The Photogrammetric Record (2018) DOI: 10.1111/phor.12229 TRUE ORTHOPHOTO GENERATION USING LINE SEGMENT MATCHES Qiang WANG (wangqiang_study@163.com) College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China; and Beijing Key Laboratory of Spatial Information Integration and Its Application, Peking University, Beijing, China Lei YAN (lyan@pku.edu.cn) Beijing Key Laboratory of Spatial Information Integration and Its Application, Peking University, Beijing, China Yanbiao SUN* (yanbiao.sun@ucl.ac.uk) Department of Civil, Environmental and Geomatic Engineering, University College London, UK Ximin CUI (cxm@cumtb.edu.cn) College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China Hugh MORTIMER (hugh.mortimer@stfc.ac.uk) Rutherford Appleton Laboratory, Harwell, Oxford, UK Yanyan LI (liyan.@pku.edu.cn) School of Software and Microelectronics, Peking University, Beijing, China *Corresponding author Abstract When generating a true orthophoto from aerial urban scenes, especially those containing man-made features with large height differences, sawtooth effects in feature edges can occur in the rectified images. Aiming to eliminate such effects, this study proposes an advanced orthorectification method using line segment matches, allowing 3D building edges to be accurately reconstructed. The corresponding 2D line segments are first extracted and matched, enabling the reconstruction of 3D line segments by joining two planes and imposing a line end-point constraint. The 3D line segments are then dissected into discrete 3D points to be incorporated into the 3D point cloud obtained by a dense matching algorithm. Finally, a more complete and accurate triangulated irregular network (TIN) model can be constructed to provide important basic data for true orthophoto production. Experimental results show that sawtooth effects can be eliminated, resulting in significantly improved quality in the true orthophotograph. © 2018 The Authors The Photogrammetric Record © 2018 The Remote Sensing and Photogrammetry Society and John Wiley & Sons Ltd