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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.，更多细节参见一键获取谷歌浏览器下载
if (n <= 1) return n;，详情可参考爱思助手下载最新版本
subscription. It is important to use the tool with caution and not to rely too