Underwater Image Enhancement Method Based on Illumination Compensation and Pyramid-Based Blending

YUE Chenghai; XU Huixi; LÜ Fengtian; SHAO Gang; ZHU Baotong; YIN Zhongxun

doi:10.11993/j.issn.2096-3920.2024-0082

Volume 33 Issue 1

Mar 2025

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Article Navigation > Journal of Unmanned Undersea Systems > 2025 > 33(1): 46-55

YUE Chenghai, XU Huixi, LÜ Fengtian, SHAO Gang, ZHU Baotong, YIN Zhongxun. Underwater Image Enhancement Method Based on Illumination Compensation and Pyramid-Based Blending[J]. Journal of Unmanned Undersea Systems, 2025, 33(1): 46-55. doi: 10.11993/j.issn.2096-3920.2024-0082

Citation:

YUE Chenghai, XU Huixi, LÜ Fengtian, SHAO Gang, ZHU Baotong, YIN Zhongxun. Underwater Image Enhancement Method Based on Illumination Compensation and Pyramid-Based Blending[J]. Journal of Unmanned Undersea Systems, 2025, 33(1): 46-55. doi: 10.11993/j.issn.2096-3920.2024-0082

Citation:

YUE Chenghai, XU Huixi, LÜ Fengtian, SHAO Gang, ZHU Baotong, YIN Zhongxun. Underwater Image Enhancement Method Based on Illumination Compensation and Pyramid-Based Blending[J]. Journal of Unmanned Undersea Systems, 2025, 33(1): 46-55. doi: 10.11993/j.issn.2096-3920.2024-0082

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Underwater Image Enhancement Method Based on Illumination Compensation and Pyramid-Based Blending

doi: 10.11993/j.issn.2096-3920.2024-0082

YUE Chenghai^{1, 2
,},
XU Huixi^{1, 2
,},
LÜ Fengtian^{1, 2
,},
SHAO Gang^{1, 2
,},
ZHU Baotong^{1, 2
,},
YIN Zhongxun^{1, 2
,}

1.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.
Key Laboratory of Marine Robotics, Liaoning Province, Shenyang 110169, China

Received Date: 2024-05-20
Accepted Date: 2024-07-02
Rev Recd Date: 2024-07-01

Available Online: 2025-01-16

Abstract

Abstract

The existing enhancement methods based on deep learning and underwater imaging quality degradation models still suffer from poor robustness due to color deviation, scattering-induced blur, and uneven brightness in underwater optical imaging. In response to these issues, this article proposed a single image-based enhancement method for underwater imaging, which combined illumination compensation and pyramid-based detail blending. First, based on global illumination and color channel characteristics, illumination intensity at the pixel level was estimated and compensated, achieving intensity correction for each color channel. Next, the scatter components of the image were estimated using Gaussian blur, and a multi-scale Gaussian filter residual method was used for descattering. Finally, a multi-image pyramid-based detail blending technique was proposed, combining edge enhancement, adaptive Gamma correction, and brightness equalization. This method effectively preserved image details while addressing uneven brightness. Compared to existing techniques, this method featured improved adaptability and achieved better performance in underwater image quality measures(UIQMs) and underwater image color and quality evaluation(UCIQE) measures.
- underwater image enhancement,
- illumination compensation,
- pyramid-based blending,
- brightness equalization,
- deep learning

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References(24)

References

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