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Haze Removal on Image Using Dark Channel and Bright Channel Methods

S. Bhavani1 , R. Shenbagavalli2

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-08 , Page no. 26-31, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si8.2631

Online published on Apr 10, 2019

Copyright © S. Bhavani, R. Shenbagavalli . 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: S. Bhavani, R. Shenbagavalli, “Haze Removal on Image Using Dark Channel and Bright Channel Methods,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.08, pp.26-31, 2019.

MLA Style Citation: S. Bhavani, R. Shenbagavalli "Haze Removal on Image Using Dark Channel and Bright Channel Methods." International Journal of Computer Sciences and Engineering 07.08 (2019): 26-31.

APA Style Citation: S. Bhavani, R. Shenbagavalli, (2019). Haze Removal on Image Using Dark Channel and Bright Channel Methods. International Journal of Computer Sciences and Engineering, 07(08), 26-31.

BibTex Style Citation:
@article{Bhavani_2019,
author = {S. Bhavani, R. Shenbagavalli},
title = {Haze Removal on Image Using Dark Channel and Bright Channel Methods},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {08},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {26-31},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=910},
doi = {https://doi.org/10.26438/ijcse/v7i8.2631}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.2631}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=910
TI - Haze Removal on Image Using Dark Channel and Bright Channel Methods
T2 - International Journal of Computer Sciences and Engineering
AU - S. Bhavani, R. Shenbagavalli
PY - 2019
DA - 2019/04/10
PB - IJCSE, Indore, INDIA
SP - 26-31
IS - 08
VL - 07
SN - 2347-2693
ER -

           

Abstract

Haze is a main degradation of outdoor images, weakening both colors and contrasts due to atmospheric phenomena. Dehazed images mean sustaining low bitrates in the transmission pipeline. .In this paper to remove haze from a single input image combination of dark channel and bright channel method were used. In a dark channel method , the non-sky patches, at least one color channel has very low intensity at some pixels or, the minimum intensity in such a patch should has a very low value. A kind of statistics of outdoor haze-free images is a dark channel prior method. Then estimate the bright channel to control the amount of brightness enhancement and combine both dark channel and bright channel method to remove haze. The Noise estimation can be measured using MSE (Mean Square Error), RMSE (Root Mean Square Error), BER (Bit Error Rate), PSNR (Peak Signal-to-Noise Ratio) and MAE (Median Angular Error). Experimental result shows that the proposed method can provide the better restored result than the existing methods.

Key-Words / Index Term

Image Dehazing, Dark Channel prior, Contrast Enhancement

References

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[2]https://www. quora.com/What-is-dark-channel-prior-in-image-processing.
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[4]https://www.semanticscholar.org/paper/Image-Enhancement-Using-Bright-Channel-Prior-Sun-Guo/33df832f332fd667449327b3be21f54e11adcb38
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