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The challenge was clear: achieve a quantum leap in speed while preserving extreme flexibility, minimal storage, regional map support, and dynamic update capabilities. Standard Highway Hierarchies were a starting point, but we needed something more – a uniquely OsmAnd solution.

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.

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