Fast and Robust Optical-to-SAR Remote Sensing Image Registration Using Region-Aware Phase Descriptor

Automatic registration of optical and synthetic aperture radar (SAR) remote sensing images has been extensively researched for decades. However, fast and robust multimodal image registration is still a challenge due to the significant region differences in many remote sensing scenarios (e.g., city and sea region coexist in single harbor imaging). To address this problem, this article proposes a novel optical-to-SAR registration method called FED-HOPC, which integrates the fast Fourier transform (FFT) and weighted edge density (WED) map into the histogram of oriented phase congruency (HOPC)-based registration framework. FFT is used to accelerate the 3-D normalized cross correlation (NCC) for coarse matching. WED map is employed to detect adaptive block-based interest points, which are used to build region-aware HOPC descriptors for the following fine registration. To evaluate the performance of FED-HOPC, extensive experiments on four optical-to-SAR registration datasets are conducted. The results demonstrate that FED-HOPC effectively registers optical-to-SAR images with significant region differences and outperforms several state-of-the-art (SOTA) methods, including HOPC, modality-independent neighborhood descriptor (MIND), modality independent region descriptor (MIRD), and channel feature of orientated gradient (CFOG).