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Visualizing Underwater Ocean Optics

Gutierrez, Diego, Seron, Francisco J., Munoz, Adolfo, Anson, Oscar·2008·Computer Graphics Forum

Abstract

Simulating the in‐water ocean light field is a daunting task. Ocean waters are one of the richest participating media, where light interacts not only with water molecules, but with suspended particles and organic matter as well. The concentration of each constituent greatly affects these interactions, resulting in very different hues. Inelastic scattering events such as fluorescence or Raman scattering imply energy transfers that are usually neglected in the simulations. Our contributions in this paper are a bio‐optical model of ocean waters suitable for computer graphics simulations, along with an improved method to obtain an accurate solution of the in‐water light field based on radiative transfer theory. The method provides a link between the inherent optical properties that define the medium and its apparent optical properties, which describe how it looks. The bio‐optical model of the ocean uses published data from oceanography studies. For inelastic scattering we compute all frequency changes at higher and lower energy values, based on the spectral quantum efficiency function of the medium. The results shown prove the usability of the system as a predictive rendering algorithm. Areas of application for this research span from underwater imagery to remote sensing; the resolution method is general enough to be usable in any type of participating medium simulation.

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Metadata

Authors
Gutierrez, D., Seron, F. J., Munoz, A., & Anson, O.
Venue
Computer Graphics Forum
Publisher
Wiley
Published
2008-04
Volume
27
Issue
2
Pages
547-556
ISSN
  • 0167-7055
  • 1467-8659
Cited by
21
References
0
Language
en

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CoChat. (2026). Citation check: Visualizing Underwater Ocean Optics. https://app.cochat.ai/papers/10.1111/j.1467-8659.2008.01152.x
The paper
Gutierrez, D., Seron, F. J., Munoz, A., & Anson, O. (2008). Visualizing Underwater Ocean Optics. Computer Graphics Forum. https://doi.org/10.1111/j.1467-8659.2008.01152.x

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.