Urban surface model generation from remotely sensed airborne image sequence data

This paper presents an improvement of epipolar plane image (EPI) analysis technique for producing high‐accuracy urban 3D surface data from remotely sensed airborne image sequences. The method first forms 3D spatio‐temporal solid data from the image sequences, then calculates 3D ground coordinates using the slope and intercept of straight lines in the EPIs, which are generated by slicing the 3D spatio‐temporal solid data along a temporal dimension. The early experimental results demonstrated that the digital elevation model (DEM) using this technique is quite rough. The improvements of mathematical model and computational procedures for increasing the DEM accuracy are presented in this paper. The improvement of the mathematical model is implemented via rectifying those possible errors without directly solving the rectification parameters, and the improvement of the computational process is implemented via avoiding nonlinear iteration of rectification process. Three test fields in Berlin, Germany were established for testing the algorithms and methods. The experimental results demonstrated that this method is radically different from traditional two‐view stereo photogrammetric methods commonly used in 3D urban surface information extraction, and is a useful tool in solving the depth discontinuities and occlusion problems with which photogrammetrists have been wrestling for decades. With the presented improved method and computational procedures, the accuracy of the DEMs in three urban test areas was improved by over 34% in comparison with the DEMs generated from the original image sequences, and computational time decreased by 30%.