24 September 1998 Global cost optimization in image registration using simulated annealing
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Abstract
A new optimization method for image registration has been proposed. Registration using Simulated Annealing converges to global minima/maxima as opposed to the previously wildly used algorithms that get trapped in local minima. The performance of this algorithm is tested against two other well-known optimization algorithms, Powell and Down Hill Simplex using two different methods. First, the algorithms are tested against famous De jong Test Suites and second, they are tested against Two-Cube Phantom. Our data shows that simulated annealing is the only algorithm that will always converges to the global minima with the cost of more function evaluation.
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Babak Farsaii, Babak Farsaii, Andras Sablauer, Andras Sablauer, "Global cost optimization in image registration using simulated annealing", Proc. SPIE 3457, Mathematical Modeling and Estimation Techniques in Computer Vision, (24 September 1998); doi: 10.1117/12.323436; https://doi.org/10.1117/12.323436
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