Single image haze removal using dark channel prior
Abstract
In this paper, we propose a simple but effective image prior-dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of outdoor haze-free images. It is based on a key observation-most local patches in outdoor haze-free images contain some pixels whose intensity is very low in at least one color channel. Using this prior with the haze imaging model, we can directly estimate the thickness of the haze and recover a high-quality haze-free image. Results on a variety of hazy images demonstrate the power of the proposed prior. Moreover, a high-quality depth map can also be obtained as a byproduct of haze removal.
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Recovering the clear image from a single hazy input is an ill-posed problem that can be addressed by both prior-based and learning-based methods.
“Recovering the clear image from a single hazy input is also an illposed problem, which can be addressed by both prior-based and learning-based methods [149], [150], [151].”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [149]
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- Authors
- He, K., Sun, J., & Tang, X.
- Affiliations
- Chinese University of Hong Kong (HK)
- Microsoft Research Asia (China) (CN)
- ORCID
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2011-12
- Volume
- 33
- Issue
- 12
- Pages
- 2341-2353
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2128254161
- Cited by
- 7,601
- References
- 25
- Citations by year
- 2026: 495 · 2025: 845 · 2024: 913 · 2023: 865 · 2022: 801 · 2021: 737 · 2020: 626 · 2019: 519 · 2018: 471 · 2017: 359 · 2016: 278 · 2015: 244 · 2014: 171 · 2013: 121 · 2012: 61
- FWCI
- 99.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Engineering › Media Technology › Image Processing Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
- Keywords
- single image dehazing, dark channel prior, image dehazing, depth map estimation, image priors
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