一种遥感影像地面控制点动态模板匹配算法

AN EFFICIENT REMOTE SENSING IMAGE GROUND CONTROL POINT MATCHING ALGORITHM BASED ON DYNAMIC TEMPLATE

鉴于影像灰度控制点匹配算法运算量大、识别精度低以及约束条件多等不足,本文对该算法做了改进。主要思路是:在进行模板运算时,对目标影像采用动态模板进行不等距搜索;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;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。文中给出了具体的实施流程,并采用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进行对比试验。结果表明,改进算法在运算效率、识别精度以及适应性方面,都比传统算法有明显优势。

There exist some shortages in the traditional image matching algorithm based on gray degree, such as huge quantities of calculation, relatively low accuracy, and too many restrictions in application. In order to solve these problems, this paper puts forward an optimized remote sensing image matching algorithm. The main ideas include the following several aspects: On the basis of confirming the subimage of the target image by understanding prior knowledge of remote sensing image, the first step is to search the subimage of the target image non-equidistantly with dynamic template, the second step is to locate the target position by two threshold gray degree correlation coefficients and conformal transform, and the last step is to judge the target position of the ground control point not recognized correctly by the spatial location relations of ground control points. The work flow is introduced in detail. Moreover, a comparison experiment on traditional and modified image matching algorithms is performed with an ASTER image and a TM image. From the results obtained, we can reach the conclusion that the modified algorithm is superior to the traditional algorithm in that it has much more higher accuracy and efficiency than the latter and hence it should have higher adaptability and applicability.