用物理光照模型提升小行星表面重建精度。
AstroSplat: Physics-Based Gaussian Splatting for Rendering and Reconstruction of Small Celestial Bodies
- 引入行星反照率模型，实现基于物理的高保真表面渲染
- 在黎明号任务真实图像上验证，重建精度优于传统方法
- 适合需要精确光照与材质分析的深空探测研究
基于图像的表面重建与表征对小天体（如小行星）探测任务至关重要，可支撑任务规划、导航与科学分析。近年来，高斯点阵技术实现了高质量神经场景表征，但通常依赖球谐函数强度参数化，仅关注外观而未显式建模材料属性或光-表面相互作用。本文提出 AstroSplat，一种融合行星反照率模型的物理基高斯点阵框架，提升从原位影像中自主重建与光度表征小天体表面的能力。该方法在 NASA 黎明号任务的真实影像上进行了验证，结果表明其渲染性能和表面重建精度均优于传统的球谐函数参数化。
原文摘要 · Abstract (English)
Image-based surface reconstruction and characterization are crucial for missions to small celestial bodies (e.g., asteroids), as it informs mission planning, navigation, and scientific analysis. Recent advances in Gaussian splatting enable high-fidelity neural scene representations but typically rely on a spherical harmonic intensity parameterization that is strictly appearance-based and does not explicitly model material properties or light-surface interactions. We introduce AstroSplat, a physics-based Gaussian splatting framework that integrates planetary reflectance models to improve the autonomous reconstruction and photometric characterization of small-body surfaces from in-situ imagery. The proposed framework is validated on real imagery taken by NASA's Dawn mission, where we demonstrate superior rendering performance and surface reconstruction accuracy compared to the typical spherical harmonic parameterization.
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