Abstract
The current underwater image formation model descends from atmospheric dehazing equations where attenuation is a weak function of wavelength. We recently showed that this model introduces significant errors and dependencies in the estimation of the direct transmission signal because underwater, light attenuates in a wavelength-dependent manner. Here, we show that the backscattered signal derived from the current model also suffers from dependencies that were previously unaccounted for. In doing so, we use oceanographic measurements to derive the physically valid space of backscatter, and further show that the wideband coefficients that govern backscatter are different than those that govern direct transmission, even though the current model treats them to be the same. We propose a revised equation for underwater image formation that takes these differences into account, and validate it through in situ experiments underwater. This revised model might explain frequent instabilities of current underwater color reconstruction models, and calls for the development of new methods.
Original language | English |
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Title of host publication | Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 |
Publisher | IEEE Computer Society |
Pages | 6723-6732 |
Number of pages | 10 |
ISBN (Electronic) | 9781538664209 |
DOIs | |
State | Published - 14 Dec 2018 |
Event | 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 - Salt Lake City, United States Duration: 18 Jun 2018 → 22 Jun 2018 |
Publication series
Name | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
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ISSN (Print) | 1063-6919 |
Conference
Conference | 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 |
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Country/Territory | United States |
City | Salt Lake City |
Period | 18/06/18 → 22/06/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition