Rapid Deep-Sea Image Restoration Algorithm Applied to Unmanned Underwater Vehicles

被引：0
|
作者：
Guo W. [1 ,3 ]
Zhang Y. [1 ,2 ]
Zhou Y. [2 ]
Xu G. [1 ]
Li G. [1 ]
机构：
[1] Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Sanya
[2] College of Engineering Science and Technology, Shanghai Ocean University, Shanghai
[3] University of Chinese Academy of Sciences, Beijing
来源：
Guangxue Xuebao/Acta Optica Sinica | 2022年 / 42卷 / 04期
关键词：
Artificial light source; Deep-sea image; Depth of field model; Embedded image processor; Image processing; Image restoration;
D O I：
10.3788/AOS202242.0410002
中图分类号：
学科分类号：
摘要：
Due to the absorption of seawater and the scattering of suspended particles in water, the deep-sea image obtained by underwater robot through artificial light source is generally fuzzy, color deviation, and low resolution. Focusing on the key problems to be solved in the rapid and accurate restoration of deep-sea images, the data set of real deep-sea images is firstly established, and the imaging characteristics of deep-sea images are analyzed. Based on the statistical results of image features, a linear depth of field model is proposed. Then, the model parameters are identified by supervised method. Finally, according to the depth of field model, the transmission map and background light of the original image are estimated quickly, so as to effectively avoid cumulative error and achieve effective restoration of deep-sea images. Experimental results show that the proposed algorithm is superior to other algorithms in terms of image restoration results, validity, quality, and real-time performance. Processing 600 pixel×800 pixel image on Nvidia Jetson TX2 embedded device, the average restoration speed of the proposed algorithm is 3.08 times faster than the four outstanding underwater image enhancement algorithms. © 2022, Chinese Lasers Press. All right reserved.
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