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Reseach Article

A Review on Methods of Image Dehazing

by Shruti P. Patel, Manish Nakrani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 133 - Number 12
Year of Publication: 2016
Authors: Shruti P. Patel, Manish Nakrani
10.5120/ijca2016908076

Shruti P. Patel, Manish Nakrani . A Review on Methods of Image Dehazing. International Journal of Computer Applications. 133, 12 ( January 2016), 44-49. DOI=10.5120/ijca2016908076

@article{ 10.5120/ijca2016908076,
author = { Shruti P. Patel, Manish Nakrani },
title = { A Review on Methods of Image Dehazing },
journal = { International Journal of Computer Applications },
issue_date = { January 2016 },
volume = { 133 },
number = { 12 },
month = { January },
year = { 2016 },
issn = { 0975-8887 },
pages = { 44-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume133/number12/23841-2016908076/ },
doi = { 10.5120/ijca2016908076 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:31:01.708000+05:30
%A Shruti P. Patel
%A Manish Nakrani
%T A Review on Methods of Image Dehazing
%J International Journal of Computer Applications
%@ 0975-8887
%V 133
%N 12
%P 44-49
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Literature survey is an important for understanding and gaining much more knowledge about the specific area of a subject. The outdoor images captured in inclement weather are degraded due to the presence of haze, fog, rain and so on. Images of scenes captured in bad weather have poor contrasts and colors. This may cause difficulty in detecting the objects in the captured hazy images. Due to haze there is a trouble to many computer vision applications as it diminishes the visibility of the scene. This paper presents a study about different image dehazing methods to remove the haze from the hazy images captured in real world weather conditions to recover a fast and improved quality of haze free images. There is a improvement in terms of contrast, visible range and color fidelity. All these techniques are widely used in many applications such as outdoor Surveillance, object detection, underwater images, etc.

References
  1. Bingquan Huo and Fengling Yin, “Image Dehazing With Dark Channel Prior And Novel Estimation Model”, International Journal of Multimedia and Ubiquitous Engineering Vol. 10, No. 3 (2015).
  2. Vinkey Sahu and Vinkey Sahu, “A Survey Paper On Single Image Dehazing”, IJRITCC Volume: 3 Issue: 2 February 2015.
  3. Dilraj Kaur and Pooja, “A Critical Study and comparative Analysis of Various Haze Removal Technique”, International Journal of Computer Applications (0975 – 8887) Volume 121 – o.16, July 2015.
  4. Yishu Zhai, Dongjiang Ji, “Single Image Dehazing For Visibility Improvement”, International Conference on Unmanned Aerial Vehicles in Geomatics, 30 Aug–02 Sep 2015.
  5. Pranjal Garg, Shailender Gupta, Bharat Bhushan and Prem Chand Vashist, “A Hybrid Defogging Technique Based On Anisotropic Diffusion And IDCP Using Guided Filter”, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8, No.7 (2015).
  6. Atul Gujral, Aditi, Shailender Gupta and Bharat Bhushan, “A Comparison Of Various Defogging Techniques”, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7, No.3 (2014).
  7. Shih-Chia Huang, Bo-Hao Chen, and Wei-Jheng Wang, “Visibility Restoration Of Single Hazy Images Captured In Real-World Weather Conditions”, IEEE Transactions on Circuits and Systems for Video Technology 2014.
  8. Harpoonamdeep Kaur, Dr. Rajiv Mahajan, “A Review on Various Visibility Restoration Techniques”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 5, May 2014.
  9. Gagandeep Singh, “Evaluation Of Various Digital Image Fog Removal Algorithms”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 7, July 2014.
  10. Shuai Yang, Qingsong Zhu, Jianjun Wang, Di Wu, and YaoqinXie, “An Improved Single Image Haze Removal Algorithm Based On Dark Channel Prior And Histogram Specification”, 2013.
  11. Ashok Shrivastava, Er. Rekha Kumari, “Review on Single Image Fog Removal”, International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 8, August 2013.
  12. A. K. Tripathi and S. Mukhopadhay, “Single Image Fog Removal using Anisotropic Diffusion”, IET Image Processing, vol. 6, no. 7, 2012.
  13. Tripathi, A. K., and S. Mukhopadhyay. "Single image fog removal using bilateral filter." Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on. IEEE, 2012.
  14. I. Yoon, J. Jeon, J. Lee, and J. Paik, "Spatially Adaptive Image Defogging Using Edge Analysis And Gradient-Based Tone Mapping", Proc. IEEE Int. Conf. Consumer Electronics, January 2011.
  15. Jiahao Pang, Oscar C. Au and Zheng Guo, “Improved Single Image Dehazing Using Guided Filter”, APSIPA ASC 2011.
  16. Kaiming He, Jian Sun, and Xiaoou Tang, “Single Image Haze Removal Using Dark Channel Prior”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 12, December 2011.
  17. Yan Wang and Bo Wu, “Improved Single Image Dehazing using Dark Channel Prior”, IEEE 2010.
  18. K. He, J. Sun and X. Tang, “Single Image Haze Removal Using Dark Channel Prior” , IEEE Int. Conf. on Computer Vision and Pattern reorganization, 2009.
  19. R. T. Tan, “Visibility in bad weather from a single image” , in IEEE Conf. on Computer Vision and Pattern Recognition, 2008.
  20. K. Garg, S. K. Nayar, “Vision and rain”, Int. J. Comput.Vis., 2007.
  21. A. S. Narasimhan and S. Nayar, “Contrast restoration of weather degraded images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 6, June 2003.
  22. Y.Y. Schechner, S.G. Narasimhan, and S.K. Nayar, “Polarization Based Vision Through Haze,” Proc. Applied Optics, special issue: light and color in the open air., vol. 42, no. 3, Jan. 2003.
  23. Srinivasa G. Narasimhan And Shree K. Nayar, “Vision and the Atmosphere”, International Journal of Computer Vision 48(3), 2002.
  24. Yoav Y. Schechner, Srinivasa G. Narasimhan and Shree K. Nayar, “Instant Dehazing Of Images Using Polarization”, Proc. Computer Vision & Pattern Recognition Vol. 1(2001).
Index Terms

Computer Science
Information Sciences

Keywords

Outdoor images Dehazing Hazy Images Transmission map Polarization Dark Channel Prior(DCP) Improved DCP (IDCP).