Two pictures of a coral reef, showcasing the instability of traditional tone-mapping methods compared to our method highlighting significant improvements in color consistency.

Optimizing Temporal Stability in Underwater Video Tone Mapping

Proc. Vision, Modeling and Visualization (VMV), 2023

Matthias Franz Technische UniversitätBraunschweig
Bill Matthias Thang Technische UniversitätBraunschweig
Pascal Sackhoff Technische UniversitätBraunschweig
Timon Scholz Computer Graphics Lab TU Braunschweig
Jannis Malte Möller Computer Graphics Lab TU Braunschweig
Steve Grogorick Computer Graphics Lab TU Braunschweig
Martin Eisemann Computer Graphics Lab TU Braunschweig

Abstract

In this paper, we present an approach for temporal stabilization of depth-based underwater image tone mapping methods for application to monocular RGB video. Typically, the goal is to improve the colors of focused objects, while leaving more distant regions nearly unchanged, to preserve the underwater look-and-feel of the overall image. To do this, many methods rely on estimated depth to control the recolorization process, i.e., to enhance colors (reduce blue tint) only for objects close to the camera. However, while single-view depth estimation is usually consistent within a frame, it often suffers from inconsistencies across sequential frames, resulting in color fluctuations during tone mapping. We propose a simple yet effective inter-frame stabilization of the computed depth maps to achieve stable tone mapping results. The evaluation of eight test sequences shows the effectiveness in a wide range of underwater scenarios.

Citation

@inproceedings{moller2023optimizing,
  title = {Optimizing Temporal Stability in Underwater Video Tone Mapping},
  author = {Franz, Matthias and Thang, Bill Matthias and Sackhoff, Pascal and Scholz, Timon and M{\"o}ller, Jannis Malte and Grogorick, Steve and Eisemann, Martin},
  booktitle = {Proc. Vision, Modeling and Visualization ({VMV})},
  organization = {Eurographics},
  isbn = {978-3-03868-232-5},
  doi = {10.2312/vmv.20231239},
  editor = {T. Grosch and M. Guthe},
  pages = {165--172},
  month = {Sep},
  year = {2023}
}
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Acknowledgements

Partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 491805996 and by the Lower Saxony Ministry of Science and Culture under grant number ZN3994 within the Lower Saxony “Vorab“ of the Volkswagen Foundation and supported by the Center for Digital Innovations (ZDIN).

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