一种基于边缘相关的多传感器图像配准方法

Niu Li-pi, Yang Ying-yun, Zhang Wen-hui, Jiang Xiu-hua
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引用次数: 1

摘要

本文提出了一种基于边缘相关的多传感器图像配准方法。首先提取图像的边缘,对较长的边缘进行改进的Freeman编码;其次,通过积分相关系数等方法计算链码的初始化相关性,然后采用基于边缘相关中心的相对距离比直方图聚类检测器和基于边缘相关平均方向角差的角度直方图聚类检测器进行一致性检测。在计算边缘相关的平均方向角差时,本文提出的改进直方图法比直线拟合法要好得多。最后得到精确的边缘相关对,然后在相关部分应用最小二乘算法(LSM)获得图像配准参数。本文提出的方法可以实现大范围平移和旋转图像的配准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-sensor image registration approach based on edge-correlation
In this paper we propose a multi-sensor image registration approach based on edge-correlation. Firstly, edges of images are extracted and the longer edges are coded by modified Freeman. Secondly initializing correlation of chain code is calculated by integrating correlation coefficient and other methods, then the consistency detection succeeds by relative distance ratio histogram clustering detector based on center of edge correlation and angle histogram clustering detector based on average directional angle difference of edge correlation. During the calculation of average directional angle difference of edge correlation, modified histogram approach in this paper is much better than line-fitting approach. Finally accurate edge correlation pair is obtained, and then image registration parameter is attained by applying least square algorithm (LSM) in interrelated parts. The approach presented in this paper can register images of wide translational and rotary range.
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