  Co-registering the Sentinel-1 SAR and Sentinel-2 optical data of European
Space Agency (ESA) is of great importance for many remote sensing applications.
However, we find that there are evident misregistration shifts between the
Sentinel-1 SAR and Sentinel-2 optical images that are directly downloaded from
the official website. To address that, this paper presents a fast and effective
registration method for the two types of images. In the proposed method, a
block-based scheme is first designed to extract evenly distributed interest
points. Then the correspondences are detected by using the similarity of
structural features between the SAR and optical images, where the three
dimension (3D) phase correlation (PC) is used as the similarity measure for
accelerating image matching. Finally, the obtained correspondences are employed
to measure the misregistration shifts between the images. Moreover, to
eliminate the misregistration, we use some representative geometric
transformation models such as polynomial models, projective models, and
rational function models for the co-registration of the two types of images,
and compare and analyze their registration accuracy under different numbers of
control points and different terrains. Six pairs of the Sentinel-1 SAR L1 and
Sentinel-2 optical L1C images covering three different terrains are tested in
our experiments. Experimental results show that the proposed method can achieve
precise correspondences between the images, and the 3rd. Order polynomial
achieves the most satisfactory registration results. Its registration accuracy
of the flat areas is less than 1.0 10m pixels, and that of the hilly areas is
about 1.5 10m pixels, and that of the mountainous areas is between 1.7 and 2.3
10m pixels, which significantly improves the co-registration accuracy of the
Sentinel-1 SAR and Sentinel-2 optical images.
