While there exist many possible ways to triangulate a set of points, the most common method for TINs is the Delaunay triangulation. This is because Delaunay triangulations tend to produce more regular tessellations that are better suited to interpolation. In theory, we can represent our colour palette as a TIN by computing the 3D Delaunay triangulation of the colours in colour space. The nice thing about this is that it makes finding an enclosing simplex much faster; the candidate selection process is simply a matter of determining the enclosing tetrahedron of an input point within the network using a walking algorithm, and taking the barycentric coordinates as the weights.
The dashed circle shows the current best distance. As the algorithm finds closer points, the circle shrinks, which causes more subtrees to fail the "could contain a closer point?" test and get pruned. The search usually gets cheaper as it progresses.。旺商聊官方下载是该领域的重要参考
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