Bundle adjustment of satellite images based on an equivalent geometric sensor model with digital elevation model

Abstract

High-precision georeferencing of satellite stereo images becomes a key issue in multi-source data integration, geometric processing, and analysis for many remote sensing applications. Using existing geographic data, including readily available public data, as geometric reference for georeferencing satellite imagery is an effective and feasible way to improve the positional accuracy and reduce the costs and workforce restrictions on ground control points (GCPs) acquisition. This study proposes a novel bundle adjustment approach of push broom satellite imagery based on an equivalent geometric sensor model (EGSM). As an extension of the collinearity equations, EGSM is equivalent to the rigorous geometric sensor model, whose interior and exterior orientation parameters have clear geometric interpretations. The initial values of EGSM’s parameters can be completely recovered from the RPCs and optimized within the block adjustment without using any metadata of the satellite imagery. Furthermore, a publicly accessible digital elevation model (DEM) is used as constraints in the bundle adjustment to improve the direct georeferencing accuracies without GCPs. A set of pseudo observation equations is incorporated into the EGSM associated with appropriate weights based on the estimated variance of height differences between the tie points and the DEM surface. The performance of the proposed approach was evaluated by using 143 stereo scenes of Chinese Ziyuan-3 (ZY-3) images and the global DEM data SRTM GL3, ASTER GDEM, and AW3D30. The experimental results revealed that the proposed approach could improve not only vertical accuracies but also horizontal accuracies of satellite stereo images. The geopositional accuracy after adjustment is dependent on the quality and accuracy of the reference DEM itself. With AW3D30 as exclusive controls, the horizontal and vertical root mean square errors (RMSEs) of the experimental images are reduced from 17.3 m and 2.6 m to 2.5 m and 1.5 m, respectively. The horizontal accuracy corresponds to about 1.2 pixels in the image space, and the vertical accuracy is about 0.6 pixels with the base-height ratio of ZY-3 stereo images being 0.81. The generazation ability of the approach was further proved by the experiments of WorldView-3 stereo images.