Contains possible values of color quantization algorithms.
Namespace:
Aurigma.GraphicsMill.Transforms
Assembly:
Aurigma.GraphicsMill (in Aurigma.GraphicsMill.dll)
Public Enumeration ColorQuantizationAlgorithm
public enum ColorQuantizationAlgorithm
Member name  Description  

MedianCut 
Median cut algorithm. The algorithm fits a box around all colors used in the RGB colorspace which it splits at the median value of its longest side. The algorithm stops after 255 recursions. All colors in one box are mapped to the centroid of this box. 

Octree 
Octree algorithm. The algorithm encodes image colour data as an octree up to nine levels deep. The node index to branch out from at the top level is determined by a formula that uses the most significant bits of the red, green, and blue colour components. The next lower level uses the next bit significance, and so on. Less significant bits are sometimes ignored to reduce the tree size. The algorithm is highly memory efficient because the tree's size can be limited. The bottom level of the octree consists of leaf nodes that accrue colour data not represented in the tree; these nodes initially contain single bits. If much more than the desired number of palette colours are entered into the octree, its size can be continually reduced by seeking out a bottomlevel node and averaging its bit data up into a leaf node, pruning part of the tree. Once sampling is complete, exploring all routes in the tree down to the leaf nodes, taking note of the bits along the way, will yield approximately the required number of colours. 
Color quantization is a process that reduces the number of distinct colors used in an image with the intention that the new image should be as visually similar as possible to the original image. It is used when you convert, say, 24bit image to 8bit (or lower).