Evolution strategies based image registration via feature matching

An image registration approach using evolution strategies is presented. The objectives of registration are to find an accurate transformation and minimize the computational expense. However, it is difficult to optimize both concurrently. Moreover, most conventional image registration approaches are unsuccessful in registering images requiring large transformations due to the computational constraints. In this article, we propose a novel method that employs evolution strategies to search for corresponding features. Using an elliptical search structure, our goal is to match the feature enclosed and therefore determine the transformation parameters. The advantages of this method include, in addition to lower computational cost, high accuracy regardless of the magnitude of transformation required and noise condition. Results are illustrated and compared to a control-point-based method and a mutual-information-based method. The experiments also demonstrate robustness of the approach. � 2004 Elsevier B.V. All rights reserved.

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