Abstract
The color of an object imaged in a turbid medium varies with distance and medium properties, deeming color an unstable source of information. Assuming 3D scene structure has become relatively easy to estimate, the main challenge in color recovery is calibrating medium properties in situ, at the time of acquisition. Existing attenuation calibration methods use either color charts, external hardware, or multiple images of an object. Here we show none of these is needed for calibration. We suggest a method for estimating the medium properties (both attenuation and scattering) using only images of backscattered light from the system's light sources. This is advantageous in turbid media where the object signal is noisy, and also alleviates the need for correspondence matching, which can be difficult in high turbidity. We demonstrate the advantages of our method through simulations and in a real-life experiment at sea.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Computational Photography, ICCP 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509057450 |
DOIs | |
State | Published - 16 Jun 2017 |
Event | 2017 IEEE International Conference on Computational Photography, ICCP 2017 - Stanford, United States Duration: 12 May 2017 → 14 May 2017 |
Publication series
Name | 2017 IEEE International Conference on Computational Photography, ICCP 2017 - Proceedings |
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Conference
Conference | 2017 IEEE International Conference on Computational Photography, ICCP 2017 |
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Country/Territory | United States |
City | Stanford |
Period | 12/05/17 → 14/05/17 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
ASJC Scopus subject areas
- Instrumentation
- Atomic and Molecular Physics, and Optics
- Computational Theory and Mathematics
- Computer Vision and Pattern Recognition