Fog and Haze Removal Based on Image DeHazing Technique
B. Naveen1 , P. Bharath Kumar Chowdary2
Section:Research Paper, Product Type: Journal Paper
Volume-7 ,
Issue-10 , Page no. 116-120, Oct-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i10.116120
Online published on Oct 31, 2019
Copyright © B. Naveen, P. Bharath Kumar Chowdary . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: B. Naveen, P. Bharath Kumar Chowdary, “Fog and Haze Removal Based on Image DeHazing Technique,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.10, pp.116-120, 2019.
MLA Style Citation: B. Naveen, P. Bharath Kumar Chowdary "Fog and Haze Removal Based on Image DeHazing Technique." International Journal of Computer Sciences and Engineering 7.10 (2019): 116-120.
APA Style Citation: B. Naveen, P. Bharath Kumar Chowdary, (2019). Fog and Haze Removal Based on Image DeHazing Technique. International Journal of Computer Sciences and Engineering, 7(10), 116-120.
BibTex Style Citation:
@article{Naveen_2019,
author = {B. Naveen, P. Bharath Kumar Chowdary},
title = {Fog and Haze Removal Based on Image DeHazing Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2019},
volume = {7},
Issue = {10},
month = {10},
year = {2019},
issn = {2347-2693},
pages = {116-120},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4905},
doi = {https://doi.org/10.26438/ijcse/v7i10.116120}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.116120}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4905
TI - Fog and Haze Removal Based on Image DeHazing Technique
T2 - International Journal of Computer Sciences and Engineering
AU - B. Naveen, P. Bharath Kumar Chowdary
PY - 2019
DA - 2019/10/31
PB - IJCSE, Indore, INDIA
SP - 116-120
IS - 10
VL - 7
SN - 2347-2693
ER -
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Abstract
Image dehazing is a technique to improve the images picked up in poor climate conditions, for instance, cloudiness and obscurity. Existing image dehazing systems are chiefly in perspective on dark channel prior. Since the dark channel isn`t reasonable for sky districts, a sky division and zone wised medium transmission based image dehazing methodology is proposed in this paper. Directly off the bat, sky areas are separated by quad-tree part based segment pixels area. By then, a medium transmission estimation methodology for sky locales is proposed in perspective on shading trademark view of sky areas. The medium transmission is then isolated by an edge sparing guided channel. Finally, in light of the assessed medium transmission, the hazed images are reestablished. Exploratory results demonstrate that the execution of the proposed procedure is better than that of existing methods. The reestablished image is progressively ordinary, particularly in the sky areas
Key-Words / Index Term
Image dehazing, image segmentation, dark channel prior
References
[1] Y. K. Wang, and C. T. Fan, “Single image defogging by multiscale depth fusion,” IEEE Trans. Image Process., vol. 23, no. 11, pp. 4826- 4837, Nov. 2014.
[2] 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. Consum. Electron., vol. 58, no. 1, pp. 111-116, Feb. 2012.
[3] 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, vol. 4, pp. 165-188, Mar. 2016
[4] R. T. Tan, “Visibility in bad weather from a single image,” in Proc. Of IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), pp. 1–8, Jun. 2008, Anchorage, Alaska.
[5] Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar, “Polarizationbased vision through haze,” Appl. Opt., vol. 42, no. 3, pp. 511–525, 2003.
[6] K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 12, pp.2341-2353, Dec. 2011.
[7] Y. Zhu, J. Liu, and Y. Hao, “A single image dehazing algorithm using sky detection and segmentation,” in Proc. of IEEE Int. Congr. Image Signal Process. (CISP), pp. 248-252, Oct. 2014. Dalian, China.
[8] K. B. Gibson, D. T. Vo, and T. Q. Nguyen, “An investigation of dehazing effects on image and video coding,” IEEE Trans. Image Process., vol.21, no.2, pp. 662-673, Feb. 2012.
[9] U.S. Department of Transportation Federal Highway Administration. http://ops.fhwa.dot.gov/Weather/
[10] National Highway Traffic Safety Administration. http://www. nhtsa.gov/
[11] Siogkas, G.K., Dermatas, E.S.: Detection, tracking and classification of road signs in adverse conditions. In: IEEE MELECON, pp. 537–540 (2006)
[12] Garg, K., Nayar, S.K.: Vision and rain. Int. J. Comput. Vis. 75(1), 3–27 (2007)
[13] Roser, M., Moosmann, F.: Classification of weather situations on single color images. In: IEEE Intelligent Vehicles Symposium, pp. 798–803. Eindhoven (2008)
[14] Narasimhan, S.G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vis. 48(3), 233–254 (2002)
[15] Narasimhan, S.G., Nayar, S.K.: Shedding light on the weather. In: International Conference on Com Computer Vision and, Pattern Recognition, pp. 665–672 (2003)
[16] Narasimhan, S.G., Nayar, S.K.: Contrast restoration of weather degraded images. IEEE Trans. Pattern Anal. Mach. Intell. 25(6), 713–724 (2003)
[17] Narasimhan, S.G., Nayar, S.K.: Interactive (De) weathering of an image using physical models. In: IEEE Workshop on Color and Photometric Methods in Computer Vision, in conjunction with ICCV (2003)
[18] Schechner, Y.Y., Narasimhan, S.G., Nayar, S.K.: Instant dehazing of images using polarization. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 325–332 (2001)