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.
The only difference is the test constant: 0x10 for a data segment load, 0x15 for a far call target.
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According to Chris Fayers, head of environment at Hinkley Point C, the system has been working "really well".
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