Sorting pixels along a middle “energy seam”, similar to how Photoshop’s “content-aware scaling” works, with additional glitchy goodness. Source images (top to bottom) are: an idyllic mountainscape, a crowd of people, the face of a weird looking man, a missile launch, and sheep on a mountain hill.
An image of four tacos, sorted in pixel blocks.
Image of tacos, sorted in chunks of N pixels (with wrapping).
Sorting X, Y, and both.
I’m currently working on a poster/catalog for an upcoming curatorial project at the Bemis Underground and was thinking of using an image of sorted white noise on a television set. Grayscale white noise is actually pretty boring (so long as it’s actually close to random, the values will fall along a Gaussian curve), so I tried some other experiments.
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Using hexadecimal color yielded some pretty interesting results. The above image is 1,296,000 random values that range from #000000-FFFFFF (0 – 16,777,215). A Processing sketch sorts those values numerically and fills the pixels of the image in order.
Also of interest were Photoshop’s histograms of the color – I’ve not really looked at histograms much in the past, but these were really strange. Luminosity was, as I suspected, a Gaussian curve and RGB values were each close to a flat line. But overall “color” resulted in the above images. The top is the raw image, the one below after “Auto Color” correction: 8-bit fortress meets birthday cake.
Attempting to sort by height… ended up with this instead.