Problem
Research questions and friction points this paper is trying to address.
Digital Surface Model
3D Gaussian Splatting
height-layer mixing
DSM reconstruction
optical satellite imagery
HLC-GS: Risk-Map-Guided Height-Layer Consistency Gaussian Splatting for DSM Reconstruction from Optical Satellite Imagery
🤖 AI Summary
本文提出HLC-GS方法，通过风险图引导的高度层一致性高斯点渲染来解决从光学卫星影像重建DSM时的高度层混合问题。
📝 Abstract
A Digital Surface Model (DSM) is a fundamental geospatial data product for representing the elevation of the Earth's surface. Recently, 3D Gaussian Splatting (3DGS) has shown considerable potential for DSM reconstruction from multi-view optical satellite imagery due to its explicit scene representation and efficient optimization. However, in 3DGS-based DSM generation, alpha-weighted aggregation of Gaussian altitudes may blend splats from different height layers at the same rendered pixel or DSM sampling location, producing non-physical intermediate elevations and height-layer mixing errors. To address this problem, we propose HLC-GS, a risk-map-guided height-layer consistency Gaussian Splatting method for DSM reconstruction from optical satellite imagery. HLC-GS consists of a risk map module, a dominant-layer reliability correction module, and a secondary-layer suppression module. The risk map localizes high-risk pixels with abnormal height dispersion and unreliable dominant-layer responses, while the latter two modules regularize unreliable dominant-layer responses and suppress weakly supported far secondary-layer responses. Extensive experiments are conducted on the DFC2019 and IARPA2016 datasets. Compared with six state-of-the-art DSM reconstruction methods, HLC-GS achieves better overall accuracy. Compared with the latest and precision-enhanced EOGS, HLC-GS reduces the average MAE from 1.46 m to 1.18 m and the average RMSE from 2.78 m to 2.58 m over the evaluated scenes, while improving PAG$_{2.5}$ from 86.09\% to 88.61\%. Overall, these results demonstrate that explicitly modeling per-pixel height-layer consistency alleviates height-layer mixing and improves the geometric quality of 3DGS-based DSM reconstruction from optical satellite imagery.
Innovation
Methods, ideas, or system contributions that make the work stand out.
risk-map-guided
height-layer consistency
Gaussian Splatting
DSM reconstruction
optical satellite imagery
🔎 Similar Papers
No similar papers found.
