基于线特征和控制点的可见光和SAR图像配准

以具有典型人造目标的可见光和SAR (Synthetic aperture radar)图像为研究对象,提出一种自适应多尺度快速Beamlet变换方法提取人造目标在可见光和SAR图像的共有特征---线特征, 并基于线特征构造控制点,设计了一种基于控制点特征的匹配度函数,采用基于特征一致的粗配准和基于控制点的精确配准方法,对待配准图像实现由粗到精的自动配准. 实验表明,在可见光和SAR图像存在较大灰度差异、旋转和平移的情况下,该算法仍然能够精确配准图像.

Optical Image and SAR Image Registration Based on Linear Features and Control Points

This paper presents a method for automatically registrating multi-sensor images based on linear features and control points. Taking optical images and synthetic aperture radar (SAR) images containing man-made objects as examples, we propose an adaptive multi-scale fast discrete Beamlet transform to extract the common features for the same man-made objects shown in both images, i.e., the salient linear features. Then, we construct the control points based on the linear features and design the matching function based on the control point features. Automatic coarse-to-fine registration between images of different sensors is realized by the feature consensus based coarse registration and the control points based fine registration. The experiment results show that the proposed method has high registration accuracy for the optical image and SAR image which differ in intensity, rotation or translation.