Liang Shiyu, Gao Yang, Hu Chonghao, Hao Aimin, Qin Hong
IEEE Trans Vis Comput Graph. 2025 Sep;31(9):5348-5363. doi: 10.1109/TVCG.2024.3447668.
Real-time subsurface scattering techniques are widely used in translucent material rendering. Among advanced methods that rely on the bidirectional scattering-surface reflectance distribution function (BSSRDF), screen space algorithms exhibit limited translucency, while existing large-distance methods are inefficient and yield poor illumination details. To address these limitations for better large-distance scattering, we develop a novel algorithm by extending the photon beam diffusion (PBD) model within the light view and screen space. Unlike surface irradiance in prior methods, we incorporate the refracted beam in the medium into real-time scattering estimation, presenting a new consideration for photon beam utilization. Concretely, we store all photon beam samples in light view textures and utilize an adaptive sampling pattern for beam sample selection in large filtering kernel sizes. This can reduce the sample count based on surface attributes. In screen space, virtual sources are derived from samples to estimate PBD contributions, with an approximation that preserves boundary conditions. To avoid possible overestimation, we implement correction factors that scale contributions, effectively aligning our results with path-tracing references. Through these reformulations, our efficient PBD generates results closest to references among existing methods. The experiments accurately represent better front-face illumination details and backlit translucency effects, while significantly accelerating performance compared to previous large-distance methods.
实时次表面散射技术广泛应用于半透明材质渲染。在依赖双向散射表面反射分布函数(BSSRDF)的先进方法中,屏幕空间算法的半透明效果有限,而现有的远距离方法效率低下且光照细节不佳。为解决这些限制以实现更好的远距离散射,我们通过在光视图和屏幕空间内扩展光子束扩散(PBD)模型开发了一种新颖的算法。与先前方法中的表面辐照度不同,我们将介质中的折射光束纳入实时散射估计,为光子束利用提出了新的考量。具体而言,我们将所有光子束样本存储在光视图纹理中,并在大滤波内核尺寸下使用自适应采样模式进行光束样本选择。这可以根据表面属性减少样本数量。在屏幕空间中,从样本中导出虚拟源以估计PBD贡献,并采用一种保留边界条件的近似方法。为避免可能的高估,我们实施了缩放贡献的校正因子,有效地使我们的结果与路径追踪参考对齐。通过这些重新公式化,我们高效的PBD在现有方法中生成了最接近参考的结果。实验准确地呈现了更好的正面光照细节和背光半透明效果,同时与先前的远距离方法相比显著提高了性能。