Two-Stage Registration of SAR Images With Large Distortion Based on Superpixel Segmentation

When the geometric distortion of the SAR images to be registered is large, the spatial correspondence between the feature points of the two images will change significantly. Hence, the registration of SAR images with large geometric distortion is challenging. To solve this problem, a two-stage registration method of SAR images with large distortion based on superpixel segmentation is proposed in this paper. Firstly, the two SAR images are coarsely registered by geographic coordinate referencing. After coarse registration, superpixel segmentation is performed on the two SAR images respectively. Next, in the superpixel neighborhood of the reference image, we slide the corresponding superpixel template of the sensed image, finding its position with the highest similarity in the reference image. Compared with the traditional fixed-size template, the superpixel template can segment the distorted region more effectively. Meanwhile, with the help of the adaptive threshold detector proposed in this paper, the regions with varying degrees of distortion can be distinguished based on the similarity. Further, the geometry mapping relationship is calculated for the regions with different distortion degrees in the images respectively, and the corresponding feature points in different images are accurately matched to complete the fine registration. Finally, the registration results of regions with different degrees of distortion are fused to obtain the final SAR image registration results. Experimental results based on Sentinel-1 data show that the registration accuracy of the proposed method can reach within 1 pixel.