2022/04/05 by Mojdeh Ebrahimikia, Ali Hosseininaveh, Ali Hosseininaveh Ahmadabadian
Earth and Planetary Sciences · Engineering · Environmental Science · #3D Surveying and Cultural Heritage #Remote Sensing and LiDAR Applications #Robotics and Sensor-Based Localization
paper · doi:10.1111/phor.12409
crossref issued 2022/04/05 · crossref published 2022/04/05 · crossref published-online 2022/04/05 · openalex publication_date 2022/04/05 · crossref created 2022/04/06 · crossref published-print 2022/06/01 · openalex created_date 2025/10/10 · crossref deposited 2026/01/05 · crossref indexed 2026/07/28 · openalex updated_date 2026/07/28
Abstract After considering state‐of‐the‐art algorithms, this paper presents a novel method for generating true orthophotos from unmanned aerial vehicle (UAV) images of urban areas. The procedure consists of four steps: 2D edge detection in building regions, 3D edge graph generation, digital surface model (DSM) modification and, finally, true orthophoto and orthomosaic generation. The main contribution of this paper is concerned with the first two steps, in which deep‐learning approaches are used to identify the structural edges of the buildings and the estimated 3D edge points are added to the point cloud for DSM modification. Running the proposed method as well as four state‐of‐the‐art methods on two different datasets demonstrates that the proposed method outperforms the existing orthophoto improvement methods by up to 50% in the first dataset and by 70% in the second dataset by reducing true orthophoto distortion in the structured edges of the buildings.