Underwater Image Enhancement Algorithm Based on Blue-green Channel Color Compensation

ZHOU Jingchun; WEI Xiaojing; SHI Jinyu

doi:10.11999/JEIT211444

Volume 44 Issue 8

Aug. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(8): 2932-2939

ZHOU Jingchun, WEI Xiaojing, SHI Jinyu. Underwater Image Enhancement Algorithm Based on Blue-green Channel Color Compensation[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2932-2939. doi: 10.11999/JEIT211444

Citation:

ZHOU Jingchun, WEI Xiaojing, SHI Jinyu. Underwater Image Enhancement Algorithm Based on Blue-green Channel Color Compensation[J]. Journal of Electronics & Information Technology, 2022, 44(8): 2932-2939. doi: 10.11999/JEIT211444

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Underwater Image Enhancement Algorithm Based on Blue-green Channel Color Compensation

doi: 10.11999/JEIT211444 cstr: 32379.14.JEIT211444

Institute of Information Science and Technology, Dalian Maritime University, Dalian 116000, China

Funds: The Foundational Research Foundation for the Central University (3132019354)

Received Date: 2021-12-06
Rev Recd Date: 2022-03-01

Available Online: 2022-04-11

Publish Date: 2022-08-17

Abstract

Abstract

When light travels in water, it is absorbed by water and scattered by particles, resulting in color distortion, low quality, and poor visibility of underwater images. To solve this problem, an underwater image enhancement method is proposed based on blue-green channel color compensation. First, the characteristics of the underwater imaging model is analyzed, and the depth of the underwater scene is classified according to the proportion of the mean value of the blue and green channels in the sum of the mean value of the three channels, the light attenuation rate characteristic is used to adaptively compensate the color, and multi-scene color correction is realized. Then the color-compensated image is divided into four regions: dark tone, mid-dark tone, mid-bright tone, and bright tone. The dark region of the image is mapped to the bright region using the dark region mapping function, which improves the contrast while suppressing the generation of noise. Finally, bilinear interpolation is used to solve the regional effect of block processing. Experimental results on real underwater datasets show that compared with existing methods, this method can improve low-quality underwater images in a variety of scenes.
- Underwater image,
- Underwater imaging model,
- Blue-green channel,
- Color compensation

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References(21)

References

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