Registration of SAR and Optical Images by Weighted Sift Based on Phase Congruency
Shuai Jiang, Uaz Jzang, Bingnan Wang, Xiangyu Zhu, Maosheng Xiang, Xikai Fu, Xiaofan Sun · 2018
In this paper, to address problems in the registration of synthetic aperture radar (SAR) and optical images due to large gray differences, the scale-invariant feature transform (SIFT) approach based on phase congruency (PC-SIFT) is proposed. This approach is used to address the gradient inversion in multi-source images, and it is based on optimizing the dominant direction interval of the descriptors. We construct a new descriptor by combining phase consistency and the gradient amplitude, which is referred to as PCG-SIFT descriptor. The proposed algorithm is suitable for multi-sensor images with large gray differences and significant edge features The results of experiments show that compared to the traditional gradient-based SIFT descriptor, the PC-SIFT descriptor and PCG-SIFT descriptor improve the robustness and matching probability of the registration algorithm for multi-source images.