CFP last date
20 January 2025
Reseach Article

Efficient Dehazing Technique for Hazy Images using DCP and WAF

by Monika, Lavi Tyagi, Rajiv Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 42
Year of Publication: 2018
Authors: Monika, Lavi Tyagi, Rajiv Singh
10.5120/ijca2018916991

Monika, Lavi Tyagi, Rajiv Singh . Efficient Dehazing Technique for Hazy Images using DCP and WAF. International Journal of Computer Applications. 179, 42 ( May 2018), 15-21. DOI=10.5120/ijca2018916991

@article{ 10.5120/ijca2018916991,
author = { Monika, Lavi Tyagi, Rajiv Singh },
title = { Efficient Dehazing Technique for Hazy Images using DCP and WAF },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 179 },
number = { 42 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 15-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number42/29362-2018916991/ },
doi = { 10.5120/ijca2018916991 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:09.026076+05:30
%A Monika
%A Lavi Tyagi
%A Rajiv Singh
%T Efficient Dehazing Technique for Hazy Images using DCP and WAF
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 42
%P 15-21
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Attenuation minimizes the contrast and air-light enlarges the whiteness in the captured image. Fog and haze are atmospheric conditions generated by floating particles, degrade the quality of images. Haze removal algorithms have become more beneficial for several vision applications. As we know there is no single technique i.e. accurate for all different kind of problems and circumstances. The existing methods have neglected many issues like noise reduction and non-uniform illumination which will be presented in the output image of the existing haze removal algorithms. These existing approaches either required single image or multiple images for removing haze from an input image. Multiple image of a same scene is required in multiple images based algorithms. So, this requirement is not fulfilled mostly times. So, the area of single image dehazing is an active area in the field of digital image processing. This paper introduced an efficient haze removal method based on Dark Channel Prior (DCP) and Weighted Average Filter (WAF). Refinement of transmission map will be done using WAF, and then image is restored. This proposed algorithm is implemented and tested in MATLAB. The results have shown that the proposed algorithm gives quite effective and quality results.

References
  1. Saggu, Manpreet Kaur, and Satbir Singh. "A review on various haze removal techniques for image processing." International Journal of Current Engineering and Technology. 5, no. 3 (2015): 1500-1505.
  2. Narasimhan, Srinivasa G., and Shree K. Nayar. "Vision and the atmosphere." International Journal of Computer Vision 48, no. 3 (2002): 233-254.
  3. He, Kaiming, Jian Sun, and Xiaoou Tang. "Single image haze removal using dark channel prior." IEEE transactions on pattern analysis and machine intelligence 33, no. 12 (2011): 2341-2353.
  4. Mao, Jun, UthaiPhommasak, Shinya Watanabe, and Hiroyuki Shioya. "Detecting foggy images and estimating the haze degree factor." Journal of Computer Science & Systems Biology 7, no. 6 (2014): 1.
  5. Bronte, Sebastián, Luis M. Bergasa, and Pablo Fernandez Alcantarilla. "Fog detection system based on computer vision techniques." In Intelligent Transportation Systems, 2009. ITSC'09. 12th International IEEE Conference on, pp. 1-6. IEEE, 2009.
  6. He, Kaiming, Jian Sun, and Xiaoou Tang. "Guided image filtering." IEEE transactions on pattern analysis and machine intelligence 35, no. 6 (2013): 1397-1409.
  7. Tomasi, C., Manduchi, R.: Bilateral filtering for gray and color images. In: ICCV (1998).
  8. Levin, Anat, Dani Lischinski, and Yair Weiss. "A closed-form solution to natural image matting." IEEE Transactions on Pattern Analysis and Machine Intelligence 30, no. 2 (2008): 228-242.
  9. Guo, Fan, Jin Tang, and Xiaoming Xiao. "Foggy scene rendering based on transmission map estimation." International Journal of Computer Games Technology 2014 (2014): 10.
  10. He, Kaiming, Jian Sun, and Xiaoou Tang. "X.: Single image haze removal using dark channel prior." (2009).
  11. Xie, Bin, Fan Guo, and Zixing Cai. "Improved single image dehazing using dark channel prior and multi-scale Retinex." In Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on, vol. 1, pp. 848-851. IEEE, 2010.
  12. Xu, Haoran, Jianming Guo, Qing Liu, and Lingli Ye. "Fast image dehazing using improved dark channel prior." In Information Science and Technology (ICIST), 2012 International Conference on, pp. 663-667. IEEE, 2012.
  13. Anupama, Nidhi Singh and Lavi Tyagi. Hybrid Dehazing Technique using IDCP with Histogram Equalization for Color Image. International Journal of Computer Applications 174(1):1-5, September 2017.
  14. W.K. Middleton, Vision through the Atmosphere (1957).
  15. Md. Imtiyaz Anwar, Arun Khosla," Vision enhancement through single image fog removal" Engineering Science and Technology, an International Journal, Volume 20, Issue 3, June 2017, Pages 1075-1083.
  16. http://www.lcpc.fr/english/products/image-databases/article/frida-foggy-road-image-database
Index Terms

Computer Science
Information Sciences

Keywords

Dark Channel Prior (DCP) Guided Filter Average Filter Weighted Average Filter.