Another way to look at our threshold matrix is as a kind of probability matrix. Instead of offsetting the input pixel by the value given in the threshold matrix, we can instead use the value to sample from the cumulative probability of possible candidate colours, where each colour is assigned a probability or weight . Each colour’s weight represents it’s proportional contribution to the input colour. Colours with greater weight are then more likely to be picked for a given pixel and vice-versa, such that the local average for a given region should converge to that of the original input value. We can call this the N-candidate approach to palette dithering.
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Games and physics simulations need to detect which objects are touching or overlapping. With nnn objects, checking every pair is O(n2)O(n^2)O(n2) comparisons, which gets expensive fast. A hundred objects means roughly 5,000 pair checks. A thousand means nearly 500,000.，推荐阅读下载安装 谷歌浏览器 开启极速安全的 上网之旅。获取更多信息
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