JOURNAL ARTICLE

Fast Computation of Single Scattering in Participating Media with Refractive Boundaries Using Frequency Analysis

Yulin LiangBeibei WangLu WangNicolas Holzschuch

Year: 2019 Journal:   IEEE Transactions on Visualization and Computer Graphics Vol: 26 (10)Pages: 2961-2969   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Many materials combine a refractive boundary and a participating media on the interior. If the material has a low opacity, single scattering effects dominate in its appearance. Refraction at the boundary concentrates the incoming light, resulting in an important phenomenon called volume caustics. This phenomenon is hard to simulate. Previous methods used point-based light transport, but attributed point samples inefficiently, resulting in long computation time. In this paper, we use frequency analysis of light transport to allocate point samples efficiently. Our method works in two steps: in the first step, we compute volume samples along with their covariance matrices, encoding the illumination frequency content in a compact way. In the rendering step, we use the covariance matrices to compute the kernel size for each volume sample: small kernel for high-frequency single scattering, large kernel for lower frequencies. Our algorithm computes volume caustics with fewer volume samples, with no loss of quality. Our method is both faster and uses less memory than the original method. It is roughly twice as fast and uses one fifth of the memory. The extra cost of computing covariance matrices for frequency information is negligible.

Keywords:
Computation Kernel (algebra) Covariance Computer science Scattering Opacity Algorithm Rendering (computer graphics) Optics Mathematics Physics Computer vision Statistics

Metrics

5
Cited By
3.01
FWCI (Field Weighted Citation Impact)
15
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Computer Graphics and Visualization Techniques
Physical Sciences →  Computer Science →  Computer Graphics and Computer-Aided Design
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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