Non-rigid image registration based on the globally optimized correspondences
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.