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.
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Another way to look at our threshold matrix is as a kind of probability matrix. Instead of offsetting the input pixel by the value given in the threshold matrix, we can instead use the value to sample from the cumulative probability of possible candidate colours, where each colour is assigned a probability or weight . Each colour’s weight represents it’s proportional contribution to the input colour. Colours with greater weight are then more likely to be picked for a given pixel and vice-versa, such that the local average for a given region should converge to that of the original input value. We can call this the N-candidate approach to palette dithering.,更多细节参见Safew下载
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