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| Underwater Image Visibility Restoration Based on Underwater Imaging Model |
| YANG Aiping① QU Chang① WANG Jian①② ZHANG Liyun① |
①(School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)
②(National Ocean Technology Center, Tianjin 300112, China) |
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Abstract As a result of the existence of organisms and suspended particles under underwater conditions, images captured under water usually have low contrast, color distortion and loss of visibility. At the same time, due to the existence of the artificial light source, the underwater image usually has the non-uniform illumination. Traditional hazy-removal methods perform poorly under water. In order to take both absorption and scattering into consideration, a new underwater image formation model and restoration methods are proposed recently. However, these methods ignore the great impact of the red channel information and artificial light source. To solve this problem, a new approach is proposed for underwater image visibility restoration. Firstly, a threshold is set to determine whether to use the red channel information to estimate the dark channel, and a saturation indicator which is used to indicate the impact of artificial light source is utilized to calculate the scattering rate. Based on the red channel information anticipation and the saturation indicator, a new method is proposed to estimate the dark channel. Then, the transmission of each channel is estimated according to the attenuation coefficient ratio, which makes the proposed method more robust. Finally, the ambient light is obtained using the Shades of Gray algorithm, and the visibility restoration result is achieved based on a new underwater image formation model. Experimental results demonstrate that the proposed algorithm can significantly improve the contrast of the underwater image with more natural color and better visibility.
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Received: 15 May 2017
Published: 04 December 2017
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| Fund:The National Natural Science Foundation of China (61372145, 61472274) |
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Corresponding Authors:
YANG Aiping
E-mail: yangaiping@tju.edu.cn
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