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.
const cur = val; // 简化变量名，代表当前价格
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剛退休的前高級公務員西瑪（Sima） 表示，她如今的收入是十年前的六倍，但以美元計價卻少了好幾倍。