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Air Light Estimation Algorithm by using Fuzzy based Dark Channel Prior

by Simranjit Kaur, S. A. Khan, Rajwant Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 24
Year of Publication: 2018
Authors: Simranjit Kaur, S. A. Khan, Rajwant Kaur
10.5120/ijca2018918019

Simranjit Kaur, S. A. Khan, Rajwant Kaur . Air Light Estimation Algorithm by using Fuzzy based Dark Channel Prior. International Journal of Computer Applications. 182, 24 ( Oct 2018), 14-20. DOI=10.5120/ijca2018918019

@article{ 10.5120/ijca2018918019,
author = { Simranjit Kaur, S. A. Khan, Rajwant Kaur },
title = { Air Light Estimation Algorithm by using Fuzzy based Dark Channel Prior },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 182 },
number = { 24 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 14-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number24/30080-2018918019/ },
doi = { 10.5120/ijca2018918019 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:19.816428+05:30
%A Simranjit Kaur
%A S. A. Khan
%A Rajwant Kaur
%T Air Light Estimation Algorithm by using Fuzzy based Dark Channel Prior
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 24
%P 14-20
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The unwanted environmental circumstances decrease the visibility and hidden information of theremotely sensed images. Since visibility is a significant quality issue in these images, thus, visibilityimprovement methods are necessary for improving the significant details of remotely sensed images. Thispaper has proposed a novel technique for improving the visibility of outdoor images. Theproposed method produces efficient results by using fuzzy filter based dark channel prior. The fuzzy filter can automatically extract the local atmospheric light and roughly eliminate theatmospheric veil in local detail enhancement. The proposed technique is designed and implemented usingin MATLAB with the help of image processing toolbox. The qualitative results have clearly show that theproposed image enhancement technique can preserve significant detail of the original image.

References
  1. Wei, Sun, and Han Long,"A New Fast Single-Image Defog Algorithm", Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on. IEEE, 2013
  2. Tripathi A.K and S. Mukhopadhyay,"Single image fog removal using bilateral filter", Signal Processing, Computing and Control (ISPCC), 2012International Conference on. IEEE, 2012
  3. Nishino, Ko, Louis Kratz, and Stephen Lombardi, "Bayesian defogging", International journal of computer vision , pp 263-278, 2012.
  4. Xu Haoran, Guo Jianming, Liu Xing and Ye Lingli, "Fast image dehazing using improved dark channel prior",Information Science and Technology (ICIST), 2012 International Conference on. IEEE, 2012.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. Wang, Yan, and Bo Wu, "Improved single image dehazing using dark channel prior", Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on. IEEE, 2010.
  10. Xu, Zhiyuan, and Xiaoming Liu, "Bilinear interpolation dynamic histogram equalization for fog-degraded image enhancement",  J Inf Comput Sci 7.8 (2010) 1727-1732.
  11. Wolfe, Christopher, T. C. Graham and Joseph A. Pape, "Seeing through the fog: an algorithm for fast and accurate touch detection in optical tabletop surfaces", ACM International Conference on Interactive Tabletops and Surfaces, 2010.
  12. Chen and Mengyang, "Single image defogging", Network Infrastructure and Digital Content, (NIDC), 2009 International Conference on. IEEE, 2009.
  13. Xu, Zhiyuan, Xiaoming Liu, and Xiaonan Chen,"Fog removal from video sequences using contrast limited adaptivehistogramequalization", Computational Intelligence and Software Engineering, 2009 International Conference on. IEEE, 2009
  14. 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
Index Terms

Computer Science
Information Sciences

Keywords

Dark channel prior Haze Airlight Fuzzy filter

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