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Proceedings Paper

Study of defog technology based on scattering model with laser imaging night vision assistant driving system
Author(s): Hongjun Liu; Yan Zhou; Xin-wei Wang
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Paper Abstract

In the night vision assistant driving systems with near IR active imaging, the contrast and resolution of images or videos captured by cameras are drastically altered by back scattering in bad weather such as fog and mist etc, which brings a hidden danger in the night driving. In order to remove weather effects from images and make vision information captured by vision systems more valuable, it is imperative to make a study of the defog algorithm in laser night vision images. Direct towards laser active imaging assistant driving system, Monocular Camera Machine Vision and ABA Model are combined to restore the blurred images of driving environment in night fog day. In order to obtain the scene depth information, the camera was calibrated firstly; then, the scene depth map by linear imaging model and the Technical Standard of Highway Engineering was constructed. The brightness of each pixel at the receiver is composed of scene point attenuation irradiance, back scattering irradiance and airlight illumination scattering intensity in ABA model simply. By removing back scattering and airlight illumination scattering by particles to restore the image degraded in foggy day.

Paper Details

Date Published: 4 August 2009
PDF: 6 pages
Proc. SPIE 7383, International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications, 73830R (4 August 2009); doi: 10.1117/12.835538
Show Author Affiliations
Hongjun Liu, Institute of Semiconductors (China)
Kunming Univ. of Science and Technology (China)
Yan Zhou, Institute of Semiconductors (China)
Xin-wei Wang, Institute of Semiconductors (China)

Published in SPIE Proceedings Vol. 7383:
International Symposium on Photoelectronic Detection and Imaging 2009: Advances in Infrared Imaging and Applications
Jeffery Puschell; Hai-mei Gong; Yi Cai; Jin Lu; Jin-dong Fei, Editor(s)

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