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I built the proof-of-concept alternative around a different set of principles.
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Instead of taking the nearest candidates to , we can look for a set of candidates whose centroid is close to . The N-convex algorithm works by finding the closest colour to a given target colour for iterations, where the target is first initialised to be equal to the input pixel. Every iteration the closest colour added to the candidate list, and the quantisation error between it and the original input pixel is added to the target.