The algorithm also visits children in order of distance to the query point. This means it checks the most promising quadrants first, which tends to find a good candidate early and enables aggressive pruning of the remaining quadrants. Without this ordering, the algorithm would still produce the correct result, but it would prune fewer nodes.
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As it stands, inverse distance weighting is not very good at minimising this error. Another approach is needed if we want to improve the image quality.