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Image Dehazing (Defogging) by using Depth Estimation and Fusion with Guided Filter

by Anil Kumar, Bharti Chourasia
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 8
Year of Publication: 2017
Authors: Anil Kumar, Bharti Chourasia
10.5120/ijca2017912835

Anil Kumar, Bharti Chourasia . Image Dehazing (Defogging) by using Depth Estimation and Fusion with Guided Filter. International Journal of Computer Applications. 158, 8 ( Jan 2017), 16-20. DOI=10.5120/ijca2017912835

@article{ 10.5120/ijca2017912835,
author = { Anil Kumar, Bharti Chourasia },
title = { Image Dehazing (Defogging) by using Depth Estimation and Fusion with Guided Filter },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 8 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 16-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number8/26928-2017912835/ },
doi = { 10.5120/ijca2017912835 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:18.013687+05:30
%A Anil Kumar
%A Bharti Chourasia
%T Image Dehazing (Defogging) by using Depth Estimation and Fusion with Guided Filter
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 8
%P 16-20
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The season affects the imaging of the hill station highly and all other reasons moreover time to time. Our universal defoging method that determining the atmospheric light and produces a spread map in the YCbCr color channels. With this relative depth information we can construct the corresponding atmospheric light to restrain the edge halation. We generate the spread map by estimating the atmospheric light except a continuous region which has no edge information. The method performs a per-pixel manipulation, which is straightforward to implement and then apply the Guided filter to improve the image quality. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

References
  1. I. Yoon, S. Kim, D. Kim, M. H. Hayes, and J. Paik, "Adaptive defogging with color correction in the HSV color space for consumer surveillance system," IEEE Trans. on Consumer Electronics, vol. 58, no. 1, Feb. 2012, pp. 111-116.
  2. C. Zhen, S. Jihong, and P. Roth, "Single image defogging algorithm based on dark channel priority," Journal of Multimedia, vol. 8, no. 4, Aug. 2013, pp. 432-438.
  3. W. Feng, N. Guan, X. Zhang, X. Huang, and Z. Luo, "Single image defogging with single and multiple hybrid scattering model," International Conf. on Security, Pattern Analysis, and Cybernetics (SPAC), 18-19 Oct. 2014, pp. 247-252.
  4. H. Kawarabuki and K. Onoguchi, "Snowfall detection in a foggy scene," 22nd International Conf. on Pattern Recognition (ICPR), 24-28 Aug. 2014, pp. 877 - 882.
  5. Y. –K. Wang and C.-T. Fan, "Single image defogging by multiscale depth fusion," IEEE Trans. on Image Process., vol. 23, no. 11, Nov. 2014, pp. 4826-4837.
  6. Y. Lee, K. B. Gibson, Z. Lee, and T. Q. Nguyen, "Stereo image defogging," IEEE International Conf. on Image Processing (ICIP), 27-30 Oct. 2014, pp. 5427 - 5431.
  7. C. C. Cheng, F.-C. Cheng, P.-H. Lin, S.-C. Huang, "A L0 norm transmission model for defogging images," IEEE International Conf. on Consumer Electronics - Taiwan, 2014, pp. 151 - 152.
  8. H. Zhao, C. Xiao, J. Yu, and X. Xu, "Single Image Fog Removal Based on Local Extrema," IEEE/CAA Journal of Automatica Sinica, vol. 2, no. 2, Apr. 2015, pp. 158-165.
  9. L. K. Choi, J. You, and A. C. Bovik, "Referenceless prediction of perceptual fog density and perceptual image defogging," IEEE Trans. on Image Process., vol. 24, no. 11, Nov. 2015, pp. 3888-3901.
  10. Y. Xu, J. Wen, L. Fei, and Z. Zhang, "Review of Video and Image Defogging Algorithms and Related Studies on Image Restoration and Enhancement," IEEE Access, 2016, vol.: 4, pp. 165 - 188.
  11. F. Fu and F. Liu, "Wavelet-based retinex algorithm for unmanned aerial vehicle image defogging," 8th International Symposium on Computational Intelligence and Design (ISCID), 2015, vol. 1, pp. 426 - 430.
  12. L. Deng, O.-X. Li, and S.-W. Zhao, "An improved image defogging algorithm based on global dark channel prior and fuzzy logic control," 12th International Computer Conf. on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 18-20 Dec. 2015, pp. 188 - 191.
  13. D. Sharma, Y. Kurmi, and V. Chaurasia, “Formation of super- resolution image: a review,” Int. Jour. of Emerging Tech. and Adv. Engg., Apr. 2014, vol. 4, no. 4, pp. 218-221.
  14. Y. Kurmi and V. Chaurasia, “An image fusion approach based on adaptive fuzzy logic model with local level processing,” Int. Jour. of Comp. Appl., Aug. 2015, vol. 124, no.1, pp. 39-42.
  15. S. Tiwari, K. Chauhan, and Y. Kurmi “Shadow detection and compensation in aerial images using MATLAB,” Int. Jour. of Comp. Appl., June 2015, vol. 119, no.20, pp. 5-9.
  16. Y. Kurmi and V. Chaurasia, “Performance of haze removal filter for hazy and noisy images,” Int. Jour. of Sci. Engg. and Tech., Apr. 2014, vol. 3 no. 4, pp. 437-439.
  17. M. K. Patle, B. Chourasia, and Y. Kurmi, "High Dynamic Range Image Analysis through Various Tone Mapping Techniques," Int. Jour. of Comp. Appl., vol.153, no. 11, Nov. 2016 pp. 14-17.
  18. A. Kumar, B. Chourasia, and Y. Kurmi, "Image defogging by multiscale depth fusion and hybrid scattering model," International Journal of Computer Applications (0975 – 8887), vol. 155, no 11, Dec. 2016, pp. 34-38.
  19. C. Chengtao1, Z. Qiuyu, and L. Yanhua, "A Survey of Image Dehazing Approaches," 27th Chinese Control and Decision Conf. (CCDC), 2015, pp. 3964 - 3969.
  20. Fengzhi Fu; Fang Liu, "Wavelet-Based Retinex Algorithm for Unmanned Aerial Vehicle Image Defogging," 8th Inter. Symposium on Comput. Intell. and Design (ISCID), 2015, vol. 1, pp. 426-430.
  21. L. Deng; O. X. Li; S. W. Zhao, "An improved image defogging algorithm based on global dark channel prior and fuzzy logic control," 12th International Computer Conf. on Wavelet Active Media Tech. and Info. Process. (ICCWAMTIP), 2015, pp.188 - 191.
  22. L. Bo, X. Qingguo, "Inland river image defogging based on optimized contrast enhancement," IEEE Information Technology, Networking, Electronic and Automation Control Conf., 2016, pp. 145 - 150.
  23. H. Park, J. Park, H. Kim and J. Paik, "Improved DCP-Based Image Defogging Using Stereo Images," 6th International Conf. on Consumer Electronics - Berlin (ICCE-Berlin), 2016, pp. 48 - 49.
  24. Y. Lee, K. Hirakawa, and T. Q. Nguyen, "Joint defogging and demosaicking," IEEE Trans. on Image Process., 2016, vol. PP, no. 99, pp. 1 - 1.
  25. K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., Jun. 2009, pp. 1956–1963.
  26. L. Kratz and K. Nishino, “Factorizing scene albedo and depth from a single foggy image,” in Proc. IEEE Int. Conf. Comput. Vis., Sep.–Oct. 2009, pp. 1701–1708.
  27. J.-P. Tarel and N. Hautiere, “Fast visibility restoration from a single color or gray level image,” in Proc. IEEE Int. Conf. Comput. Vis., Sep.–Oct. 2009, pp. 2201–2208.
  28. C. O. Ancuti, C. Ancuti, and P. Bekaert, “Effective single image dehazing by fusion,” in Proc. IEEE Int. Conf. Image Process., Sep. 2010, pp. 3541–3544.
  29. H. B. Mitchell, Image Fusion: Theories, Techniques and Applications. New York, NY, USA: Springer-Verlag, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Image Fusion Image Defogging Scattering model single image defogging

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