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2022年 第17卷 第3期

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《机械工程前沿（英文）》 >> 2022年 第17卷 第3期 doi: 10.1007/s11465-021-0669-8

Turbidity-adaptive underwater image enhancement method using image fusion

1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;2. Guangdong Intelligent Robotics Institute, Dongguan 523808, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;1. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

收稿日期： 2021-08-08 发布日期： 2021-08-08
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摘要

Clear, correct imaging is a prerequisite for underwater operations. In real freshwater environment including rivers and lakes, the water bodies are usually turbid and dynamic, which brings extra troubles to quality of imaging due to color deviation and suspended particulate. Most of the existing underwater imaging methods focus on relatively clear underwater environment, it is uncertain that if those methods can work well in turbid and dynamic underwater environments. In this paper, we propose a turbidity-adaptive underwater image enhancement method. To deal with attenuation and scattering of varying degree, the turbidity is detected by the histogram of images. Based on the detection result, different image enhancement strategies are designed to deal with the problem of color deviation and blurring. The proposed method is verified by an underwater image dataset captured in real underwater environment. The result is evaluated by image metrics including structure similarity index measure, underwater color image quality evaluation metric, and speeded-up robust features. Test results exhibit that the method can correct the color deviation and improve the quality of underwater images.

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