提出并发展了一套对多源遥感影像(不同传感器、不同分辨率、不同时相的遥感影像)的高精度自动纠正与配准技术与方法。遥感影像首先通过一个多项式模型进行整体粗纠正,然后在待配准影像上提取均匀分布的特征点。以提取的特征点为引导,利用金字塔逐层模板匹配的方法获得配准用同名控制点,基此构建不规则三角网将影像分解为各三角形区域,在每个三角形范围内实现逐三角网的高精度影像纠正与配准。

The high precise method that automatically rectifying and registering the multi-source remote sensing imagery which are from different sensors with different resolutions and taken from different times, is presented in this paper. First of all, the image to be registered is roughly rectified by using the polynomial model. Then, the feature points are extracted automatically, which are distributing evenly on the roughly rectified image. Guided by the extracted feature points, the common points to be used in automatic registration are obtained by using the pyramid-layered template matching technique. Finally, both the geo-refe-rencing image and the image to be precisely registered are divided into a number of triangular regions by constructing the Triangulated Irregular Network (TIN) on them, and the high precise rectification and registration can be fulfilled on each triangular region one by one.