Unformatted text preview: R or D is quite expensive, since it involves a mapping each of the 1,000 pixels to a cluster. Therefore, the overhead of the algorithm is insigniFcant and the time is proportional to the number of function evaluations. The functions are not di±erentiable, so modeling as a quadratic function is not so e±ective. This slows the convergence rate, although only 15-25 iterations are used. This was enough to converge when minimizing D , but not enough for R to converge. Actually, a major part of the time in the sample implementation is postpro-cessing: the construction of the resulting image! (c) ²igures 11.2 and 11.3 show the results with k = 3 , 4 , 5 clusters. The solution...
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- Fall '11
- Calculus, Objective Function Values