Multi-sensor optical remote sensing image registration based on Line-Point Invariant
Xianmin Wang, Qizhi Xu · 2016
Due to the different imaging modalities and acquisition time, keypoint-based registration methods often suffer from false matches of keypoints while utilizing to register the optical remote sensing images from multi-sensors. In this paper, we proposed a novel method based on Line-Point Invariant for the multi-sensor image registration. First, the line segments of the images are extracted, and then the salient line segments are detected depending upon the adaptive confidence. Subsequently, conjugate salient lines between the two images are identified as the registration primitives by the probability relaxation labelling approach. Second, we obtain the SIFT keypoints of the images and establish the matches of the keypoints based on the Line-Point Invariant via dual matching. Consequently, false keypoint matches are greatly reduced and the correct match rate is significantly enhanced. The experiments conducted on various multi-sensor images demonstrate the effectiveness of the proposed method.