用2D高斯点阵高效生成高精度正射影像图，省去传统繁琐流程。
High-Quality Spatial Reconstruction and Orthoimage Generation Using Efficient 2D Gaussian Splatting
- 基于2D高斯点阵直接重建，无需数字表面模型和遮挡检测
- 支持高分辨率场景重建，复杂地形与细结构保持高质量渲染
- 资源消耗低，适合大规模城市与环境监测应用
真实数字正射影像图（TDOM）以高几何精度和密集图像特征为特点，广泛应用于城市规划、基础设施管理与环境监测。传统TDOM生成需依赖数字表面模型（DSM）和遮挡检测等复杂流程，计算开销大且易出错。本文提出一种基于2D高斯点阵（2DGS）的替代方法，无需显式构建DSM或进行遮挡检测。通过深度图获取每个像素的空间信息，实现高精度场景重建。采用分治策略，在较低资源开销下完成高质量的高分辨率TDOM训练与渲染，有效保持复杂地形与细长结构的渲染质量，同时不降低效率。实验表明该方法在大规模场景重建与高精度地形建模方面具有显著优势。该技术可提供精确空间数据，助力用户更优地图决策。
原文摘要 · Abstract (English)
Highly accurate geometric precision and dense image features characterize True Digital Orthophoto Maps (TDOMs), which are in great demand for applications such as urban planning, infrastructure management, and environmental monitoring. Traditional TDOM generation methods need sophisticated processes, such as Digital Surface Models (DSM) and occlusion detection, which are computationally expensive and prone to errors. This work presents an alternative technique rooted in 2D Gaussian Splatting (2DGS), free of explicit DSM and occlusion detection. With depth map generation, spatial information for every pixel within the TDOM is retrieved and can reconstruct the scene with high precision. Divide-and-conquer strategy achieves excellent GS training and rendering with high-resolution TDOMs at a lower resource cost, which preserves higher quality of rendering on complex terrain and thin structure without a decrease in efficiency. Experimental results demonstrate the efficiency of large-scale scene reconstruction and high-precision terrain modeling. This approach provides accurate spatial data, which assists users in better planning and decision-making based on maps.
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