图像分层匹配的HJ-1A/B CCD影像自动几何精校正技术与系统实现

Automatic geometric precise correction technology and system based on hierarchical image matching for HJ-1A/B CCD images

环境与灾害监测预报小卫星星座(环境一号卫星,HJ-1A/B)自发射以来,在环境监测、灾害评估、土地资源调查等领域发挥了重要的作用。但是HJ-1A/B卫星CCD图像的2级产品(HJ-1 CCD图像)几何精度低,实际应用中需要进行几何精校正。HJ-1 CCD图像具有宽覆盖、大视场角、几何变形复杂的特点,几何精校正难度大。针对该问题,本文提出了一个以Landsat TM全球拼接图像为基准,基于Forstner算子和模板匹配的分层配准方法。该方法使用分层匹配获得的大量高精度且分布均匀的控制点构建Delaunay三角网,有效地解决了HJ-1 CCD图像的几何精校正问题。在配准技术研究的基础上,研发了HJ-1 CCD图像几何精校正系统,系统具有全球HJ-1 CCD图像的自动批量处理能力。实验结果表明,本文提出的几何精校正方法精度高,实现了环境星图像的自动批量处理。

Two optical satellites HJ-1A and HJ-1B play an important role in natural disaster monitoring and risk assessment, environment monitoring, and other fields. However, the system geometric correction products of HJ-1 CCD have low geometric precision and need to be corrected. H J-1 CCD images have a larger aspect angle, a wider swath width and a larger image size. Furthermore, local geometric distortions are too complex in one scene. Thus, the geometric correction is difficult. In this paper, a hierarchical approach to automatic registration between HJ-1 CCD images and Landsat TM images based on the combination of Forstner operator and template matching is proposed firstly. The approach can obtain a large number of Control Points （CPs） with high precision and even distribution. These CPs are used to generate Delaunay TIN. Then, local distortions of HJ-1 images can be rectified with the Delaunay triangulated irregular network （Delaunay TIN）. A geometric precise correction system is then imple- mented, thereby completing the automatic processing for global HJ-1 images. Experiments with six HJ-1 images demonstrate that the approach is efficient, accurate, and fully automatic.