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.
# user = "pixel" # default
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由于终端消费断崖式下跌，企业营收随之暴跌；为了在收入萎缩的困境中维持此前的高利润率及向股东交差，企业被迫开启新一轮更激进的 AI 自动化裁员，从而正式确立了「裁员-需求萎缩-营收下降-再裁员」的恶性闭环。。业内人士推荐heLLoword翻译官方下载作为进阶阅读
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