Using the Local Phase of the Magnitude of the Local Structure Tensor for Image Registration

The presentation of our SCIA paper "Using the Local Phase of the Magnitude of the Local Structure Tensor for Image Registration" Abstract The need of image registration is increasing, especially in the medical image domain. The simplest kind of image registration is to match two images that have similar intensity. More advanced cases include the problem of registering images of different intensity, for which phase based algorithms have proven to be superior. In some cases the phase based registration will fail as well, for instance when the images to be registered do not only differ in intensity but also in local phase. This is the case if a dark circle in the reference image is a bright circle in the source image. While rigid registration algorithms can use other parts of the image to calculate the global transformation, this problem is harder to solve for non-rigid registration. The solution that we propose in this work is to use the local phase of the magnitude of the local structure tensor, instead of the local phase of the image intensity. By doing this, we achieve invariance both to the image intensity and to the local phase and thereby only use the structural information, i.e. the shapes of the objects, for registration.

我们在SCIA会议发表的论文《利用局部结构张量幅值的局部相位实现图像配准》的摘要如下：图像配准的需求日益增长，尤其在医学影像领域。最基础的图像配准方法是匹配两幅强度相似的图像；更复杂的场景则涉及不同强度图像的配准问题，基于相位的算法已被证实在此类场景中表现更优。在部分场景中，基于相位的配准方法同样会失效，例如当待配准图像不仅强度存在差异，局部相位也各不相同。若参考图像中的暗环在源图像中表现为亮环，就属于这类情况。刚性配准算法可借助图像的其他区域计算全局变换，但对于非刚性配准而言，该问题的解决难度更大。本研究提出的解决方案为：采用局部结构张量幅值的局部相位，替代图像强度的局部相位。通过该方法，我们实现了对图像强度与局部相位的双重不变性，从而仅利用结构信息（即物体的形状）完成图像配准。