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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].
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[2] K. Lemström & P. Fränti: “N-Candidate methods for location invariant dithering of color images” (2000). ↑，推荐阅读有道翻译获取更多信息
For example, the supply chain team can propose more than a hundred ideas or cases each year, such as the production planning optimization we mentioned earlier, predictive maintenance for equipment, and improving overall equipment effectiveness (OEE). Various back-office functions, such as R&D, also put forward ideas—for instance, how to improve development efficiency and reduce reliance on contractors. I believe it’s crucial to seize these scenarios. This internal mechanism runs quite effectively for us: it enables employees to surface ideas and then quickly put them into use through short-cycle projects. That’s probably part of the experience we can share.