Data compression for measured heterogeneous subsurface scattering via scattering profile blending

Tatsuya Yatagawa*, Hideki Todo, Yasushi Yamaguchi, Shigeo Morishima

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Subsurface scattering involves the complicated behavior of light beneath the surfaces of translucent objects that includes scattering and absorption inside the object’s volume. Physically accurate numerical representation of subsurface scattering requires a large number of parameters because of the complex nature of this phenomenon. The large amount of data restricts the use of the data on memory-limited devices such as video game consoles and mobile phones. To address this problem, this paper proposes an efficient data compression method for heterogeneous subsurface scattering. The key insight of this study is that heterogeneous materials often comprise a limited number of base materials, and the size of the subsurface scattering data can be significantly reduced by parameterizing only a few base materials. In the proposed compression method, we represent the scattering property of a base material using a function referred to as the base scattering profile. A small subset of the base materials is assigned to each surface position, and the local scattering property near the position is described using a linear combination of the base scattering profiles in the log scale. The proposed method reduces the data by a factor of approximately 30 compared to a state-of-the-art method, without significant loss of visual quality in the rendered graphics. In addition, the compressed data can also be used as bidirectional scattering surface reflectance distribution functions (BSSRDF) without incurring much computational overhead. These practical aspects of the proposed method also facilitate the use of higher-resolution BSSRDFs in devices with large memory capacity.

Original languageEnglish
Pages (from-to)541-558
Number of pages18
JournalVisual Computer
Volume36
Issue number3
DOIs
Publication statusPublished - 2020 Mar 1

Keywords

  • BSSRDF
  • Data compression
  • Mobiles
  • Subsurface scattering

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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