图像到 N 个三角形，颜色损失最小
Image to N triangles with minimum loss of the color
需要使用 Delaunay 三角剖分将图像变成 N 个三角形。每个三角形一种颜色，颜色可以重复。
损失函数由每个像素颜色差异的平方给出。
那么如何优化颜色和三角形的顶点？
递归拆分过程大纲：
Terminate the recursion if N < 2
Split the given area A in two triangles A1 and A2 in such a way that the
sum of standard deviations of the pixel colors is cut in halves.
Assign N/2 colors to A1 and N - N/2 colors to A2.
Recursively split A1 and A2.
N 个三角形的结果网络被着色以最小化损失函数：
For every triangle the color chosen is the average color of the pixels within that triangle.
可能值得对有关该主题的现有文献进行调查。第一个搜索引擎命中返回 Fractal image compression based on Delaunay triangulation and vector quantization
需要使用 Delaunay 三角剖分将图像变成 N 个三角形。每个三角形一种颜色，颜色可以重复。 损失函数由每个像素颜色差异的平方给出。 那么如何优化颜色和三角形的顶点？
递归拆分过程大纲：
Terminate the recursion if N < 2
Split the given area A in two triangles A1 and A2 in such a way that the
sum of standard deviations of the pixel colors is cut in halves.
Assign N/2 colors to A1 and N - N/2 colors to A2.
Recursively split A1 and A2.
N 个三角形的结果网络被着色以最小化损失函数：
For every triangle the color chosen is the average color of the pixels within that triangle.
可能值得对有关该主题的现有文献进行调查。第一个搜索引擎命中返回 Fractal image compression based on Delaunay triangulation and vector quantization