Underwater Image Dehazing Method Based on Image Layering

In the single-image dehazing method based on the underwater imaging model, the accurate estimation and separation of background scattered light has consistently been a core challenge. Degraded underwater images restrict their use in high-level visual applications such as target segmentation, image recognition, and scene reconstruction. Therefore, studying methods for reconstructing target objects in underwater environments is crucial for improving the clarity and contrast of detection images. This paper introduces an image-layering method that integrates with a physical model and estimates Scattering light using only mean filtering. The algorithm is simple and effective, making it suitable for real-time computation. Experimental results demonstrate that, in comparison with other algorithms, the results offer excellent visibility.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/iccea65460.2025.11103241
Primary Topic
Image Enhancement Techniques
Type
article
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article

Underwater Image Dehazing Method Based on Image Layering

Haihong Jin, Junjie Ji, Haowei Yao, Wenjie Zhang et al.
Image Enhancement Techniques
article

Underwater Image Dehazing Method Based on Image Layering

Haihong Jin, Junjie Ji, Haowei Yao, Wenjie Zhang, Ming Zhang, S. Yao
article en

Abstract

In the single-image dehazing method based on the underwater imaging model, the accurate estimation and separation of background scattered light has consistently been a core challenge. Degraded underwater images restrict their use in high-level visual applications such as target segmentation, image recognition, and scene reconstruction. Therefore, studying methods for reconstructing target objects in underwater environments is crucial for improving the clarity and contrast of detection images. This paper introduces an image-layering method that integrates with a physical model and estimates Scattering light using only mean filtering. The algorithm is simple and effective, making it suitable for real-time computation. Experimental results demonstrate that, in comparison with other algorithms, the results offer excellent visibility.

Changchun University of Science and Technology (CN), Anhui Jianzhu University (CN)
Openalex Percentile: Top 81%
Image Enhancement Techniques
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Underwater Image Dehazing Method Based on Image Layering — Haihong Jin, Junjie Ji, et al. · (2025) | TGRS Research Map | TGRS