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The center region of the photo in Figure 1, before and after being scrambled.

The center region of the photo in Figure 1, before and after being scrambled.

Source publication
Figure 1: A photo of a wall, and that photo after being scrambled.
Figure 2: The center region of the photo in Figure 1, before and after...
Figure 3: The original photo, together with the average color of each...
Figure 4: The original photo, together with an image showing the...
+3 Figure 4: The original photo, the average color of each region, and the...
Vectorized Image Partitioning
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  • Jun 2019
In this article, I'm going to present a low-degree polynomial runtime image partition algorithm that can quickly and reliably partition an image into objectively distinct regions, using only the original image as input, without any training dataset or other exogenous information. All of the code necessary to run the algorithm is available on my res...
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Contexts in source publication

Context 1
... implies that as we scramble an image, we should expect to increase the local complexity of the image. For example, we can say that the wall in Figure 2 is "red", even though it contains 41, 542 unique colors. After scrambling the image, that same region can no longer be reasonably described using a single color, and the actual number of colors within the region increases to 47, 471 unique colors. ...
Context 2
... implies that as we scramble an image, we should expect to increase the local complexity of the image. For example, we can say that the wall in Figure 2 is "red", even though it contains 41, 542 unique colors. After scrambling the image, that same region can no longer be reasonably described using a single color, and the actual number of colors within the region increases to 47, 471 unique colors. ...
Context 3
... implies that as we scramble an image, we should expect to increase the local complexity of the image. For example, we can say that the wall in Figure 2 is "red", even though it contains 41, 542 unique colors. After scrambling the image, that same region can no longer be reasonably described using a single color, and the actual number of colors within the region increases to 47, 471 unique colors. ...