[1] Li Nan, Lu Xiaobo,. Removing fog from traffic image sequence [J]. Journal of Southeast University (English Edition), 2011, 27 (3): 290-294. [doi:10.3969/j.issn.1003-7985.2011.03.013]

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Removing fog from traffic image sequence()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

27

Issue:

2011 3

Page:

290-294

Research Field:

Computer Science and Engineering

Publishing date:

2011-09-30

Info

Title:

Removing fog from traffic image sequence

Author(s):

Li Nan¹;  Lu Xiaobo²

¹School of Transportation, Southeast University, Nanjing 210096, China
² School of Automation, Southeast University, Nanjing 210096, China

Keywords:

traffic images;  fog;  distance field;  depth of field;  physical model

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2011.03.013

Abstract:

Aiming at removing fog from traffic images, a distance field is built according to the characteristics of traffic images, and a novel parameter estimation method based on the traffic image sequence is proposed. The fog model is derived from atmospheric scattering models. The direction of the distance field is parallel to the center line of the road, which increases along a line from the observer to the horizon, and the normalization is carried out to improve the distribution of the distance field model. After parameter initialization, the variations of the average gray values of reference regions are taken as the determining conditions to adjust the parameters. Finally, restorations are made by the fog model. Experimental results show that the proposed method can effectively remove fog from traffic images.

References:

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[2] Zhu Pei, Zhu Hong, Qian Xueming, et al. An image clearness method for fog [J]. Journal of Image and Graphics, 2004, 9(1): 124-128.
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[5] Narasimhan S G, Nayar S K. Chromatic framework for vision in bad weather[C]//IEEE Conference on Computer Vision and Pattern Recognition. Hiton Head Island, South Carolina, USA, 2000: 598-605.
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[7] Narasimhan S G, Nayar S K. Contrast restoration of weather degraded images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6): 713-723.
[8] Hautiere N, Tarel J P, Aubert D. Mitigation of visibility loss for advanced camera-based driver assistance[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(2): 474-448.
[9] Huang Lihong. Defogging method for degraded image[J]. Infrared and Laser Engineering, 2010, 39(5): 985-988.(in Chinese)
[10] Dong Huiying, Fang Shuai, Wang Xinwei, et al. Method based on physical model to restore degraded weather images and its application[J]. Journal of Northeastern University, 2005, 26(3): 217-219.(in Chinese)

Memo

Memo:

Biographies: Li Nan(1982—), male, graduate; Lu Xiaobo(corresponding author), male, doctor, professor, xblu@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.60972001), the National Key Technologies R& D Program of China during the 11th Five-Year Period(No.2009BAG13A06).
Citation: Li Nan, Lu Xiaobo. Removing fog from traffic image sequence[J].Journal of Southeast University(English Edition), 2011, 27(3):290-294.[doi:10.3969/j.issn.1003-7985.2011.03.013]

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