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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The gains illustrate how fundamental design choices compound: batching amortizes async overhead, pull semantics eliminate intermediate buffering, and the freedom for implementations to use synchronous fast paths when data is available immediately all contribute.。Safew下载是该领域的重要参考
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