Volume 42 Issue 9
Feb.  2014
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Wang Sen, Pan Yuzhai, Liu Yi, Yang Baosen, Qu Shiliang. Image quality improvement of laser active imaging in fog[J]. Infrared and Laser Engineering, 2013, 42(9): 2392-2396.
Citation: Wang Sen, Pan Yuzhai, Liu Yi, Yang Baosen, Qu Shiliang. Image quality improvement of laser active imaging in fog[J]. Infrared and Laser Engineering, 2013, 42(9): 2392-2396.

Image quality improvement of laser active imaging in fog

  • Received Date: 2013-01-07
  • Rev Recd Date: 2013-02-17
  • Publish Date: 2013-09-25
  • The image quality of laser active imaging system degraded dramatically in fog. The obtained infrared image had the features of low contrast and serious noise. Thus an image process method combining dark channel prior and bilateral filter was proposed. The dark channel prior was adopted to remove fog from the image. Then the image was denoised using the bilateral filter. So the contrast of the image was improved and the noise was reduced. Both subjective and objective evaluation of the processed image by different methods show that the proposed method could obtain better visual effect. The standard deviation is more than doubled. The information entropy and information capacity have about a twenty percent improvement. Thus, it's an effective way to improve the quality of infrared image in fog.
  • [1] Wang Dejun, Wang Jianli, Yin Yumei, et al. Near infrared real-time penetrating fog imaging method based on FPGA[J]. Chinese Journal of Optics and Applied Optics, 2009, 2(5): 445-451. (in Chinese) 王德俊,王建立,阴玉梅, 等. 基于FPGA的近红外实时透雾成像方法[J]. 中国光学与应用光学, 2009, 2(5): 445-451.
    [2]
    [3] Li li, Gao Zhiyun, Wang Xia, et al. effects of forward-scattering of fog on range-gated system[J]. Infrared and Laser Engineering, 2004, 33(6): 562-566.(in Chinese). 李丽, 高稚允, 王霞, 等. 雾的前向散射对距离选通成像系统的影响[J]. 红外与激光工程, 2004, 33(6): 562-566.
    [4]
    [5] Zhu Haibo, Zhang Shengchong, Yang Haibo, et al. System design of active imaging[J]. Infrared and Laser Engineering, 2008, 37(S): 93-94. (in Chinese) 朱海波, 张晟翀, 杨海波, 等. 激光主动成像系统设计[J]. 红外与激光工程, 2008, 37(S): 93-94.
    [6]
    [7]
    [8] Yu Tianhe, Hao Fuchun, Kang Weimin, et al. Summarization on infrared image enhancement technology[J]. Infrared and Laser Engineering, 2007, 36(S): 335-338. (in Chinese) 于天河, 郝富春, 康为民,等. 红外图像增强技术综述[J]. 红外与激光工程, 2007, 36(S): 335-338.
    [9] He Kaiming, Sun Jian, Tang Xiaoou. Single image haze removal using dark channel prior[J]. Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353.
    [10]
    [11]
    [12] Tomasi C, Manduchi R. Bilateral filtering for gray and color images[C]//Proceedings of IEEE Conference on Computer vision, 1998.
    [13]
    [14] He Kaiming, Sun Jian, Tang Xiaoou. Guided image filtering[C]//ECCV, 2010: 1-14.
    [15]
    [16] Jiang Jianguo, Hou Tianfeng, Qi Meibin, et al. Improved algorithm on image haze removal using dark channel prior[J]. Journal of Circuits and Systems, 2011, 16(2): 7-12.(in Chinese) 蒋建国, 侯天峰, 齐美彬, 等. 改进的基于暗原色先验的图像去雾算法[J]. 电路与系统学报, 2011, 16(2): 7-12.
    [17] Xu Chunmei, Li Gang, Hu Wengang, et al. Image quality evaluation of infrared image[J]. Infrared Technology, 2004, 26(6):72-75. (in Chinese) 徐春梅, 李刚, 胡文刚, 等. 红外图像评价质量研究[J]. 红外技术, 2004, 26(6): 72-75.
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Image quality improvement of laser active imaging in fog

  • 1. Department of Opt-electronics,Harbin Institute of Technology at Weihai,Weihai 264209,China

Abstract: The image quality of laser active imaging system degraded dramatically in fog. The obtained infrared image had the features of low contrast and serious noise. Thus an image process method combining dark channel prior and bilateral filter was proposed. The dark channel prior was adopted to remove fog from the image. Then the image was denoised using the bilateral filter. So the contrast of the image was improved and the noise was reduced. Both subjective and objective evaluation of the processed image by different methods show that the proposed method could obtain better visual effect. The standard deviation is more than doubled. The information entropy and information capacity have about a twenty percent improvement. Thus, it's an effective way to improve the quality of infrared image in fog.

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