GEDR:Gaussian-Enhanced Detail Reconstruction for Real-Time High-Fidelity 3D Scene Reconstruction

3D Gaussian Splatting (3DGS) has gained significant attention for its exceptional performance in real-time rendering and novel view synthesis. However, the traditional Gaussian densification method struggles to effectively capture the complexity of regions with insufficient point cloud density. Although this method improves overall rendering quality by expanding the point cloud to millions of points, blurring and distortion issues still persist in edge details and high-intensity lighting regions. To address these limitations, this paper proposes Gaussian-Enhanced Detail Reconstruction (GEDR), which enhances 3DGS with two key innovations: (1) Multi-scale adaptive Gaussian kernels, dynamically adjusted based on geometric features such as gradient and curvature, enabling finer reconstruction in high-detail regions while maintaining efficiency. (2) Opacity optimization leveraging illumination information, reducing artifacts caused by ambient lighting variations and ensuring stable rendering in large-scale scenes. This strategy ensures efficient and stable rendering, even in large-scale scenes. Evaluations on Mip-NeRF 360 and Tanks & Temples datasets demonstrate that GEDR significantly improves detail preservation, complex region restoration, and robustness to lighting changes while maintaining controlled storage overhead. These results highlight GEDR’s advantages over traditional 3DGS in high-fidelity scene reconstruction.