Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICCP48838.2020.9105267 | 2020 IEEE International Conference on Computational Photography (ICCP) |
Keywords | DocType | ISSN |
Computational Photography,Image Restoration,Image Color Analysis | Conference | 2164-9774 |
ISBN | Citations | PageRank |
978-1-7281-5231-8 | 0 | 0.34 |
References | Authors | |
17 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yael Bekerman | 1 | 0 | 0.34 |
| Shai Avidan | 2 | 3291 | 208.12 |
| Tali Treibitz | 3 | 178 | 13.09 |