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:
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英伟达的股价困境，不是AI行业的终点，而是市场对AI产业从“宏大叙事”回归“微观盈利”的必然调整：当投资者不再追问“模型参数有多大”，而是开始关注“每个Token能赚多少钱”时，AI行业真正的价值投资才正式开始。