搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

时变复杂背景自由运动目标的高灵敏追迹成像

许明伟 杜康 李可 王飞翔 肖体乔

引用本文:
Citation:

时变复杂背景自由运动目标的高灵敏追迹成像

许明伟, 杜康, 李可, 王飞翔, 肖体乔

High sensitivity tracking of free-moving targets in time-varying complex backgrounds

Xu Ming-Wei, Du Kang, Li Ke, Wang Fei-Xiang, Xiao Ti-Qiao
PDF
HTML
导出引用
  • 复杂背景下低可见度目标追迹是成像领域的一个重要研究方向, 现有方法难以对运动方向和速率均无规则变化的低可见度目标进行追迹成像. 运动衬度成像可大幅提升目标追迹的灵敏度, 已在X射线成像领域取得重要应用, 但仅局限于固定轨迹或单调背景的成像. 本文将运动衬度成像引入到时变复杂背景中轨迹不确定的目标追迹成像任务, 通过解决现有方法受复杂背景和高频噪声干扰严重的问题, 实现目标的高灵敏追迹成像. 天空和树林中飞鸟的追迹结果表明, 该方法能有效地消除野外自然光和树叶无规则摆动导致背景灰度无规则变化的影响, 实现时变复杂背景中自由运动弱信号小目标的高灵敏追迹成像. 本文发展的方法有望为低可见度目标追迹成像提供一种新的手段.
    Tracking of low-visibility targets in complex backgrounds is an important research field, where existing methods struggle to image low-visibility targets with irregular changes in moving direction and speed. Move contrast imaging can greatly improve the sensitivity of target tracking, which has achieved important applications in the field of X-ray imaging, including high-resolution imaging to microvessels in living rats with the help of contrast agents, in-situ dynamic observation of ion migration and redox reactions during electrochemical reactions, and water refilling along vessels in willow branch without resorting to agents. However, all these applications are limited to imaging with fixed trajectories or monotonous backgrounds. In principle, move contrast imaging is based on the frequency spectral characteristics of the time-domain grayscale signal and is highly sensitive to moving components, which is wavelength-independent. This paper extends the move contrast imaging to the visible light waveband for tracking free-moving targets in time-varying complex backgrounds. To meet the need for tracking imaging of free-moving targets in complex backgrounds, we develop a move contrast imaging (MCI) method based on continuous wavelet transform (CWT) and Hilbert-Huang transform (HHT) with high discriminatory capability for non-stationary signals. Selecting birds in the sky and forest for the tracking imaging, the irregular grayscale changes caused by natural light intensity in the wild field and random swaying of tree leaves result in complex imaging backgrounds. The tracing results of low-visibility free-moving targets show that FT-MCI method, CWT-MCI method and HHT-MCI method can improve the target tracing imaging sensitivity by 179.9 times, 175.8 times and 214.6 times compared with temporal subtraction imaging, respectively. The results of tracking imaging of free-moving targets in complex backgrounds show that compared with the FT-MCI method and CWT-MCI method, the HHT-MCI method can further effectively suppress the influence of background noise on tracking imaging of targets of interest, thus achieving high sensitivity imaging of free-moving targets in time-varying complex backgrounds. Combining the phase diagram of FT-MCI and the imaging parameters, we can further show the motion direction, the motion speed or the distance from the observation point. Therefore, the HHT-MCI imaging method developed in this paper is expected to provide a novel method for tracking free-moving targets in time-varying complex backgrounds.
      通信作者: 肖体乔, tqxiao@sari.ac.cn
    • 基金项目: 国家重点基础研究发展计划(批准号: 2022YFA1603601, 2021YFF0601203, 2021YFA1600703)和国家自然科学基金青年科学基金(批准号: 12205361)资助的课题.
      Corresponding author: Xiao Ti-Qiao, tqxiao@sari.ac.cn
    • Funds: Project supported by the National Key Research and Development Program of China (Grant Nos. 2022YFA1603601, 2021YFF0601203, 2021YFA1600703) and the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 12205361).
    [1]

    Cheng Y H, Wang J 2014 AMM 490 1283Google Scholar

    [2]

    徐艳, 王培光, 杨青, 董江涛 2019 68 164203Google Scholar

    Xu Y, Wang P G, Yang Q, Dong J T 2019 Acta Phys. Sin. 68 164203Google Scholar

    [3]

    沈瑜, 王新新 2017 自动化与仪器仪表 4 122Google Scholar

    Shen Y, X. W X 2017 Autom. Instrum. 4 122Google Scholar

    [4]

    Husein A M, Calvin, Halim D, Leo R, William 2019 J. Phys. Conf. Ser. 1230 012017Google Scholar

    [5]

    Markandey V, Reid A, Wang S 1996 IEEE Trans Aerosp. Electron. Syst. 32 866Google Scholar

    [6]

    崔智高, 王华, 李艾华, 王涛, 李辉 2017 66 084203Google Scholar

    Cui Z G, Wang H, Li A H, Wang T, Li H 2017 Acta Phys. Sin. 66 084203Google Scholar

    [7]

    袁国武, 陈志强, 龚健, 徐丹, 廖仁健, 何俊远 2013 小型微型计算机系统 34 668

    Yuan G W, Chen Z Q, Gong J, Xu D, Liao R J, He J Y 2013 J. Chin. Comput. Syst. 34 668

    [8]

    Han X W, Gao Y, Zheng L, Zhang Z M, Niu D 2015 Fifth International Conference on Instrumentation & Measurement, Computer, Communication, and Control (IMCCC) Qinhuangdao, China, September 18–20, 2015 p579

    [9]

    连可, 严明, 李丹, 王厚军 2011 电讯技术 51 49

    Lian K, Yan M, Li D, Wang H J 2011 Telecommun. Eng. 51 49

    [10]

    Dong X B, Huang X S, Zheng Y B, Bai S J, Xu W Y 2014 Infrared Phys. Technol. 65 36Google Scholar

    [11]

    张弘, 赵保军, 毛二可, 朱梦宇 2001 红外与激光工程 30 96

    Zhang H, Zhao B J, Mao E K, Zhu M Y 2001 Infrared Laser Eng. 30 96

    [12]

    Lü P Y, Sun S L, Lin C Q, Liu G R 2018 Infrared Phys. Technol. 91 107Google Scholar

    [13]

    Wu Y, Yang Z, Niu W L, Zheng W 2018 IGARSS Valencia, Spain, July 22−27, 2018, p7066

    [14]

    郑晓枫 2015 硕士学位论文 (杭州: 杭州电子科技大学)

    Zheng X F 2015 M. S. Thesis (Hangzhou: Hangzhou Dianzi University) (in Chinese)

    [15]

    吕腾蛟, 袁子乔, 雷刚, 任泽宇 2021 火控雷达技术 50 78Google Scholar

    Lyu T J, Yuan Z Q, Lei G, Ren Z Y 2021 Fire Contrl Radar Technol. 50 78Google Scholar

    [16]

    Liu B, J L, Li X R 2016 IEEE Trans. Signal Process. 64 3221Google Scholar

    [17]

    王海梅, 洪敏 2018 火力与指挥控制 43 78

    Wang H M, Hong M 2018 Fire Control & Command Control 43 78

    [18]

    Ward M 2011 IEEE Aerospace Conference. Big Sky, Montana, USA, March 05–12, 2011 p1

    [19]

    侯旺, 于起峰, 雷志辉, 刘晓春 2014 63 074208Google Scholar

    Hou W, Yu Q F, Lei Z H, Liu X C 2014 Acta Phys. Sin. 63 074208Google Scholar

    [20]

    Wang F X, Zhou P T, Li K, et al. 2020 IUCrJ 7 793Google Scholar

    [21]

    李可 2021 博士学位论文 (北京: 中国科学院大学)

    Li K 2021 Ph. D. Dissertation (Beijing: University of Chinese Academy of Sciences) (in Chinese)

    [22]

    鞠晓璐, 李可, 余福成, 许明伟, 邓彪, 李宾, 肖体乔 2022 71 144101Google Scholar

    Ju X L, Li K, Yu F C, Xu M W, Deng B, Li B, Xiao T Q 2022 Acta Phys. Sin. 71 144101Google Scholar

    [23]

    Aguiar-Conraria L, Soares M J 2011 The Continuous Wavelet Transform: A Primer (NIPE-Universidade do Minho) No. 16/2011

    [24]

    Sadowsky J 1994 Johns Hopkins APL. Tech. Digest 15 306

    [25]

    Huang N E, Shen Z, Long S R, et al. 1998 Proc. R. Soc. A-Math. Phys. Eng. Sci. 454 903Google Scholar

    [26]

    Guan J, Zhang J, Liu N B, Li B 2009 IEEE Rad Conf Pasadena, CA, USA, May 04–08, 2009 p1

    [27]

    Huang N E, Wu Z H 2008 Rev. Geophys. 46 RG2006Google Scholar

    [28]

    Huang N E, Shen S S P 2014 Hilbert Huang Transform and its Applications (2nd Ed.) (Singapore: World Scientific) p13

    [29]

    孙玉宇 2007 硕士学位论文 (哈尔滨: 哈尔滨工业大学)

    Sun Y Y 2007 M. S. Thesis (Harbin: Harbin Industrial University) (in Chinese)

    [30]

    Bruderer B, Boldt A 2001 Ibis 143 178Google Scholar

    [31]

    张园, 谢红兰, 杜国浩, 许明伟, 薛艳玲, 肖体乔 2021 核技术 44 060101

    Zhang Y, Xie H L, Du G H, Xu M W, Xue Y L, Xiao T Q 2021 Nucl. Tech. 44 060101

  • 图 1  时序图像数据采集示意图

    Fig. 1.  Schematic diagram of time sequence image data acquisition.

    图 2  低可见度目标的时频分析结果 (a) 原始图像及4个特征点; (b) 图(a)中蓝色虚线位置的灰度轮廓曲线, 黑色曲线代表背景, 红色曲线代表鸟飞过时的灰度分布; (c) 图(a)中标示的4个特征点傅里叶变换频谱; (d)飞鸟、(e)建筑物、(f)黄浦江以及(g)天空的连续小波变换时频图; (h)飞鸟、(i)建筑物、(j)黄浦江以及(k)天空的希尔伯特-黄变换时频图

    Fig. 2.  Low visibility target image and time-frequency analysis: (a) Raw image and 4 feature points; (b) grayscale line profile at the position of blue dashed line in panel (a), where the black and red curve represent before and after the bird’s flight, respectively; (c) Fourier transform spectrum of 4 feature points marked in panel (a); continuous Wavelet transform time-frequency graphs of (d) flying bird, (e) house, (f) Huangpu River and (g) sky marked in panel (a); Hilbert-Huang transform time-frequency graphs of (h) flying bird, (i) buildings, (j) Huangpu River and (k) sky marked in panel (a).

    图 3  基于不同频谱分析方法的运动衬度成像结果比对 (a) TSI, (b) FT-MCI, (c) CWT-MCI和(d) HHT-MCI成像结果与原始图像融合, 从红到蓝的颜色变化代表目标位置随时间的演化; (e) 图(a)—(d)白色虚线标记处目标轨迹的归一化灰度分布轮廓曲线

    Fig. 3.  Comparison of move contrast imaging results based on different spectral analysis methods. The imaging results of (a) TSI, (b) FT-MCI, (c) CWT-MCI and (d) HHT-MCI merged with raw image, and the color evolution from red to blue indicates the change of target position over time. (e) Normalized grayscale line profile of target trajectory marked by white dashed line in panel (a)–(d).

    图 B2  (a)时间减影和(b)—(d)运动衬度成像对平均速度的估算结果

    Fig. B2.  Average speed estimation based on (a) time subtraction imaging and (b)–(d) move contrast imaging.

    图 4  FT-MCI对时变复杂背景自由运动目标的追迹成像结果 (a)原始图像; (b)时间减影图像; (c)原始图像和时间减影图像标准差随帧数的变化; (d)基于傅里叶变换的运动衬度图像, 黄色箭头标示飞鸟轨迹位置

    Fig. 4.  FT-MCI imaging results of target trajectory in time-varying complex background: (a) Raw image; (b) time subtraction image; (c) the evolution of standard deviation of raw image and time subtraction image with the number of frames; (d) move contrast image based on Fourier transform, and yellow arrow marked the location of bird trajectory.

    图 5  目标特征点的时频分析结果 (a) 原始图像及4个特征点; (b) 图(a)中标记的4个特征点的傅里叶变换频谱; (c) 飞鸟、(d) 建筑物、(e) 天空以及(f) 树林的连续小波变换时频图; (g) 飞鸟、(h) 建筑物、(i) 天空及(j) 树林的希尔伯特-黄变换时频图

    Fig. 5.  Time-frequency analysis of target feature points: (a) Raw image and 4 feature points; (b) Fourier transform spectrum of 4 feature points marked in panel (a); (c)–(f) continuous wavelet transform time-frequency graphs of (c) flying bird, (d) house, (e) sky and (f) tree marked in panel (a); (g)–(j) Hilbert-Huang transform time-frequency graphs of (g) flying bird, (h) house, (i) sky, and (j) tree marked in panel (a).

    图 6  HHT-MCI对时变复杂背景中自由运动目标的追迹成像结果 (a)飞鸟轨迹运动衬度像; (b)运动衬度图像与原始图像的融合

    Fig. 6.  Target tracking results under complex background: (a) Bird trajectories obtained by HHT-MCI; (b) fusion of HHT-MCI, FT-MCI and raw image.

    图 B1  成像模型

    Fig. B1.  Imaging model.

    表 1  不同方法对低可见度目标追迹成像效果比较

    Table 1.  Comparison of relative contrast in tracking imaging of low-visibility targets.

    Evaluating
    indicator
    TSIFT-MCICWT-MCIHHT-MCI
    CR0.00460.82750.80880.9873
    Improvement179.9175.8214.6
    下载: 导出CSV
    Baidu
  • [1]

    Cheng Y H, Wang J 2014 AMM 490 1283Google Scholar

    [2]

    徐艳, 王培光, 杨青, 董江涛 2019 68 164203Google Scholar

    Xu Y, Wang P G, Yang Q, Dong J T 2019 Acta Phys. Sin. 68 164203Google Scholar

    [3]

    沈瑜, 王新新 2017 自动化与仪器仪表 4 122Google Scholar

    Shen Y, X. W X 2017 Autom. Instrum. 4 122Google Scholar

    [4]

    Husein A M, Calvin, Halim D, Leo R, William 2019 J. Phys. Conf. Ser. 1230 012017Google Scholar

    [5]

    Markandey V, Reid A, Wang S 1996 IEEE Trans Aerosp. Electron. Syst. 32 866Google Scholar

    [6]

    崔智高, 王华, 李艾华, 王涛, 李辉 2017 66 084203Google Scholar

    Cui Z G, Wang H, Li A H, Wang T, Li H 2017 Acta Phys. Sin. 66 084203Google Scholar

    [7]

    袁国武, 陈志强, 龚健, 徐丹, 廖仁健, 何俊远 2013 小型微型计算机系统 34 668

    Yuan G W, Chen Z Q, Gong J, Xu D, Liao R J, He J Y 2013 J. Chin. Comput. Syst. 34 668

    [8]

    Han X W, Gao Y, Zheng L, Zhang Z M, Niu D 2015 Fifth International Conference on Instrumentation & Measurement, Computer, Communication, and Control (IMCCC) Qinhuangdao, China, September 18–20, 2015 p579

    [9]

    连可, 严明, 李丹, 王厚军 2011 电讯技术 51 49

    Lian K, Yan M, Li D, Wang H J 2011 Telecommun. Eng. 51 49

    [10]

    Dong X B, Huang X S, Zheng Y B, Bai S J, Xu W Y 2014 Infrared Phys. Technol. 65 36Google Scholar

    [11]

    张弘, 赵保军, 毛二可, 朱梦宇 2001 红外与激光工程 30 96

    Zhang H, Zhao B J, Mao E K, Zhu M Y 2001 Infrared Laser Eng. 30 96

    [12]

    Lü P Y, Sun S L, Lin C Q, Liu G R 2018 Infrared Phys. Technol. 91 107Google Scholar

    [13]

    Wu Y, Yang Z, Niu W L, Zheng W 2018 IGARSS Valencia, Spain, July 22−27, 2018, p7066

    [14]

    郑晓枫 2015 硕士学位论文 (杭州: 杭州电子科技大学)

    Zheng X F 2015 M. S. Thesis (Hangzhou: Hangzhou Dianzi University) (in Chinese)

    [15]

    吕腾蛟, 袁子乔, 雷刚, 任泽宇 2021 火控雷达技术 50 78Google Scholar

    Lyu T J, Yuan Z Q, Lei G, Ren Z Y 2021 Fire Contrl Radar Technol. 50 78Google Scholar

    [16]

    Liu B, J L, Li X R 2016 IEEE Trans. Signal Process. 64 3221Google Scholar

    [17]

    王海梅, 洪敏 2018 火力与指挥控制 43 78

    Wang H M, Hong M 2018 Fire Control & Command Control 43 78

    [18]

    Ward M 2011 IEEE Aerospace Conference. Big Sky, Montana, USA, March 05–12, 2011 p1

    [19]

    侯旺, 于起峰, 雷志辉, 刘晓春 2014 63 074208Google Scholar

    Hou W, Yu Q F, Lei Z H, Liu X C 2014 Acta Phys. Sin. 63 074208Google Scholar

    [20]

    Wang F X, Zhou P T, Li K, et al. 2020 IUCrJ 7 793Google Scholar

    [21]

    李可 2021 博士学位论文 (北京: 中国科学院大学)

    Li K 2021 Ph. D. Dissertation (Beijing: University of Chinese Academy of Sciences) (in Chinese)

    [22]

    鞠晓璐, 李可, 余福成, 许明伟, 邓彪, 李宾, 肖体乔 2022 71 144101Google Scholar

    Ju X L, Li K, Yu F C, Xu M W, Deng B, Li B, Xiao T Q 2022 Acta Phys. Sin. 71 144101Google Scholar

    [23]

    Aguiar-Conraria L, Soares M J 2011 The Continuous Wavelet Transform: A Primer (NIPE-Universidade do Minho) No. 16/2011

    [24]

    Sadowsky J 1994 Johns Hopkins APL. Tech. Digest 15 306

    [25]

    Huang N E, Shen Z, Long S R, et al. 1998 Proc. R. Soc. A-Math. Phys. Eng. Sci. 454 903Google Scholar

    [26]

    Guan J, Zhang J, Liu N B, Li B 2009 IEEE Rad Conf Pasadena, CA, USA, May 04–08, 2009 p1

    [27]

    Huang N E, Wu Z H 2008 Rev. Geophys. 46 RG2006Google Scholar

    [28]

    Huang N E, Shen S S P 2014 Hilbert Huang Transform and its Applications (2nd Ed.) (Singapore: World Scientific) p13

    [29]

    孙玉宇 2007 硕士学位论文 (哈尔滨: 哈尔滨工业大学)

    Sun Y Y 2007 M. S. Thesis (Harbin: Harbin Industrial University) (in Chinese)

    [30]

    Bruderer B, Boldt A 2001 Ibis 143 178Google Scholar

    [31]

    张园, 谢红兰, 杜国浩, 许明伟, 薛艳玲, 肖体乔 2021 核技术 44 060101

    Zhang Y, Xie H L, Du G H, Xu M W, Xue Y L, Xiao T Q 2021 Nucl. Tech. 44 060101

  • [1] 吴长茂, 唐熊忻, 夏媛媛, 杨瀚翔, 徐帆江. 用于空间相机设计的高精度光线追迹方法.  , 2023, 72(8): 084201. doi: 10.7498/aps.72.20222463
    [2] 陈子涵, 宋梦齐, 陈恒, 王志立. 双三角形相位光栅X射线干涉仪的条纹可见度.  , 2023, 72(14): 148701. doi: 10.7498/aps.72.20230461
    [3] 鞠晓璐, 李可, 余福成, 许明伟, 邓彪, 李宾, 肖体乔. 电解池电化学反应过程的运动衬度X射线成像.  , 2022, 71(14): 144101. doi: 10.7498/aps.71.20220339
    [4] 柳雪玲, 田进寿, 田丽萍, 陈萍, 张敏睿, 薛彦华, 李亚晖, 方玉熳, 徐向晏, 刘百玉, 缑永胜. 一种高偏转灵敏度同步扫描条纹管.  , 2021, 70(21): 218502. doi: 10.7498/aps.70.20210814
    [5] 张敬娜, 张慧滔, 徐文峰, 朱溢佞, 邓世沃, 朱佩平. 微分相位衬度计算机层析成像的感兴趣区域重建方法.  , 2021, 70(11): 118702. doi: 10.7498/aps.70.20202192
    [6] 姚春霞, 何其利, 张锦, 付天宇, 吴朝, 王山峰, 黄万霞, 袁清习, 刘鹏, 王研, 张凯. 免分析光栅一次曝光相位衬度成像方法.  , 2021, 70(2): 028701. doi: 10.7498/aps.70.20201170
    [7] 雒亮, 夏辉, 刘俊圣, 费家乐, 谢文科. 基于元胞自动机的气动光学光线追迹算法.  , 2020, 69(19): 194201. doi: 10.7498/aps.69.20200532
    [8] 范启蒙, 尹成友. 高对比度目标的电磁逆散射超分辨成像.  , 2018, 67(14): 144101. doi: 10.7498/aps.67.20180266
    [9] 王盼盼, 姚旭日, 刘雪峰, 俞文凯, 邱棚, 翟光杰. 基于行扫描测量的运动目标压缩成像.  , 2017, 66(1): 014201. doi: 10.7498/aps.66.014201
    [10] 张腾飞, 杨晶, 侯岩雪, 王伟伟, 赵巍, 张景园, 崔大复, 彭钦军, 许祖彦. 基于光参量变频与放大的高灵敏红外成像技术.  , 2016, 65(1): 014209. doi: 10.7498/aps.65.014209
    [11] 杨孝敬, 杨阳, 李淮周, 钟宁. 基于模糊近似熵的抑郁症患者静息态功能磁共振成像信号复杂度分析.  , 2016, 65(21): 218701. doi: 10.7498/aps.65.218701
    [12] 侯旺, 梅风华, 陈国军, 邓喜文. 基于背景最佳滤波尺度的红外图像复杂度评价准则.  , 2015, 64(23): 234202. doi: 10.7498/aps.64.234202
    [13] 高文, 汤洋, 朱明. 复杂背景下目标检测的级联分类器算法研究.  , 2014, 63(9): 094204. doi: 10.7498/aps.63.094204
    [14] 吴健雄, 程腾, 张青川, 高杰, 伍小平. 光学读出红外成像中面光源影响下的光学检测灵敏度研究.  , 2013, 62(22): 220703. doi: 10.7498/aps.62.220703
    [15] 王驰, 毕书博, 王利, 夏学勤, 丁卫, 于瀛洁. 超小自聚焦光纤探头研究用场追迹数值模拟技术.  , 2013, 62(2): 024217. doi: 10.7498/aps.62.024217
    [16] 陈灿, 佟亚军, 谢红兰, 肖体乔. Laue弯晶聚焦特性的光线追迹研究.  , 2012, 61(10): 104102. doi: 10.7498/aps.61.104102
    [17] 杨强, 刘鑫, 郭金川, 雷耀虎, 黄建衡, 牛憨笨. 无吸收光栅的X射线相位衬度成像实验研究.  , 2012, 61(16): 160702. doi: 10.7498/aps.61.160702
    [18] 陈 敏, 肖体乔, 骆玉宇, 刘丽想, 魏 逊, 杜国浩, 徐洪杰. 微聚焦管硬x射线位相衬度成像.  , 2004, 53(9): 2953-2957. doi: 10.7498/aps.53.2953
    [19] 黄万霞, 田玉莲, 朱佩平, 麦振洪, 胡小方. 北京同步辐射装置上的位相衬度成像.  , 2002, 51(5): 1040-1043. doi: 10.7498/aps.51.1040
    [20] 曹念文, 刘文清, 张玉钧. 偏振成像技术提高成像清晰度、成像距离的定量研究.  , 2000, 49(1): 61-66. doi: 10.7498/aps.49.61
计量
  • 文章访问数:  3204
  • PDF下载量:  94
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-03-10
  • 修回日期:  2023-05-06
  • 上网日期:  2023-05-25
  • 刊出日期:  2023-08-05

/

返回文章
返回
Baidu
map