Incorporation of Structural Tensor and Driving Force Into Log-Demons for Large-Deformation Image Registration

Large-deformation image registration is important in theory and application in computer vision, but is a difficult task for non-rigid registration methods. In this paper, we propose a structural Tensor and Driving force-based Log-Demons algorithm for it, named TDLog-Demons for short. The structural...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 28(2019), 12 vom: 28. Dez., Seite 6091-6102
1. Verfasser: Wen, Ying (VerfasserIn)
Weitere Verfasser: Zhang, Le, He, LiangHua, Zhou, MengChu
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2019
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
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520 |a Large-deformation image registration is important in theory and application in computer vision, but is a difficult task for non-rigid registration methods. In this paper, we propose a structural Tensor and Driving force-based Log-Demons algorithm for it, named TDLog-Demons for short. The structural tensor of an image is proposed to obtain a highly accurate deformation field. The driving force is proposed to solve the registration issue of large-deformation that often causes Log-Demons to trap into local minima. It is defined as a point correspondence obtained via multisupport-region-order-based gradient histogram descriptor matching on image's boundary points. It is integrated into an exponentially decreasing form with the velocity field of Log-Demons to move the points accurately and to speed up a registration process. Consequently, the driving force-based Log-Demons can well deal with large-deformation image registration. Extensive experiments demonstrate that the TDLog-Demons not only captures large deformations at a high accuracy but also yields a smooth deformation 
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700 1 |a Zhou, MengChu  |e verfasserin  |4 aut 
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