八叉树算法，提取图片主色调，颜色量化，聚类
function [img,ImgMap]=Octre(Image,ColorOfNumber)
switch ColorOfNumber
case 2
Result=255;
case 4
Result=255;
case 8
Result=255;
case 16
Result=80;
case 32
Result=50;
case 64
Result=20;
case 128
Result=10.3;
case 256
Result=5.5;
case 512
Result=2.32;
otherwise
Result=ColorOfNumber;
end
Img = imread(Image);
% Extract pixels as RGB point triplets
pts = reshape(Img,[],3);
% Create OcTree decomposition object using a target bin capacity
OT = OcTree(pts,'BinCapacity',ceil((size(pts,1) / 256) *Result));
% Find which bins are "leaf nodes" on the octree object
leafs = find(~ismember(1:OT.BinCount, OT.BinParents) & ...
ismember(1:OT.BinCount,OT.PointBins));
% Find the central RGB location of each leaf bin
binCents = mean(reshape(OT.BinBoundaries(leafs,:),[],3,2),3);
% Make a new "indexed" image with a color map
ImgIdx = zeros(size(Img,1), size(Img,2));
for i = 1:length(leafs)
pxNos = find(OT.PointBins==leafs(i));
ImgIdx(pxNos) = i;
end
ImgMap = binCents / 255; % Convert 8-bit color to MATLAB rgb values
% Display the original color image and result color image
figure
imshow(Img);
title(sprintf('Original %d color image', size(unique(pts,'rows'),1)))
figure
imshow(ImgIdx, ImgMap);
title(sprintf('Octree-quantized %d color image', size(ImgMap,1)))
img=ImgIdx;
% imshow(img,ImgMap);
end