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Co-registering the Sentinel-1 SAR and Sentinel-2 optical data of EuropeanSpace Agency (ESA) is of great importance for many remote sensing applications.However, we find that there are evident misregistration shifts between theSentinel-1 SAR and Sentinel-2 optical images that are directly downloaded fromthe official website. To address that, this paper presents a fast and effectiveregistration method for the two types of images. In the proposed method, ablock-based scheme is first designed to extract evenly distributed interestpoints. Then the correspondences are detected by using the similarity ofstructural features between the SAR and optical images, where the threedimension (3D) phase correlation (PC) is used as the similarity measure foraccelerating image matching. Finally, the obtained correspondences are employedto measure the misregistration shifts between the images. Moreover, toeliminate the misregistration, we use some representative geometrictransformation models such as polynomial models, projective models, andrational function models for the co-registration of the two types of images,and compare and analyze their registration accuracy under different numbers ofcontrol points and different terrains. Six pairs of the Sentinel-1 SAR L1 andSentinel-2 optical L1C images covering three different terrains are tested inour experiments. Experimental results show that the proposed method can achieveprecise correspondences between the images, and the 3rd. Order polynomialachieves the most satisfactory registration results. Its registration accuracyof the flat areas is less than 1.0 10m pixels, and that of the hilly areas isabout 1.5 10m pixels, and that of the mountainous areas is between 1.7 and 2.310m pixels, which significantly improves the co-registration accuracy of theSentinel-1 SAR and Sentinel-2 optical images.

Improving Co-registration for Sentinel-1 SAR and Sentinel-2 Optical images