Editing Octree (section)

==Example color quantization==
Taking the full list of colors of a 24-bit RGB image as point input to the Octree point decomposition implementation outlined above, the following example show the results of octree color quantization. The first image is the original (532818 distinct colors), while the second is the quantized image (184 distinct colors) using octree decomposition, with each pixel assigned the color at the center of the octree bin in which it falls. Alternatively, final colors could be chosen at the centroid of all colors in each octree bin, however this added computation has very little effect on the visual result.<ref>Bloomberg, Dan S. [http://leptonica.org/papers/colorquant.pdf "Color quantization using octrees."], 4 September 2008. Retrieved on 12 December 2014.</ref>
<syntaxhighlight lang="matlab">
% Read the original RGB image
Img = imread('IMG_9980.CR2');
% 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) * 7));
% 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 532818-color image and resulting 184-color image 
figure
subplot(1, 2, 1), imshow(Img)
title(sprintf('Original %d color image', size(unique(pts,'rows'), 1)))
subplot(1, 2, 2), imshow(ImgIdx, ImgMap)
title(sprintf('Octree-quantized %d color image', size(ImgMap, 1)))
</syntaxhighlight>