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.
"There's the urine, the droppings," he says. "One time there was a carpet leading up to the altar that became absolutely sodden with urine and droppings and had to be thrown away. They also destroyed the brass work."
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"The platform is also unevenly moderated, and quality varies massively by community," say Oc.
I've spent a lot of time on my desk setup, and there's nothing else I can think of that I would change.
Source: Computational Materials Science, Volume 267