1 & x_0 & x_0^2 & \dots & x_0^n\\
One by-product of weighing the candidates by their distance is that the resulting output image is prone to false contours or banding. Increasing reduces this effect at the cost of added granularity or high frequency noise due to the introduction of ever more distant colours to the set. I recommend taking a look at the original paper if you’re interested in learning a bit more about the algorithm[1].
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Note the implication of uniqueness here: given our set of n+1
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Researchers and academics developing experimental applications
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