High-Resolution Optical and SAR Image Registration Using Local Self-Similar Descriptor Based on Edge Feature
Yiqun Pan, Ling Tong, Yuxia Li, Fanghong Xiao, Haoyu Wang · 2020
Due to different imaging mechanisms, the registration of optical and Synthetic Aperture Radar (SAR) image is a very challenging task. Many optical and SAR registration methods have been proposed. But most of them are for low-to-medium resolution images, and less for high-resolution images. Therefore, this paper proposes a high-resolution optical and SAR image registration method using local self-similar descriptor based on edge feature. Firstly, a Gauss-Gamma bi-windows algorithm is used to extract the edge intensity maps of the images respectively. Its function is to eliminate the non-linear gray-scale difference between SAR and optical images, and also to avoid the interference of isolated speckle noise on feature point extraction. Then, local self-similar descriptor is extracted on the edge intensity map, and descriptor matching is performed using Euclidean distance. Finally, the fast sample consensus algorithm is used to eliminate mismatched point pairs. The experimental results can effectively resist speckle noise and radiation differences, and obtain pixel-level registration accuracy.