True Digital Orthophoto Maps (TDOMs) are essential products for digital twins and Geographic Information Systems (GIS). Traditionally, TDOM generation involves a complex set of traditional photogrammetric process, which may deteriorate due to various challenges, including inaccurate Digital Surface Model (DSM), degenerated occlusion detections, and visual artifacts in weak texture regions and reflective surfaces, etc. To address these challenges, we introduce TOrtho-Gaussian, a novel method inspired by 3D Gaussian Splatting (3DGS) that generates TDOMs through orthogonal splatting of optimized anisotropic Gaussian kernel. More specifically, we first simplify the orthophoto generation by orthographically splatting the Gaussian kernels onto 2D image planes, formulating a geometrically elegant solution that avoids the need for explicit DSM and occlusion detection. Second, to produce TDOM of large-scale area, a divide-and-conquer strategy is adopted to optimize memory usage and time efficiency of training and rendering for 3DGS. Lastly, we design a fully anisotropic Gaussian kernel that adapts to the varying characteristics of different regions, particularly improving the rendering quality of reflective surfaces and slender structures. Extensive experimental evaluations demonstrate that our method outperforms existing commercial software in several aspects, including the accuracy of building boundaries, the visual quality of low-texture regions and building facades. These results underscore the potential of our approach for large-scale urban scene reconstruction, offering a robust alternative for enhancing TDOM quality and scalability.
真实数字正射影像图 (TDOMs) 是数字孪生和地理信息系统 (GIS) 的重要产品。然而，传统 TDOM 生成方法依赖复杂的摄影测量流程，容易受到各种挑战的影响，例如数字表面模型 (DSM) 的不准确性、遮挡检测的退化，以及弱纹理区域和反射表面中的视觉伪影等问题。 为了解决这些问题，我们提出了 TOrtho-Gaussian，一种基于 3D Gaussian Splatting (3DGS) 的新方法，通过正交投影优化的各向异性高斯核生成 TDOM。具体而言： 1. 简化正射影像生成：我们通过将高斯核正交投影到 2D 图像平面，提供了一种几何上优雅的解决方案，避免了对显式 DSM 和遮挡检测的需求。 2. 处理大规模区域的 TDOM：我们采用分治策略，优化 3DGS 的内存使用和训练与渲染效率，从而支持大规模区域的正射影像生成。 3. 全各向异性高斯核设计：我们设计了一个完全各向异性的高斯核，根据不同区域的特性进行适配，特别是在提高反射表面和细长结构的渲染质量方面表现出色。 通过大量实验评估，我们的方法在多个方面优于现有的商业软件，包括建筑边界的精确度、低纹理区域和建筑立面的视觉质量。这些结果表明，TOrtho-Gaussian 为大规模城市场景重建提供了一种强大的替代方法，显著提升了 TDOM 的质量和可扩展性。