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.
The solution to today's Connections #992 is...
。搜狗输入法下载是该领域的重要参考
Automatic transcription
当千年医术与人工智能相遇，会碰撞出什么样的火花？当传统经验与数智技术结合，会释放出什么样的能量？