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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.。旺商聊官方下载对此有专业解读
Intuitively, it’s not too difficult to understand why this is the case. Remember that error-diffusion works in response to the relationship between the input value and the quantised value. In other words, the colour palette is already factored in during the dithering process. On the other hand, ordered dithering is completely agnostic to the colour palette being used. Images are perturbed the same way every time, regardless of the given palette.
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