针对现有配准方法在用于多光谱图象与SAR遥感图象配准时,存在受SAR图象斑纹噪声影响大、手工选取配准控制点(RCP)精度低、利用图象景物特征配准时获取区域和边沿困难等缺点,以Landsat TM图象与JERS-1 SAR图象配准为例,提出了一种利用分类图象形成的二值图象相关寻求配准控制点,并应用表面样条插值以提高RCP精度的多光谱与SAR遥感图象配准方法.由于在SAR图象分类中利用了斑纹噪声的纹理特征,因而使斑纹噪声不再成为配准障碍.该方法对实验图象的配准误差小于1个象素.

Considering the shortcomings of low accuracies in manual selecting registration control points (RCP) and difficulties in extrcting regions and edges because of SAR speckle noise in the registration for multi-spectrum and SAR remote sensing images, a new registration method for multi-spectrum and SAR images is presented in this paper. With the images of Landsat TM and JERS-1 SAR, this method extracts the RCP from the correlation of the binary classified images, and the RCP accuracies are improved with surface spline interpolation. Because the texture characters of SAR speckle noise are employed in SAR image classification, the speckel noise is no longer obstacles in the registration, and all these efforts make the registration errors of experiment images lower than a pixel.