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基于行扫描测量的运动目标压缩成像

王盼盼 姚旭日 刘雪峰 俞文凯 邱棚 翟光杰

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基于行扫描测量的运动目标压缩成像

王盼盼, 姚旭日, 刘雪峰, 俞文凯, 邱棚, 翟光杰

Moving target compressive imaging based on improved row scanning measurement matrix

Wang Pan-Pan, Yao Xu-Ri, Liu Xue-Feng, Yu Wen-Kai, Qiu Peng, Zhai Guang-Jie
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  • 运动目标成像在实际应用中具有重要作用,而如何获取高质量运动目标图像是该领域研究中的一个热点问题.本文采用行扫描采样的方式,通过构造运动测量矩阵,建立一种基于压缩感知理论的运动物体成像模型,并通过仿真及实验,验证了该模型对于恢复运动物体图像信息的可行性.实验结果证明,该方法可获得高质量的运动物体成像.通过引入图像质量评价标准,分析了运动物体成像质量与速度之间的关系.将该方法与普通压缩感知算法进行比较,结果证明,在相同速度下,该方法的成像质量更高.该方法在无人机对地观测、产品线视频监测等领域有着很好的应用前景.
    Moving target imaging(MTI) plays an important role in practical applications. How to capture dynamic images of the targets with high qualities has become a hot point of research in the field of MTI. In order to improve the reconstruction quality, a new MTI model based on compressed sensing(CS) is proposed here, by using a sampling protocol of the row-scanning together with a motion measurement matrix constructed by us. It is proved by the simulation and the experimental results that a relatively high quality can be achieved through this approach. Furthermore, an evaluation criterion of reconstructed image is introduced to analyze the relationship between the imaging quality and the moving speed of the target. By contrast, the performance of our algorithm is much better than that of traditional CS algorithm under the same moving speed condition. As a result, it is suggested that our imaging method may have a great application prospect in the earth observation of unmanned aerial vehicles, video monitoring in the product line and other fields.
      通信作者: 翟光杰, gjzhai@nssc.ac.cn
    • 基金项目: 国家重大科学仪器设备开发专项(批准号:2013YQ030595)、国家高技术研究发展计划(批准号:2013AA122902)、国家自然科学基金(批准号:61575207)和中国科学院国防科技创新基金项目(批准号:CXJJ-16S047)资助的课题.
      Corresponding author: Zhai Guang-Jie, gjzhai@nssc.ac.cn
    • Funds: Project supported by the National Major Scientific Instruments Development Project of China(Grant No. 2013YQ030595), the Hi-Tech Research and Development Program of China(Grant No. 2013AA122902), the National Natural Science Foundation of China(Grant No. 61575207), and the National Defense Science and Technology Innovation Fund of Chinese Academy of Sciences(Grant No. CXJJ-16S047).
    [1]

    Candès E J, Romberg J, Tao T 2006 IEEE Trans. Inf. Theory 52 489

    [2]

    Donoho D L 2004 IEEE Trans. Inf. Theory 52 1289

    [3]

    Candès E J 2006 Proc. Int. Congr. Math. 3 1433

    [4]

    Romberg J 2008 IEEE Signal Process. Mag. 25 14

    [5]

    Duarte M F, Davenport M A, Takhar D, Laska J N, Sun T, Kelly K F, Baraniuk R G 2008 IEEE Signal Process. Mag. 25 83

    [6]

    Takhar D, Laska J N, Wakin M B, Duarte M F, Baron D, Sarvotham S, Kelly K F, Baraniuk R G 2010 Proc. SPIE San Jose, CA, USA, Feb. 2, 2006 p43

    [7]

    Candès E J, Romberg J, Tao T 2006 Commun. Pure Appl. Math. 59 1027

    [8]

    Howland G A, Howell J C 2013 Phys. Rev. X 3 1071

    [9]

    Zhao C Q, Gong W L, Chen M L, Li E R, Wang H, Xu W D, Han S S 2012 Appl. Phys. Lett. 101 141123

    [10]

    Chen G H, Tang J, Leng S H 2008 Med. Phys. 35 660

    [11]

    Gross D, Liu Y K, Flammia S T, Becker S, Eisert J 2010 Phys. Rev. Lett. 105 2903

    [12]

    Zhu L, Zhang W, Elnatan D, Huang B 2012 Nat. Methods 9 721

    [13]

    Wu Y, Mirza I O, Arce G R, Prather D W 2011 Opt. Lett. 36 2692

    [14]

    Arce G R, Brady D J, Carin L, Arguello H, Kittle D S 2014 IEEE Signal Process. Mag. 31 105

    [15]

    Spagnolo P, Orazio T D, Leo M, Distante A 2006 Image Vis. Comp. 24 411

    [16]

    Zhang C, Gong W L, Han S S 2012 Chin. J. Lasers 12 204 (in Chinese)[张聪, 龚文林, 韩申生2012中国激光12 204]

    [17]

    Li X H, Deng C J, Chen M L, Gong W L, Han S S 2015 Photon. Res. 3 153

    [18]

    Li E R, Bo Z W, Chen M L, Gong W L, Han S S 2014 Appl. Phys. Lett. 104 251120

    [19]

    Yan F X, Zhu J B, Liu J Y 2014 Spacecraft Recovery & Remote Sensing 35 54 (in Chinese)[严奉霞, 朱炬波, 刘吉英2014航天返回与遥感35 54]

    [20]

    Liu J Y, Zhu J B, Yan F X, Zhang Z 2013 Inverse Probl.Imag. 4 1295

    [21]

    Yu W K, Yao X R, Liu X F, Li L Z, Zhai G J 2015 Appl. Opt. 54 4249

    [22]

    Yu W K, Yao X R, Liu X F, Lan R M, Wu L A, Zhai G J 2016 Opt. Comm. 371 105

    [23]

    Yu W K, Liu X F, Yao X R, Wang C 2014 Sci. Rep. 4 5834

    [24]

    Yu W K, Liu X F, Yao X R, Wang C, Zhai G J, Zhao Q 2014 Phys. Lett. A 378 3406

    [25]

    Ri S, Fujigaki M, Matui T, Morimoto Y 2006 Appl. Opt. 45 6940

    [26]

    Chan W L, Charan K, Takhar D, Kelly K F, Baraniuk R G, Mittleman D M 2008 Appl. Phys. Lett. 93 121105

    [27]

    Howland G A, Dixon P B, Howell J C 2011 Appl. Opt. 50 5917

    [28]

    Gonzalez R C, Woods R E(translated by Ruan Q Q, Ruan Y Z) 2010 Digital Image Processing (Beijing:Publishing House of Electronics Industry) pp40-55(in Chinese)[冈萨雷斯, 伍兹著(阮秋琦, 阮宇智译) 2013数字图像处理(北京:电子工业出版社)第40–55页]

    [29]

    Li M F, Zhang Y R, Luo K H, Fan H 2013 Phys. Rev. A 87 2285

    [30]

    Li M F, Zhang Y R, Fan H, Wu L A, Liu X F, Yao X R, Luo K H 2013 Appl. Phys. Lett. 103 211119

    [31]

    Yu W K, Li X, Yao X R, Liu X F, Wu L A, Zhai G J 2013 Appl. Opt. 52 7882

    [32]

    Gu Y F, Yan B, Li L, W F, Han Y, Chen J 2014 Acta Phys. Sin. 63 018701 (in Chinese)[古宇飞, 闫镔, 李磊, 魏峰, 韩玉, 陈健2014物理学报63 018701]

    [33]

    Yu W K, Li M F, Yao X R, Liu X F, Wu L A, Zhai G J 2014 Opt. Express 22 7133

    [34]

    Candès E J, Tao T 2005 IEEE Trans. Inf. Theory 51 4203

    [35]

    Baraniuk R G, Davenport M, Devore R A, Wakin M B 2008 Constr. Approx. 28 253

  • [1]

    Candès E J, Romberg J, Tao T 2006 IEEE Trans. Inf. Theory 52 489

    [2]

    Donoho D L 2004 IEEE Trans. Inf. Theory 52 1289

    [3]

    Candès E J 2006 Proc. Int. Congr. Math. 3 1433

    [4]

    Romberg J 2008 IEEE Signal Process. Mag. 25 14

    [5]

    Duarte M F, Davenport M A, Takhar D, Laska J N, Sun T, Kelly K F, Baraniuk R G 2008 IEEE Signal Process. Mag. 25 83

    [6]

    Takhar D, Laska J N, Wakin M B, Duarte M F, Baron D, Sarvotham S, Kelly K F, Baraniuk R G 2010 Proc. SPIE San Jose, CA, USA, Feb. 2, 2006 p43

    [7]

    Candès E J, Romberg J, Tao T 2006 Commun. Pure Appl. Math. 59 1027

    [8]

    Howland G A, Howell J C 2013 Phys. Rev. X 3 1071

    [9]

    Zhao C Q, Gong W L, Chen M L, Li E R, Wang H, Xu W D, Han S S 2012 Appl. Phys. Lett. 101 141123

    [10]

    Chen G H, Tang J, Leng S H 2008 Med. Phys. 35 660

    [11]

    Gross D, Liu Y K, Flammia S T, Becker S, Eisert J 2010 Phys. Rev. Lett. 105 2903

    [12]

    Zhu L, Zhang W, Elnatan D, Huang B 2012 Nat. Methods 9 721

    [13]

    Wu Y, Mirza I O, Arce G R, Prather D W 2011 Opt. Lett. 36 2692

    [14]

    Arce G R, Brady D J, Carin L, Arguello H, Kittle D S 2014 IEEE Signal Process. Mag. 31 105

    [15]

    Spagnolo P, Orazio T D, Leo M, Distante A 2006 Image Vis. Comp. 24 411

    [16]

    Zhang C, Gong W L, Han S S 2012 Chin. J. Lasers 12 204 (in Chinese)[张聪, 龚文林, 韩申生2012中国激光12 204]

    [17]

    Li X H, Deng C J, Chen M L, Gong W L, Han S S 2015 Photon. Res. 3 153

    [18]

    Li E R, Bo Z W, Chen M L, Gong W L, Han S S 2014 Appl. Phys. Lett. 104 251120

    [19]

    Yan F X, Zhu J B, Liu J Y 2014 Spacecraft Recovery & Remote Sensing 35 54 (in Chinese)[严奉霞, 朱炬波, 刘吉英2014航天返回与遥感35 54]

    [20]

    Liu J Y, Zhu J B, Yan F X, Zhang Z 2013 Inverse Probl.Imag. 4 1295

    [21]

    Yu W K, Yao X R, Liu X F, Li L Z, Zhai G J 2015 Appl. Opt. 54 4249

    [22]

    Yu W K, Yao X R, Liu X F, Lan R M, Wu L A, Zhai G J 2016 Opt. Comm. 371 105

    [23]

    Yu W K, Liu X F, Yao X R, Wang C 2014 Sci. Rep. 4 5834

    [24]

    Yu W K, Liu X F, Yao X R, Wang C, Zhai G J, Zhao Q 2014 Phys. Lett. A 378 3406

    [25]

    Ri S, Fujigaki M, Matui T, Morimoto Y 2006 Appl. Opt. 45 6940

    [26]

    Chan W L, Charan K, Takhar D, Kelly K F, Baraniuk R G, Mittleman D M 2008 Appl. Phys. Lett. 93 121105

    [27]

    Howland G A, Dixon P B, Howell J C 2011 Appl. Opt. 50 5917

    [28]

    Gonzalez R C, Woods R E(translated by Ruan Q Q, Ruan Y Z) 2010 Digital Image Processing (Beijing:Publishing House of Electronics Industry) pp40-55(in Chinese)[冈萨雷斯, 伍兹著(阮秋琦, 阮宇智译) 2013数字图像处理(北京:电子工业出版社)第40–55页]

    [29]

    Li M F, Zhang Y R, Luo K H, Fan H 2013 Phys. Rev. A 87 2285

    [30]

    Li M F, Zhang Y R, Fan H, Wu L A, Liu X F, Yao X R, Luo K H 2013 Appl. Phys. Lett. 103 211119

    [31]

    Yu W K, Li X, Yao X R, Liu X F, Wu L A, Zhai G J 2013 Appl. Opt. 52 7882

    [32]

    Gu Y F, Yan B, Li L, W F, Han Y, Chen J 2014 Acta Phys. Sin. 63 018701 (in Chinese)[古宇飞, 闫镔, 李磊, 魏峰, 韩玉, 陈健2014物理学报63 018701]

    [33]

    Yu W K, Li M F, Yao X R, Liu X F, Wu L A, Zhai G J 2014 Opt. Express 22 7133

    [34]

    Candès E J, Tao T 2005 IEEE Trans. Inf. Theory 51 4203

    [35]

    Baraniuk R G, Davenport M, Devore R A, Wakin M B 2008 Constr. Approx. 28 253

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出版历程
  • 收稿日期:  2016-07-05
  • 修回日期:  2016-09-27
  • 刊出日期:  2017-01-05

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