Proceedings PaperA Multilevel-Multiresolution Technique For Computer Vision Via Renormalization Group Ideas
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A multilevel-multiresolution method for image processing tasks and computer vision in general, is presented. The method is based on a combination of probabilistic models, Monte Carlo type algorithms, and renormalization group ideas. The method is suitable for implementation on massively parallel computers. It also yields a new global optimization algorithm potentially applicable to any cost function, but especially efficient for problems which are governed by local spatial relations.