Gabor Feature-Based LogDemons With Inertial Constraint for Nonrigid Image Registration
Gabor Feature-Based LogDemons With Inertial Constraint for Nonrigid Image Registration
复制标题
用于非刚性图像配准的具有惯性约束的基于 Gabor 特征的 LogDemon
DOI：
10.1109/tip.2020.3013169
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发表时间：
2020
影响因子：
10.6
通讯作者：
Lianghua He
中科院分区：
文献类型：
--
作者：
Ying Wen;Cheng Xu;Yue Lu;Qingli Li;Haibin Cai;Lianghua He
非刚性图像配准在计算机视觉和医学应用领域起着重要作用。基于 demons算法的图像配准方法通常使用强度差异作为相似性准则。然而，基于强度的方法不能很好地保留图像纹理细节，并且受局部极小值的限制。为了解决这些问题，我们在本文中提出了一种基于加博尔（Gabor）特征的LogDemons配准方法，称为GFDemons。由于加博尔滤波器适合提取图像纹理信息，我们提取配准图像的加博尔特征来构建特征相似性度量。此外，由于某些图像区域的梯度较弱，更新场太小以至于无法将运动图像正确地变换为固定图像。为了弥补这一缺陷，我们提出了一种基于GFDemons的惯性约束策略，称为IGFDemons，利用先前的更新场为当前更新场提供引导信息。惯性约束策略可以在准确性和收敛性方面进一步提高所提方法的性能。我们在三种不同类型的图像上进行了实验，结果表明所提方法比一些流行的方法取得了更好的性能。
Nonrigid image registration plays an important role in the field of computer vision and medical application. The methods based on Demons algorithm for image registration usually use intensity difference as similarity criteria. However, intensity based methods can not preserve image texture details well and are limited by local minima. In order to solve these problems, we propose a Gabor feature based LogDemons registration method in this article, called GFDemons. We extract Gabor features of the registered images to construct feature similarity metric since Gabor filters are suitable to extract image texture information. Furthermore, because of the weak gradients in some image regions, the update fields are too small to transform the moving image to the fixed image correctly. In order to compensate this deficiency, we propose an inertial constraint strategy based on GFDemons, named IGFDemons, using the previous update fields to provide guided information for the current update field. The inertial constraint strategy can further improve the performance of the proposed method in terms of accuracy and convergence. We conduct experiments on three different types of images and the results demonstrate that the proposed methods achieve better performance than some popular methods.