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The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:

* 核心思路:单调递减栈(找「上一个比当前价格大的元素索引」),时间复杂度O(n),空间复杂度O(n),更多细节参见91视频

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