提出一种基于对齐度和模糊梯度相似性的图像配准方法。
A new approach for image registration is proposed based on alignment metric and fuzzy gradient similarity.
本文提出基于梯度场相似性和邻域膨胀的快速图像匹配方法。
A fast images matching way is implemented in this paper, which is based on gradient similarity and neighbor expansion.
另外，针对进行相似性变换的目标也提出了一种新的候选目标模型，并用类似的梯度下降算法估计目标的平移向量和旋转角度。
Furthermore, a new candidate model is proposed that handles similarity transformation, and the corresponding MS algorithm can be obtained that estimates the translation vector and rotation Angle.
另外，针对进行相似性变换的目标也提出了一种新的候选目标模型，并用类似的梯度下降算法估计目标的平移向量和旋转角度。
Furthermore, a new candidate model is proposed that handles similarity transformation, and the corresponding MS algorithm can be obtained that estimates the translation vector and rotation Angle.
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