一种基于动态模板和等角变换的遥感影像地面控制点匹配算法

A remote sensing image ground control point matching algorithm based on dynamic template and conformal transform

传统的基于影像灰度的控制点匹配算法,存在着运算量大,识别精度较低,约束条件多等不足。为解决上述问题,本文对传统算法进行了优化,主要思路是:在利用遥感影像先验知识确定搜索子区的基础上,首先采用动态模板进行不等距搜索,然后利用灰度相关系数双阈值和等角变换对目标控制点进行判别,最后结合控制点间的空间位置关系对未识别出的控制点进行定位。本文给出具体的实施流程,并结合ASTER和TM两种成像差异显著的图像数据,对优化前后的匹配算法均进行了试验,给出了试验结果和对比分析。结果表明,采用动态模板结合等角变换的匹配算法,无论在运算效率上,还是在控制点识别精度上,都较之传统匹配算法有明显优势,具有较强的适应性和应用价值。

There are some shortages in traditional image matching algorithm based on gray degree,such as huge quantity of calculation,lower accuracy,and too many restrictions of application.In order to solve these problems,an optimized algorithm is introduced.It includes several aspects:on the basis of confirming the sub image by understanding prior knowledge of Remote Sensing image,the first step is to search the sub image unequdistantly with dynamic template,the second step is to locate the true target points by two thresholds of gray degree correlation coefficient and conformal transform,the last step is to calculate the true location of the false target points by the spatial location relations of ground control points.The work flow is described in detail.Moreover,a comparison between traditional and modified image matching algorithm is performed with an ASTER image and a TM image with distinct imaging differences.We can conclude that the modified algorithm is superior to the traditional one,with its higher accuracy and efficiency,its adaptability.