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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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Point lookups are useful, but the operation you'll reach for more often is a range query: give the tree a rectangular region and retrieve every point inside it, without scanning the entire dataset.