Most of the algorithms described here are quite straightforward to implement. Some of them can be written in just a few lines of code, and those that require a bit more effort can be better understood by reading through the relevant papers and links I have provided. The exception to this are those that rely on the Delaunay triangulation to work. Robust Delaunay triangulations in 3D are fairly complex and there isn’t any publicly available software that I’m aware of that leverages them for dithering in the way I’ve described.
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Regions with many nearby points keep subdividing. Regions with few or no points stay large. The tree adapts to the data: dense areas get fine-grained cells, sparse areas stay coarse. The split grid is predetermined (always at midpoints), but the tree only refines cells that need it. Sparse regions stay as single large nodes while dense regions subdivide deeply.
Жители Санкт-Петербурга устроили «крысогон»17:52