NATO approves the iPhone and iPad for classified use

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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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Equal (1): Everything in this purple space must be equal to 1. The answer is 1-4, placed horizontally; 3-1, placed horizontally.

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As it stands, inverse distance weighting is not very good at minimising this error. Another approach is needed if we want to improve the image quality.