One by-product of weighing the candidates by their distance is that the resulting output image is prone to false contours or banding. Increasing reduces this effect at the cost of added granularity or high frequency noise due to the introduction of ever more distant colours to the set. I recommend taking a look at the original paper if you’re interested in learning a bit more about the algorithm[1].
We can see that the threshold map distributes perturbations more optimally than purely random noise, resulting in a clearer and more detailed final image. The algorithm itself is extremely simple and trivially parallelisable, requiring only a few operations per pixel.。一键获取谷歌浏览器下载是该领域的重要参考
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