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Non-rigid image registration based on the globally optimized correspondences

机译:基于全局优化的对应关系的非刚性图像配准

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In this paper, we propose a new approach to the non-rigid image registration. This problem can be easily attacked if we can find regularly distributed correspondence points over the whole image or over the objects of interest. Dense and stable image registration can be achieved by using some natural mapping (e.g., Thin Plate Spline) of these correspondences. However, the problems with conventional correspondence matching methods are that the features can rarely be found at the textureless regions and the matching accuracy is degraded at the parts with non-rigid motions. In order to find the regularly spaced correspondences and their accurate matching even under the non-rigid motion, we place mesh nodes over the image and develop a new cost function that considers three complementary terms: similarity, smoothness and some topological constraint that prevents unlikely mappings. Experimental results demonstrate that the proposed method can find correct correspondences in the presence of non-rigid motions, multi-layers (motion discontinuity) and even in the textureless regions. Experimental results also show that the proposed method can be applied to old film restoration as well as image registration.
机译:在本文中,我们提出了一种新的非刚性图像配准方法。如果我们可以在整个图像或感兴趣的对象上找到定期分布的通信点,则可以很容易地攻击此问题。可以通过使用这些对应关系的一些自然映射(例如,薄板样条)来实现密集和稳定的图像配准。然而,传统对应匹配方法的问题是在织地区可以很少能够在具有非刚性运动的部件处降低匹配精度的特征。为了找到常规间隔的对应关系和即使在非刚性运动下的准确匹配,我们将在图像上放置网状节点并开发一种新的成本函数,并考虑三个互补项:相似性,平滑度和一些防止不太可能映射的拓扑限制。实验结果表明,所提出的方法可以在存在非刚性运动,多层(运动不连续)甚至在织地区的情况下找到正确的对应关系。实验结果还表明,该方法可以应用于旧薄膜恢复以及图像配准。

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