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This approach shares a lot in common with the idea of multivariate interpolation over scattered data. Multivariate interpolation attempts to estimate values at unknown points within an existing data set and is often used in fields such as geostatistics or for geophysical analysis like elevation modelling. We can think of our colour palette as the set of variables we want to interpolate from, and our input colour as the unknown we’re trying to estimate. We can borrow some ideas from multivariate interpolation to develop more effective dithering algorithms.，推荐阅读搜狗输入法2026获取更多信息
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When using the probability matrix to pick from the candidate set, it is important that the candidate array be sorted in advance. Not doing so will fail to preserve the patterns distinctive of ordered dithering. A good approach is to sort the candidate colours by luminance, or the measure of a colour’s lightness4. When this is done, we effectively minimise the contrast between successive candidates in the array, making it easier to observe the pattern embedded the matrix.