Abstract
The appearance of underwater scenes is highly governed by the optical properties of the water (attenuation and scattering). However, most research effort in physics-based underwater image reconstruction methods is placed on devising image priors for estimating scene transmission, and less on estimating the optical properties. This limits the quality of the results. This work focuses on robust estimation of the water properties. First, as opposed to previous methods that used fixed values for attenuation, we estimate it from the color distribution in the image. Second, we estimate the veiling-light color from objects in the scene, contrary to looking at background pixels. We conduct an extensive qualitative and quantitative evaluation of our method vs. most recent methods on several datasets. As our estimation is more robust our method provides superior results including on challenging scenes.
Original language | English |
---|---|
Title of host publication | IEEE International Conference on Computational Photography, ICCP 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728152301 |
DOIs | |
State | Published - Apr 2020 |
Event | 2020 IEEE International Conference on Computational Photography, ICCP 2020 - Saint Louis, United States Duration: 24 Apr 2020 → 26 Apr 2020 |
Publication series
Name | IEEE International Conference on Computational Photography, ICCP 2020 |
---|
Conference
Conference | 2020 IEEE International Conference on Computational Photography, ICCP 2020 |
---|---|
Country/Territory | United States |
City | Saint Louis |
Period | 24/04/20 → 26/04/20 |
Bibliographical note
Funding Information:TT was supported by the The Leona M. and Harry B. Helmsley Charitable Trust, The Maurice Hatter Foundation, Israel Science Foundation grant 680/18, and the Technion Ollendorff Minerva Center for Vision and Image Sciences. This work was also partly funded by ISF grant number 1549/19.
Publisher Copyright:
© 2020 IEEE.
Keywords
- Computational Photography
- Image Color Analysis
- Image Restoration
ASJC Scopus subject areas
- Computer Science Applications
- Signal Processing
- Media Technology
- Instrumentation