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Survey Paper on Image Defogging Using Various Techniques

Bulbul Bandil, Dr. Vandana Vikas Tharke, Dr.Vikas Mahor

Abstract


Because of the adverse climate conditions like the nearness fog or heavy rain, digital images are effectively subjected to a wide assortment of disturbance amid acquisition, which may decrease visual impact and influence post-handling of the image. Images corrupted by mist fog adversely the nature of vision-based physical security framework. Writing review is an imperative for comprehension and increasing significantly more learning about the particular zone of a subject. The outdoor images caught in severe climate are corrupted because of the presence of fog, rain et cetera. Images of scenes caught in awful climate have poor contrasts and hues. This may cause trouble in distinguishing the items in the caught murky pictures. Because of fog there is an inconvenience to numerous PC vision applications as it lessens the perceivability of the scene. This paper exhibits an study about various image defogging techniques to expel the haze from the fog images caught in true world to recuperate a fast and enhanced nature of fog free images.

Keywords: Defog, DCP, IDCP, CLAHE, Mix-CLAHE etc.

Cite this Article
Bulbul Bandil, Vandana Vikas Tharke, Vikas Mahor. Survey Paper on Image Defogging Using Various Techniques. Recent Trends in Parallel Computing. 2018; 5(1): 20–26p.



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References


S. G. Narasimhan and S. K. Nayar. Contrast restoration of weather degraded images. PAMI, 25:713–724, 2003

K. He, J. Sun, and X. Tang. Single image haze removal using dark channel prior. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR'09), pages 1 956-1963, 2009

Pranjal Garg, Shailender Gupta, Bharat Bhushan3 and Prem Chand Vashist “An in-Depth Analyses of Various Defogging Techniques” International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8, No.10 (2015), pp.279-296.

Yadav, G. Maheshwari, S. and Agarwal, A., "Fog removal techniques from images: A comparative review and future directions,” Signal Propagation and Computer Technology, 2014, pp. 44-52.

Saggu, M.K. and Singh, S., "Review on Various Haze Removal Techniques for Image Processing," International Journal of Current Engineering and Technology, vol. 5, no. 3, pp. 1500-1505, June 2015

R. T. Tan, “Visibility in bad weather from a single image” , in IEEE Conf. on Computer Vision and Pattern Recognition, (2008), pp. 1-81.

Jing-Ming Guo, Jin-yuSyue, Vincent Radzicki, and Hua Lee, Fellow,” An Efficient Fusion-Based Defogging”, IEEE IEEE Transactions on Image Processing ,Vol: 26, Issue: 9, Sept. 2017.

W. S. Zheng, S. Gong, and T. Xiang, "Quantifying and Transferring Contextual Information in Object Detection",IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 4, pp. 762-777,2012.

A. Levin, D. Lischinski, and Y. Weiss, “A Closed Form Solution to Natural Image Matting,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, (2006), pp. 61-68.

H. Koschmieder, “Theorie der Horizontalen Sichtweite”, Beitr. Phys. Freien Atm., vol. 12, (1924), pp. 171-181.

K. He, J. Sun, and X. Tang, “Guide image filtering”, (2010), pp. 1-14.

Kaur, D. and Pooja, "A Critical Study and Comparative Analysis of various fog removal techniques," International Journal of Computer Applications, vol. 121, no. 16, pp. 9-14, July 2015.

Zhigang Ling, Jianwei Gong, Guoliang Fan, Senior Member, IEEE, and Xiao Lu “Optimal Transmission Estimation via Fog Density Perception for Efficient Single Image Defogging” 1520-9210 (c) 2017 IEEE.

Changli Lii, Tanghuai Fan, Xiao Ma, Zhen Zhang Hongxin Wui, Lin Chen “An Improved Image Defogging Method Based on Dark Channel Prior” 2017 2nd International Conference on Image, Vision and Computing.

Md. Imtiyaz Anwar, Arun Khosla, and Gajendra Singh ‘Visibility Enhancement with Single Image Fog Removal scheme using a Post-processing Technique’2017 4th International Conference on Signal Processing and Integrated Networks (SPIN)

Jaiveer Singh Sikarwar, Abhinav Vidwans “Modified Dark Channel Prior Model and Gaussian Laplacian Filtering with Transmission Map For Fog Removal” International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) – 2016 978-1-4673-9939-5/16/$31.00 ©2016 IEEE.

Krishna Swaroop Gautam, Abhishek Kumar Tripathi, M.V. Srinivasa Rao “Vectorization and optimization of fog removal algorithm” 978-1-4673-8286-1/16 $31.00 © 2016 IEEE

Yu Li, Shaodi You, Michael S. Brown, and Robby T. Tan “Haze Visibility Enhancement: A Survey and Quantitative Benchmarking” 2016 IEEE.

Negru, M., Nedevschi, S., & Peter, R. I. (2014, October). Exponential image enhancement in daytime fog conditions. In Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on (pp. 1675-1681). IEEE.


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