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Robotics 2018, 7(1), 14; https://doi.org/10.3390/robotics7010014

An Underwater Image Enhancement Algorithm for Environment Recognition and Robot Navigation

Fujian Key Laboratory of Brain-inspired Computing Technique and Applications, School of Information Science and Engineering, Xiamen University, Xiamen 361005, China
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Received: 18 November 2017 / Revised: 1 March 2018 / Accepted: 6 March 2018 / Published: 13 March 2018
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Abstract

There are many tasks that require clear and easily recognizable images in the field of underwater robotics and marine science, such as underwater target detection and identification of robot navigation and obstacle avoidance. However, water turbidity makes the underwater image quality too low to recognize. This paper proposes the use of the dark channel prior model for underwater environment recognition, in which underwater reflection models are used to obtain enhanced images. The proposed approach achieves very good performance and multi-scene robustness by combining the dark channel prior model with the underwater diffuse model. The experimental results are given to show the effectiveness of the dark channel prior model in underwater scenarios. View Full-Text
Keywords: dark channel prior; underwater reflection models; underwater environment recognition; Image enhancement dark channel prior; underwater reflection models; underwater environment recognition; Image enhancement
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Xie, K.; Pan, W.; Xu, S. An Underwater Image Enhancement Algorithm for Environment Recognition and Robot Navigation. Robotics 2018, 7, 14.

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