Relative geometric correction of multiple satellite images by rigorous block adjustment

With the development of satellite imaging technology, many Earth observation satellites have been launched and almost all areas of the Earth are daily covered by satellite images. It is promising to utilize such images in change detection, monitoring, semantic classification, etc. To obtain geometric information on each pixel in images, Rational Polynomial Coefficients (RPCs) of a Rational Functional Model (RFM) are provided with satellite images. However initial RPCs may include geometric errors. Therefore, errors in initial RPCs must be corrected before utilization. In this study, we attempt to perform rigorous block adjustments for refining RFMs of overlapping satellite images without ground control points. Our rigorous block adjustment method operated based on automatically extracted tie-points within overlapping areas. It estimates the optimal adjustment coefficients of RPCs and ground coordinates of tie-points. We achieved relative geometric correction of multiple satellite images by transforming the images based on the estimated adjustment coefficients. As a result, an initial RFM model with an error of around 21.73 pixels was corrected to within 1 pixel, and the reprojection error of check points decreased to 0.87 pixels. We also confirmed that our method showed more accurate results than general image registration methods, such as 2D homography transformation.