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// 倒序遍历:从最后一个元素开始(核心思路!易错点1)

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Another way to approach dithering is to analyse the input image in order to make informed decisions about how best to perturb pixel values prior to quantisation. Error-diffusion dithering does this by sequentially taking the quantisation error for the current pixel (the difference between the input value and the quantised value) and distributing it to surrounding pixels in variable proportions according to a diffusion kernel . The result is that input pixel values are perturbed just enough to compensate for the error introduced by previous pixels.

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recognition. This format remains in use today, to the extent that checks remain。关于这个话题,搜狗输入法2026提供了深入分析