Spatiotemporal Filtering for Light Transport Simulation
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Solution Overview
Problem
Existing light transport simulation techniques, such as ray tracing, face impractical processing and memory resource demands, especially in real-time applications, and often result in visual artifacts like flickering due to temporal reprojection and sampling noise.
Innovation Solution
The implementation of spatiotemporal filtering in world-space using spatial hashing to refine and reuse irradiance estimates, combined with multi-pass image-space filtering that selects and weights neighboring pixels based on proximity and normal similarity, and adapts to material properties and camera motion for adaptive temporal smoothing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ray tracing techniques are used to simulate light transport, then visual realism and accuracy are improved, but processing resources and memory requirements become impractical
Solution Approach 1:
The system pre-calculates and stores irradiance information in world-space hash maps before rendering frames. By performing light transport simulation in advance and caching the results spatially organized by world coordinates, the system avoids repeating expensive ray tracing calculations for every frame, thus reducing real-time processing requirements while maintaining visual realism
Solution Approach 2:
The system creates simplified copies of lighting information by storing irradiance estimates in hash maps that represent world-space locations. These compressed representations serve as proxies for full ray tracing results, enabling fast retrieval and reuse without requiring the complete original simulation data, thus reducing memory and processing demands
2Productivity
If temporal reprojection is used to reduce processing resources, then productivity is improved, but visual artifacts like flickering are introduced
Solution Approach 1:
The system introduces world-space hash maps as an intermediary between full ray tracing and temporal reprojection. Instead of directly reprojecting image-space pixels which causes flickering, the system uses world-coordinate-based hash maps to mediate the temporal accumulation, providing a stable reference frame that avoids reprojection artifacts while maintaining processing efficiency
Solution Approach 2:
The system replaces the mechanical reprojection process (which geometrically maps pixels between frames) with a world-space accumulation approach using hash maps. This substitution eliminates the geometric approximations and occlusion issues inherent in reprojection, providing visually stable results while maintaining computational efficiency
3Productivity
If the number of rays or pixels processed is reduced to improve processing speed, then productivity is improved, but manufacturing precision (visual accuracy) deteriorates
Solution Approach 1:
The system performs comprehensive light transport simulation in advance to build detailed irradiance maps in world-space hash maps. By pre-calculating with sufficient sample density and storing the results organized by world coordinates, the system captures accurate lighting information beforehand, allowing reduced sampling in real-time rendering without sacrificing visual accuracy
Solution Approach 2:
The system transitions from image-space to world-space organization of lighting data. By storing irradiance information indexed by world coordinates rather than pixel coordinates, the system enables more efficient spatial reuse of lighting data across multiple pixels and frames, achieving both speed and accuracy through this dimensional transformation
Data Source
AI summary
Approaches presented herein provide systems and methods for lighting a scene in world-space. The systems and methods may generate lighting effects based on both temporally averaged world-space lighting data and screen-space spatial filtering. The lighting data may be based on material properties for objects within an image, where different material properties may lead to larger weighting factors based on a one or more optical properties of an object surface.