HydroGaussian: Physically‐Guided Hierarchical Gaussian Splatting for Underwater Scene Reconstruction

Abstract Reconstructing underwater three‐dimensional (3D) scenes presents a significant yet captivating challenge, with applications spanning from naval robotics to virtual reality. Although 3D Gaussian Splatting (3DGS) demonstrates great potential in underwater 3D scene reconstruction, its capability as an explicit renderer to express underwater lighting models remains insufficient. This paper introduces a hierarchical Gaussian splatting model constrained by a physical‐guided underwater lighting model. The proposed method streamlines the 3DGS fitting process for backscattering media through the analysis of the relationship between the underwater rendering equation and the lighting model. The proposed model achieves optimal decoupling between surface colours and backscattering effects by explicitly computing ray‐Gaussian intersections to constrain 3DGS positions near depth surfaces. To address the depth estimation challenges in infinite background regions, we introduce a hierarchical structure that effectively regularizes far‐field depth values. Experiments on public underwater datasets demonstrate that HydroGaussian successfully mitigates challenging underwater light scattering effects, yielding substantial improvements in both visual fidelity and scene restoration quality compared to state‐of‐the‐art methods. The implementation will be made publicly available at https://github.com/SXYuuuuuu/HydroGaussian .