Multi-sensor images registration based on SIFT and extended phase correlation
Meijun Zhou, Liaoying Zhao, Jianfeng Jiang, Shuhan Chen, Han Yang, Xiaorun Li · 2020
To achieve registration of multi-sensor images by utilizing complementary information, this paper proposes an iterative image registration method based on scale invariant feature transformation (SIFT) and extended phase correlation (EPC), named as SIFT_IEPC. The reference image and the sensed image are pre-registered by SIFT and a geometrical outlier removal method. Overlapping regions corresponding to the reference image and the rectified sensed image are partitioned to block image with equal size, and the extended phase correlation is used to estimate the translation parameters between each block pairs, which are used to tune the matched feature point pairs in the block. The tuned feature point sets are used to update the registration parameters between the reference image and the sensed image. Repeat the process of EPC matching and feature tuning until terminate condition is satisfied. Experiments on three pairs including simulated and real remote sensing images are conducted to evaluate the performance of SIFT_IEPC. The comparison experiments demonstrate that SIFT_IEPC can apparently increase the accuracy of image registration.