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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.
，详情可参考WPS官方版本下载
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export "$var=$value"。业内人士推荐heLLoword翻译官方下载作为进阶阅读
AI-GENERATED IMAGE.，更多细节参见Line官方版本下载
Александра Статных (Редактор отдела «Путешествия»)