Efficient Photon Beam Diffusion for Directional Subsurface Scattering

• Published in: IEEE transactions on visualization and computer graphics Vol. 31; no. 9; pp. 5348 - 5363
• Main Authors: Liang, Shiyu, Gao, Yang, Hu, Chonghao, Hao, Aimin, Qin, Hong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2025
• Subjects: Accuracy; Adaptive sampling; BSSRDF; Faces; Lighting; Photonics; real-time rendering; Real-time systems; Rendering (computer graphics); Scattering; subsurface scattering; translucent material
• ISSN: 1077-2626; 1941-0506; 1941-0506
• 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.