We went to a great lecture in Woods Hole this summer by Giles Laurent about how cuttlefish can match a background texture with the colored dots (chromataphores) of their skin. It was particularly fascinating in its discussion of image texture statistics being matched rather than image shape statistics.

The speaker distinguished between statistics of "things" (shape) and of "stuff" (texture) and this got me thinking about how the Blaschke problem of reconstructing shape from statistics was never evaluated for reconstructing texture from statistics. After all, the cuttlefish seems to be performing such an inversion in displaying an image on its skin that has similar texture statistics to its background. But look at the previous post about arrays of colored dots being building blocks of a form of texture recognition. There is an algorithm there, which is:

• find an array scaled correctly to best match the background - for each of several color channels.
• localize a piece of that array and display it with a matching color channel chromatophore
• do this for all color channels.

So Giles, here is an algorithm: match the scale of different colors, locally. And synchronize the displayed colors with the perceived ones - either one channel at a time or with a mixing matrix that varies locally.