按空间变换关系,图像配准可被归为两个大类: 刚性配准(Rigid Registration)和非刚性配准(Non-rigid Registration)。刚性配准包括平移和旋转变换,非刚性配准包括仿射、.
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In this paper, in allusion to the imaging of the tiros which produce rigid deformation and nonrigid deformation, we review different methods in image registration, include rigid and nonrigid registration, and propose a few amelioration as followed.1.
本文针对气象卫星分时成像所产生的同时具有刚性形变和弹性形变的图像序列，深入系统的研究了图像刚性配准和弹性配准的方法，并根据气象云图的特性和项目的要求对算法进行了一些改进。
参考来源 - 弹性图像配准方法在气象图像中的应用·2,447,543篇论文数据，部分数据来源于NoteExpress
实验证明，该算法可较好地解决非刚性配准问题。
Experiments show that it can solve non-rigid registration problems well.
新增图像配准算法插件：基于灰度的3D刚性配准算法的实现；
NEW Intensity-based 3D Rigid Registration plugin: implement the intensity-based 3D rigid registration algorithm;
标记点的选取及插值函数的确定是非刚性配准方法中最关键的两步。
The control points and the interpolation function are the key factors of the nonrigid algorithm.
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