提出了一种新的基于空间辅助面特征的主被动遥感影像区域自动配准方法, 该方法借鉴了全局区域配准高精度与局部区域配准低复杂度的算法特征, 采用正、反函数变换法提取具有相同角度和尺度的空间特征, 并采用归一化互相关系数法定义灰度相似性, 通过构建空间辅助面, 将空间特征和灰度相似性有效地结合起来, 共同用于影像的自动配准。文中选取了SPOT与ASTER影像、ASAR和ASTER影像两组数据进行实验, 并提取基准影像和配准后待配准影像的不同部位相间拼接形成结果图, 从中可以看出各种地物在拼接处表现自然平滑。实验结果证明, 该方法简单易行, 且配准精度较高。

A new method of automatic region registration method based on spatially assistant planes is introduced in this paper. The method integrates both algorithm features of the global-region registration method’s high precision and the local-region registration method’s low complexity. Spatially assistant features with the same angle and resolution are calculated from, and the gray similarity is defined by normalized cross-correlation coefficient. By introducing the spatially assistant planes, spatially assistant features and gray similarity are combined together to register images. Two groups of images SPOT and ASTER, ASAR and ASTER, were tested. A mosaic was formed from the reference and re-sampled sensed images. In the mosaic, lineal features are well-aligned, which effectively proves that the automatic registration has a high accuracy.