一种适应较大比例变化的多传感器图像配准方法

 提出了一种基于边缘曲率区域极值和边缘相关的图像配准方法。算法首先提取图像的较长边缘并对其进行改进的Freeman编码;然后使用Freeman码计算曲线的曲率,根据曲率极值的对应情况初始匹配边缘并得到比例变换因子;然后重采样图像,使用边缘相关、一致性检测方法得到对应的相关边缘对,最后使用最小二乘法得到图像的配准参数。算法可以适应配准图像间有较大旋转角度和较大平移变换等情况。

Multi-Sensor Image Registration Method Adapted for Larger Scale

A new method based on the edge curvature area extreme-value and the edge correlation for efficient image registration is proposed.Firstly,draw some edges from the pending image,set the edge length threshold by using a comparatively large Gauss parameter,save the longer edges only,and mode them with improved Freeman.Secondly,with the Freeman code aforementioned,compute the curvature of the curve,and match the edges according to the corresponding situation of the curve area curvature and get the scale transform parameter.Thirdly,resample the image by using that scale parameter,draw some edges again and get the corresponding pairs of edges by applying the edge correlation and consistency check means. Finally,obtain the registration parameter of the image by using the Least Mean Square.This arithmetic applies in situations like registration images with comparatively rotating angles and translational motions.