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A Novel Framework for Image Dehazing

D. Bhagya Sree1

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 1398-1403, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.13981403

Online published on Jul 31, 2018

Copyright © D. Bhagya Sree . 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: D. Bhagya Sree, “A Novel Framework for Image Dehazing,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1398-1403, 2018.

MLA Style Citation: D. Bhagya Sree "A Novel Framework for Image Dehazing." International Journal of Computer Sciences and Engineering 6.7 (2018): 1398-1403.

APA Style Citation: D. Bhagya Sree, (2018). A Novel Framework for Image Dehazing. International Journal of Computer Sciences and Engineering, 6(7), 1398-1403.

BibTex Style Citation:
@article{Sree_2018,
author = {D. Bhagya Sree},
title = {A Novel Framework for Image Dehazing},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1398-1403},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2618},
doi = {https://doi.org/10.26438/ijcse/v6i7.13981403}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.13981403}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2618
TI - A Novel Framework for Image Dehazing
T2 - International Journal of Computer Sciences and Engineering
AU - D. Bhagya Sree
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1398-1403
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

Image dehazing is a method to improve the images gained in poor weather conditions, for example, haze and dimness. Existing image dehazing strategies are principally in view of dark channel prior. Since the dark channel isn`t sensible for sky regions, a sky division and area wised medium transmission based image dehazing strategy is proposed in this paper. Right off the bat, sky regions are divided by quad-tree part based component pixels location. At that point, a medium transmission estimation strategy for sky regions is proposed in view of shading trademark perception of sky regions. The medium transmission is then separated by an edge saving guided channel. At long last, in light of the evaluated medium transmission, the hazed images are reestablished. Exploratory outcomes show that the execution of the proposed strategy is superior to that of existing techniques. The reestablished image is more regular, particularly in the sky regions.

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)