Volume 16 Issue 6
. 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Traffic and Transportation Engineering  > 2016  >  16(6): 149-158
GU Ming, ZHENG Lin-tao, LIU Zhong-hua. Infrared traffic image's enhancement algorithm combining dark channel prior and Gamma correction[J]. Journal of Traffic and Transportation Engineering, 2016, 16(6): 149-158.
Citation: GU Ming, ZHENG Lin-tao, LIU Zhong-hua. Infrared traffic image's enhancement algorithm combining dark channel prior and Gamma correction[J]. Journal of Traffic and Transportation Engineering, 2016, 16(6): 149-158.
shu

Infrared traffic image's enhancement algorithm combining dark channel prior and Gamma correction

  • 1.

    Department of Precision Instrument, Tsinghua University, Beijing 100084, China

  • 2.

    School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, Henan, China

  • 3.

    Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney 2007, New South Wales, Australia

More Information
  • Author Bio:

    GU Ming(1983-), male, doctoral student, +86-10-64842276, gum11@mails.tsinghua.edu.cn

  • Received Date: 2016-05-11
  • Publish Date: 2016-12-25
    Abstract
  • In order to enhance the visual quality of infrared traffic image collected by the intelligent traffic monitoring equipment effectively, the image defogging method of visible light was introduced into traffic infrared image enhancement processing, and a new infrared traffic image's enhancement algorithm combining dark channel prior and Gamma correction was proposed.First, the original degraded infrared traffic image was processed by dark channel prior algorithm to obtain initially enhanced image.Then, the brightness of initially enhanced image was adjusted by Gamma correction algorithm.The image enhancement effects of the new algorithm and other common infrared image enhancement algorithms were compared.Test result shows that the information entropies of two original infrared traffic images are respectively 4.71 and 5.07 and respectively increase to 6.45 and 5.92 after being processed by the new algorithm.The standard deviations of gray scale for two original infrared traffic images are respectively 6.90 and 19.14 and respectively increase to 31.17 and 32.35 after being processed by the new algorithm.The information entropy computational value of new algorithm is more than the values of other algorithms.So the enhancement effect of the proposed algorithm is better than the enhancement effects of other common infrared image enhancement algorithms, and it can significantly improve the visual effect of infrared traffic image and lay good foundation for following processing and analysis of image.

     

    • YOU Zheng(1963-), male, professor, PhD, +86-10-62782308, yz-dpi@mail.tsinghua.edu.cn
    FullText(HTML)
  • loading
    • References(30)
  • [1]
    白立岗, 贾冬冬. 红外摄像机在交通监控系统中的应用[J]. 中国交通信息产业, 2009(11): 89-90. doi: 10.3969/j.issn.1672-3333.2009.11.017

    BAI Li-gang, JIA Dong-dong. Application of infrared camera in traffic monitoring system[J]. China ITS Journal, 2009(11): 89-90. (in Chinese). doi: 10.3969/j.issn.1672-3333.2009.11.017
    [2]
    杜豫川, 张晓明, 刘成龙, 等. 基于红外图像和普通图像对比的高速公路可视度分析[J]. 交通运输系统工程与信息, 2016, 16(4): 73-78. doi: 10.3969/j.issn.1009-6744.2016.04.011

    DU Yu-chuan, ZHANG Xiao-ming, LIU Cheng-long, et al. Visibility analysis for freeway based on comparison of ordinary and infrared images[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(4): 73-78. (in Chinese). doi: 10.3969/j.issn.1009-6744.2016.04.011
    [3]
    丁利伟, 王宗俐, 程明阳. 高速公路红外引导系统透雾特性的试验研究[J]. 光电技术应用, 2014, 29(2): 4-9, 21. doi: 10.3969/j.issn.1673-1255.2014.02.002

    DING Li-wei, WANG Zong-Li, CHENG Ming-yang. Test research on detection ability of infrared guidance system for freeway traffic in fog[J]. Electro-Optic Technology Application, 2014, 29(2): 4-9, 21. (in Chinese). doi: 10.3969/j.issn.1673-1255.2014.02.002
    [4]
    LIN C L. An approach to adaptive infrared image enhancement for long-range surveillance[J]. Infrared Physics and Technology, 2011, 54(2): 84-91. doi: 10.1016/j.infrared.2011.01.001
    [5]
    NI Chao, LI Qi, XIA L Z. A novel method of infrared image denoising and edge enhancement[J]. Signal Processing, 2008, 88(6): 1606-1614. doi: 10.1016/j.sigpro.2007.12.016
    [6]
    LIANG Kun, MA Yong, XIE Yue, et al. A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization[J]. Infrared Physics and Technology, 2012, 55(4): 309-315. doi: 10.1016/j.infrared.2012.03.004
    [7]
    BAI Xiang-zhi, ZHOU Fu-gen, XUE Bin-dang. Image enhancement using multi scale image features extracted by top-hat transform[J]. Optics and Laser Technology, 2012, 44(2): 328-336. doi: 10.1016/j.optlastec.2011.07.009
    [8]
    LAI Rui, YANG Yin-tang, WANG Bing-jian, et al. A quantitative measure based infrared image enhancement algorithm using plateau histogram[J]. Optics Communications, 2010, 283(21): 4283-4288. doi: 10.1016/j.optcom.2010.06.072
    [9]
    DAI Shao-sheng, LIU Qin, LI Peng-fei, et al. Study on infrared image detail enhancement algorithm based on adaptive lateral inhibition network[J]. Infrared Physics and Technology, 2015, 68: 10-14. doi: 10.1016/j.infrared.2014.09.042
    [10]
    YUAN L T, SWEE S K, PING T C. Infrared image enhancement using adaptive trilateral contrast enhancement[J]. Pattern Recognition Letters, 2015, 54: 103-108. doi: 10.1016/j.patrec.2014.09.011
    [11]
    ZHAO Ju-feng, CHEN Yue-ting, FENG Hua-jun, et al. Infrared image enhancement through saliency feature analysis based on multi-scale decomposition[J]. Infrared Physics and Technology, 2014, 62: 86-93. doi: 10.1016/j.infrared.2013.11.008
    [12]
    BAI X Z, ZHOU F G. Top-hat selection transformation for infrared dim small target enhancement[J]. The Imaging Science Journal, 2010, 58(2): 112-117. doi: 10.1179/136821909X12581187860176
    [13]
    ZUO Chao, CHEN Qian, LIU Ning, et al. Display and detail enhancement for high-dynamic-range infrared images[J]. Optical Engineering, 2011, 50(12): 1-9.
    [14]
    LIU Ning, ZHAO Dong-xue. Detail enhancement for highdynamic-range infrared images based on guided image filter[J]. Infrared Physics and Technology, 2014, 67: 138-147. doi: 10.1016/j.infrared.2014.07.013
    [15]
    ZHAO Wen-da, XU Zhi-jun, ZHAO Jian, et al. Infrared image detail enhancement based on the gradient field specification[J]. Applied Optics, 2014, 53(19): 4141-4149. doi: 10.1364/AO.53.004141
    [16]
    ZHAO Ju-feng, CHEN Yue-ting, FENG Hua-jun, et al. Fast image enhancement using multi-scale saliency extraction in infrared imagery[J]. Optik, 2014, 125(15): 4039-4042. doi: 10.1016/j.ijleo.2014.01.117
    [17]
    VICKERS V E. Plateau equalization algorithm for real-time display of high-quality infrared imagery[J]. Optical Engineering, 1996, 35(7): 1921-1926. doi: 10.1117/1.601006
    [18]
    WANG Bing-jian, LIU Shang-qian, LI Qing, et al. A realtime contrast enhancement algorithm for infrared images based on plateau histogram[J]. Infrared Physics and Technology, 2006, 48(1): 77-82. doi: 10.1016/j.infrared.2005.04.008
    [19]
    HE Kai-ming, SUN Jian, Tang Xiao-ou. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353. doi: 10.1109/TPAMI.2010.168
    [20]
    周雨薇, 陈强, 孙权森, 等. 结合暗通道原理和双边滤波的遥感图像增强[J]. 中国图象图形学报, 2014, 19(2): 313-321. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201402018.htm

    ZHOU Yu-wei, CHEN Qiang, SUN Quan-sen, et al. Remote sensing image enhancement based on dark channel prior and bilateral filtering[J]. Journal of Image and Graphics, 2014, 19(2): 313-321. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB201402018.htm
    [21]
    HUANG S C, CHENG F C, CHIU Y S. Efficient contrast enhancement using adaptive Gamma correction with weighting distribution[J]. IEEE Transactions on Image Processing, 2013, 22(3): 1032-1041. doi: 10.1109/TIP.2012.2226047
    [22]
    DENG Guang. A generalized gamma correction algorithm based on the SLIP model[J]. EURASIP Journal on Advances in Signal Processing, 2016, 2016(1): 1-15. doi: 10.1186/s13634-015-0293-z
    [23]
    RAHMAN S, RAHMAN M M, ABDULLAH-AL-WADUD M, et al. An adaptive gamma correction for image enhancement[J]. EURASIP Journal on Image and Video Processing, 2016, 2016(1): 1-13.
    [24]
    JIANG G, WONG C Y, LIN S C F, et al. Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach[J]. Journal of Modern Optics, 2015, 62(7): 536-547. doi: 10.1080/09500340.2014.991358
    [25]
    GUPTA B, TIWARI M. Minimum mean brightness error contrast enhancement of color images using adaptive gamma correction with color preserving framework[J]. Optik, 2016, 127(4): 1671-1676. doi: 10.1016/j.ijleo.2015.10.068
    [26]
    符富强. 基于NURBS曲线的GAMMA校正技术的研究与应用[D]. 西安: 西安电子科技大学, 2010.

    FU Fu-qiang. Research and application of GAMMA calibration technology based on NURBS curve[D]. Xi'an: Xidian University, 2010. (in Chinese).
    [27]
    马琳, 王钧慧, 王宽全, 等. 基于特征图规正的虹膜图像自适应Gamma校正方法[J]. 燕山大学学报, 2010, 34(2): 173-179. https://www.cnki.com.cn/Article/CJFDTOTAL-DBZX201002019.htm

    MA Lin, WANG Jun-hui, WANG Kuan-quan, et al. Adaptive Gamma correction method of iris image based on characteristic pattern[J]. Journal of Yanshan University, 2010, 34(2): 173-179. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DBZX201002019.htm
    [28]
    储清翠, 王华彬, 陶亮. 图像的局部自适应Gamma校正[J]. 计算机工程与应用, 2015, 51(7): 189-193, 208. https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201507037.htm

    CHU Qing-cui, WANG Hua-bin, TAO Liang. Local adaptive Gamma correction method[J]. Computer Engineering and Applications, 2015, 51(7): 189-193, 208. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSGG201507037.htm
    [29]
    李渤, 朱梅, 樊中奎, 等. 非均匀光照图像自适应Gamma增强算法[J]. 南昌大学学报: 理科版, 2016, 40(3): 299-302. https://www.cnki.com.cn/Article/CJFDTOTAL-NCDL201603017.htm

    LI Bo, ZHU Mei, FAN Zhong-kui, et al. An adaptive gamma enhancement algorithm for non-uniform illumination images[J]. Journal of Nanchang University: Natural Science, 2016, 40(3): 299-302. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-NCDL201603017.htm
    [30]
    张曙. 自然环境下交通标志的检测及识别算法研究[D]. 武汉: 武汉理工大学, 2014.

    ZHANG Shu. Detection and recognition algorithm research of traffic signs in natural environments[D]. Wuhan: Wuhan University of Technology, 2014. (in Chinese).
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (3459) PDF downloads(2399) Cited by()
    Proportional views
    Related

    Copyright《Journal of Traffic and Transportation Engineering》编辑部陕ICP备05001904号-1

    Address ：Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi（710064） Tel：029-82334388 Email：jygc@chd.edu.cn

    All visit:Today's visit:

    Supported by: Beijing Renhe Information Technology Co. Ltd    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return