Beyond Mie Theory: Systematic Computation of Bulk Scattering Parameters based on Microphysical Wave Optics
Yu Guo1, Adrian Jarabo2, and Shuang Zhao1
1University of California, Irvine        2Universidad de Zaragoza - I3A
ACM Transactions on Graphics (SIGGRAPH Asia 2021), 40(6), 2021
teaser
Abstract

Light scattering in participating media and translucent materials is typically modeled using the radiative transfer theory. Under the assumption of independent scattering between particles, it utilizes several bulk scattering parameters to statistically characterize light-matter interactions at the macroscale. To calculate these parameters based on microscale material properties, the Lorenz-Mie theory has been considered the gold standard. In this paper, we present a generalized framework capable of systematically and rigorously computing bulk scattering parameters beyond the far-field assumption of Lorenz-Mie theory. Our technique accounts for microscale wave-optics effects such as diffraction and interference as well as interactions between nearby particles. Our framework is general, can be plugged in any renderer supporting Lorenz-Mie scattering, and allows arbitrary packing rates and particles correlation; we demonstrate this generality by computing bulk scattering parameters for a wide range of materials, including anisotropic and correlated media.

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Bibtex citation
@article{Guo:2021:Beyond_Mie,
  title={Beyond Mie Theory: Systematic Computation of Bulk Scattering Parameters based on Microphysical Wave Optics},
  author={Guo, Yu and Jarabo, Adrian and Zhao, Shuang},
  journal={ACM Trans. Graph.},
  volume={40},
  number={6},
  year={2021},
  pages={284:1--284:12}
}
Acknowledgments

We thank the anonymous reviewers for their comments and suggestions. Yu and Shuang are partially supported by NSF grant 1813553. Adrian is partially supported by the European Research Council (ERC) under the EU Horizon 2020 research and innovation programme (project CHAMELEON, grant No 682080), the EU MSCA-ITN programme (project PRIME, grant No 956585) and the Spanish Ministry of Science and Innovation (project PID2019-105004GB-I00).