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Reseach Article

A Critical Study and Comparative Analysis of Various Haze Removal Techniques

by Dilraj Kaur, Pooja
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 16
Year of Publication: 2015
Authors: Dilraj Kaur, Pooja
10.5120/21623-4916

Dilraj Kaur, Pooja . A Critical Study and Comparative Analysis of Various Haze Removal Techniques. International Journal of Computer Applications. 121, 16 ( July 2015), 9-14. DOI=10.5120/21623-4916

@article{ 10.5120/21623-4916,
author = { Dilraj Kaur, Pooja },
title = { A Critical Study and Comparative Analysis of Various Haze Removal Techniques },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 16 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number16/21623-4916/ },
doi = { 10.5120/21623-4916 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:08:36.239093+05:30
%A Dilraj Kaur
%A Pooja
%T A Critical Study and Comparative Analysis of Various Haze Removal Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 16
%P 9-14
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fog is just a combination of two parts airlight and direct attenuation; it reduces the image quality and produces big quantity of problems in video monitoring, monitoring and navigation. Therefore, to eliminate it from an image, several defogging methods have been planned in literature. Defogging may be performed applying different photos and single image haze treatment strategy. That paper presents a review on the different haze treatment methods. These methods are generally utilized in several programs for instance outdoor monitoring, subject detection, electronic devices etc. The overall objective with this paper has gone to investigate the different practices for efficiently eliminating the haze from digital images. It's been explored that nearly all the prevailing researchers have neglected several dilemmas; i. e. no approach is exact for various kind of circumstances.

References
  1. Xu, Zhiyuan, Xiaoming Liu, and Na Ji. "Fog removal from color images using contrast limited adaptive histogram equalization. " In Image and Signal Processing, 2009. CISP'09. 2nd International Congress on, pp. 1-5. IEEE, 2009.
  2. Tripathi, A. K. , and S. Mukhopadhyay. "Single image fog removal using bilateral filter. " In Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on, pp. 1-6. IEEE, 2012.
  3. Wang, Yan, and Bo Wu. "Improved single image dehazing using dark channel prior. " Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on. Vol. 2. IEEE, 2010.
  4. Yu, Jing, and Qingmin Liao. "Fast single image fog removal using edge-preserving smoothing. " Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on. IEEE, 2011.
  5. Shuai, Yanjuan, Rui Liu, and Wenzhang He. "Image Haze Removal of Wiener Filtering Based on Dark Channel Prior. " Computational Intelligence and Security (CIS), 2012 Eighth International Conference on. IEEE, 2012.
  6. Cheng, F-C. , C-H. Lin, and J-L. Lin. "Constant time O (1) image fog removal using lowest level channel. " Electronics Letters 48. 22 (2012): 1404-1406.
  7. Xu, Haoran, et al. "Fast image dehazing using improved dark channel prior. " Information Science and Technology (ICIST), 2012 International Conference on. IEEE, 2012.
  8. Sahu, Jyoti. "Design a New Methodology for Removing Fog from the Image. " International Journal 2 (2012).
  9. Matlin, Erik, and PeymanMilanfar. "Removal of haze and noise from a single image. " IS&T/SPIE Electronic Imaging. International Society for Optics and Photonics, 2012.
  10. Kang, Li-Wei, Chia-Wen Lin, and Yu-Hsiang Fu. "Automatic single-image-based rain streaks removal via image decomposition. " Image Processing, IEEE Transactions on 21. 4 (2012): 1742-1755.
  11. Yuk, Jacky Shun-Cho, and Kwan-Yee Kenneth Wong. "Adaptive background defogging with foreground decremental preconditioned conjugate gradient. " Computer Vision–ACCV 2012. Springer Berlin Heidelberg, 2013. 602-614.
  12. Hitam, M. S. , W. N. J. H. W. Yussof, E. A. Awalludin, and Z. Bachok. "Mixture contrast limited adaptive histogram equalization for underwater image enhancement. " In Computer Applications Technology (ICCAT), 2013 International Conference on, pp. 1-5. IEEE, 2013.
  13. Chu C. T. , Lee M . S. "A Content-Adaptive method for Single Image dehazing"
  14. Xu, Zhiyuan, Xiaoming Liu, and Xiaonan Chen,"Fog removal from video sequences using contrast limited adaptive histogram equalization", Computational Intelligence and Software Engineering, 2009 International Conference on. IEEE, 2009
  15. Desai, Nachiket, Chatterjee Aritra, Mishra Shaunak and Choudary Sunam, "A Fuzzy Logic Based Approach to De-Weather Fog-Degraded Images", Computer Graphics, Imaging and Visualization, 2009 Sixth International Conference on. IEEE, 2009.
  16. Yu, Jing, Chuangbai Xiao, and Dapeng Li, "Physics-based fast single image fog removal", Signal Processing (ICSP), 2010 IEEE 10th International Conference on. IEEE, 2010.
  17. Guo, Fan, Cai Zixing, Xie Bin and Tang Zin, "Automatic Image Haze Removal Based on Luminance Component", Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on. IEEE, 2010.
  18. Chu, Chao-Tsung, and Ming-Sui Lee, "A content-adaptive method for single image dehazing", Proceedings of the Advances in multimedia information processing and 11th Pacific Rim conference on Multimedia, Springer-Verlag, 2010.
  19. Xu, Zhiyuan, and Xiaoming Liu, "Bilinear interpolation dynamic histogram equalization for fog-degraded image enhancement", J Inf Comput Sci 7. 8 (2010) 1727-1732.
  20. Yu, Jing, and Qingmin Liao, "Fast single image fog removal using edge-preserving smoothing", Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on. IEEE, 2011.
  21. Huang, Darong, Zhou Fang, Ling Zhao, and Xiaoyan Chu. "An improved image clearness algorithm based on dark channel prior. " In Control Conference (CCC), 2014 33rd Chinese, pp. 7350-7355. IEEE, 2014.
  22. Ghani, Ahmad Shahrizan Abdul, and Nor Ashidi Mat Isa. "Underwater image quality enhancement through integrated color model with Rayleigh distribution. "Applied Soft Computing 27 (2015): 219-230.
  23. Wang, Jin-Bao, Ning He, Lu-Lu Zhang, and Ke Lu. "Single image dehazing with a physical model and dark channel prior. " Neurocomputing 149 (2015): 718-728.
Index Terms

Computer Science
Information Sciences

Keywords

Visibility Restoration Fog Removal Dark Channel Prior.