3.17. Comparison of Various Algorithms
From Glassner (1990)
Here is a comparison of the computational complexity of
some of the algorithms we have looked at:
Memory Search for Representatives Mapping Picture Quality
Uniform Quant. 0 O(K) O(N) bad
Popularity O(D) O(N + D.log(K)) >O(N) depends
algorithm on data
Median Cut O(D) O(N + D.log(K)) O(N.log(K)) good
Octree Quant. O(K) O(N) O(N) good
N is the number of pixels of the original image. If the image is
run-length encoded, N can also be the number of runs of the
K is the number of representatives, that is, the size of the
colour look-up table.
D is the number of different colours in the original image.