The DOI matches its Crossref record.
Mixture contrast limited adaptive histogram equalization for underwater image enhancement
Abstract
Within the last decades, improving the quality of an underwater image has received considerable attention due to poor visibility of the image which is caused by physical properties of the water medium. This paper presents a new method called mixture Contrast Limited Adaptive Histogram Equalization (CLAHE) color models that specifically developed for underwater image enhancement. The method operates CLAHE on RGB and HSV color models and both results are combined together using Euclidean norm. The underwater images used in this study were taken from Redang Island and Bidong Island in Terengganu, Malaysia. Experimental results show that the proposed approach significantly improves the visual quality of underwater images by enhancing contrast, as well as reducing noise and artifacts.
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“However, these algorithms do not consider the spatial variance of the degradation over the field of view [3,4,5,6].”
From Underwater Optical-Sonar Image Fusion Systems (2022) · cites this paper as [4]
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Cites
No references could be resolved yet.
Research works printed but not linked: 7
- abril, 2005, Color correction of underwater images for aquatic robot inspection, LNCS, 3757, 60
- aysun, 0, Visual enhancement of underwater images using empirical mode decomposition, Expert Systems with Applications, 39, 800
- 10.1364/OPEX.13.008766 · DOI
- 10.1007/BF03178082 · DOI
- zuiderveld, 1994, Contrast Limited Adaptive Histogram Equalization Graphics Gems IV
- 10.1016/S0734-189X(87)80186-X · DOI
- garg, 2011, Histogram equalization techniques for image enhancement, International Journal of Electronics and Communication Technology, 2, 107
Cited by
Sorted by citations
Underwater Optical-Sonar Image Fusion Systems
Kim, H.-G., Seo, J., & Kim, S. M. (2022) · Sensors · doi:10.3390/s22218445 · Cited by 29
“CLAHE-mix [4] Apply CLAHE on the image in RGB and HSV color models and combine two contrast-enhanced images by Euclidean norm”
Method
Metadata
- Authors
- Hitam, M. S., Yussof, W. N. J. H. W., Awalludin, E. A., & Bachok, Z.
- Affiliations
- Universiti Malaysia Terengganu (MY)
- Venue
- 2013 International Conference on Computer Applications Technology (ICCAT)
- Publisher
- IEEE
- Published
- 2013-01
- Pages
- 1-5
- OpenAlex
- W2094185466
- Cited by
- 484
- References
- 0
- Citations by year
- 2026: 31 · 2025: 67 · 2024: 72 · 2023: 58 · 2022: 35 · 2021: 29 · 2020: 48 · 2019: 29 · 2018: 32 · 2017: 37 · 2016: 14 · 2015: 22 · 2014: 10
- FWCI
- 9.79
- Type
- conference paper
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Keywords
- underwater image enhancement, CLAHE, color models, RGB color model, HSV color space, image contrast enhancement, noise reduction, artifact reduction
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- CoChat. (2026). Citation check: Mixture contrast limited adaptive histogram equalization for underwater image enhancement. https://app.cochat.ai/papers/10.1109/iccat.2013.6522017
- The paper
- Hitam, M. S., Yussof, W. N. J. H. W., Awalludin, E. A., & Bachok, Z. (2013). Mixture contrast limited adaptive histogram equalization for underwater image enhancement. 2013 International Conference on Computer Applications Technology (ICCAT). https://doi.org/10.1109/iccat.2013.6522017
