Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network
Joint Authors
Zheng, Haiyong
Yu, Zhibin
Wang, Yubo
Zheng, Bing
Wang, Nan
Gu, Zhaorui
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-15
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision.
Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods.
But these methods are inflexible and expensive to be deployed.
To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network.
The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology.
However, image-based IOPs estimation is a quite different and challenging task.
Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously.
In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy.
The imaging depth information is considered as an aided input to help our model make better decision.
American Psychological Association (APA)
Yu, Zhibin& Wang, Yubo& Zheng, Bing& Zheng, Haiyong& Wang, Nan& Gu, Zhaorui. 2017. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141157
Modern Language Association (MLA)
Yu, Zhibin…[et al.]. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1141157
American Medical Association (AMA)
Yu, Zhibin& Wang, Yubo& Zheng, Bing& Zheng, Haiyong& Wang, Nan& Gu, Zhaorui. Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141157
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141157