A PDE-Based Image Dehazing Method via Atmospheric Scattering Theory
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908588561137664 |
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| author | Hu, Liubing Wang, Pu Gao, Guangwei Wang, Chunyan Zheng, Zhuoran |
| author_facet | Hu, Liubing Wang, Pu Gao, Guangwei Wang, Chunyan Zheng, Zhuoran |
| contents | This paper introduces a novel partial differential equation (PDE) framework for single-image dehazing. We embed the atmospheric scattering model into a PDE featuring edge-preserving diffusion and a nonlocal operator to maintain both local details and global structures. A key innovation is an adaptive regularization mechanism guided by the dark channel prior, which adjusts smoothing strength based on haze density. The framework's mathematical well-posedness is rigorously established by proving the existence and uniqueness of its weak solution in $H_0^1(Ω)$. An efficient, GPU-accelerated fixed-point solver is used for implementation. Experiments confirm our method achieves effective haze removal while preserving high image fidelity, offering a principled alternative to purely data-driven techniques. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_08793 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A PDE-Based Image Dehazing Method via Atmospheric Scattering Theory Hu, Liubing Wang, Pu Gao, Guangwei Wang, Chunyan Zheng, Zhuoran Computer Vision and Pattern Recognition Image and Video Processing This paper introduces a novel partial differential equation (PDE) framework for single-image dehazing. We embed the atmospheric scattering model into a PDE featuring edge-preserving diffusion and a nonlocal operator to maintain both local details and global structures. A key innovation is an adaptive regularization mechanism guided by the dark channel prior, which adjusts smoothing strength based on haze density. The framework's mathematical well-posedness is rigorously established by proving the existence and uniqueness of its weak solution in $H_0^1(Ω)$. An efficient, GPU-accelerated fixed-point solver is used for implementation. Experiments confirm our method achieves effective haze removal while preserving high image fidelity, offering a principled alternative to purely data-driven techniques. |
| title | A PDE-Based Image Dehazing Method via Atmospheric Scattering Theory |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2506.08793 |