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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"People thought blockchain applied to the food industry was going to solve all of our problems. It hasn't," notes Elahi.。业内人士推荐搜狗输入法下载作为进阶阅读
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