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激光相干场成像散斑噪声复合去噪方法

程志远 李治国 折文集 夏爱利

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激光相干场成像散斑噪声复合去噪方法

程志远, 李治国, 折文集, 夏爱利

Compound denoising method of laser speckle noise in laser inherent field imaging

Cheng Zhi-Yuan, Li Zhi-Guo, She Wen-Ji, Xia Ai-Li
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  • 噪声是影响激光相干场高分辨成像系统像质的重要因素, 激光相干场成像系统既受背景光加性噪声影响, 又受激光乘性散斑噪声影响. 为解决激光相干场成像系统受激光乘性散斑噪声和背景光加性噪声叠加引起的成像像质退化效应问题, 从噪声抑制角度提高激光相干场系统高分辨成像像质, 研究建立了激光散斑乘性噪声和背景光加性噪声对大气下行链路激光回波场信号影响干扰模型, 并基于该模型提出了一种基于同态滤波和稀疏基追踪级联复合去噪算法. 首先基于同态滤波理论将激光乘性散斑噪声转化为加性噪声, 再由高通滤波器滤除散斑噪声, 最后采用基追踪稀疏理论方法抑制背景光等加性噪声对像质的影响. 研究表明, 较现有单一去噪方法, 该级联复合去噪方法可一次性消除激光乘性散斑噪声和背景加性噪声两种不同性质的噪声, 有效改善了激光相干场成像质量.
    Noise is an important factor affecting the image quality of laser coherent field high resolution imaging system. And there exists not only background light additive noise but also laser multiplicative speckle noise in a laser coherent field imaging system. Both of the above noise affect the imaging quality of laser coherent field system. In order to improve the imaging quality from the perspective of noise suppression and settle the imaging quality degradation problem of laser multiplicative speckle noise and background additive noise in the laser coherent field imaging system, the model for the influence of multiplicative speckle noise and background additive noise on laser echo field demodulated signal is established in atmospheric downlink. Then, based on the model, a novel homomorphic filter and sparse matrix trace cascade compound de-noising algorithm is put forward. Firstly, based on the homomorphic filtering theory, the laser multiplicative speckle noise in the laser echo demodulated signal is converted into the additive noise by logarithmic transformation. Then the low-frequency laser multiplicative speckle noise is filtered by the high-pass filter, and the high-frequency demodulated signal is retained. The logarithmic inverse transform is used to obtain the laser echo demodulation signal after the multiplicative speckle noise has been filtered out. Next, the phase random disturbance of atmosphere in laser echo demodulated signal is suppressed by phase closure technology and the imaging spectrum component is reconstructed by the spectrum iterative reconstruction method. Then the high resolution image is obtained by spectrum component inverse Fourier transform. Finally, the effect of background additive noise on the image quality is suppressed by the sparse base tracking theory. The simulated and outdoor experiment result are used to verify the denoising effect and image quality enhancement effect of the composite de-noising method. Compared with the existing single denoising method, the composite denoising method is shown to be able to effectively eliminate laser multiplicative speckle noise and background additive noise at one time. The proposed method can improve image contrast and promote the Strehl ratio of imaging quality in a coherent imaging system. It provides a theoretical basis for improving imaging quality and denosing laser multiplicative speckle noise and background additive noise in coherent field imaging system.
      通信作者: 程志远, czy@opt.ac.cn
    • 基金项目: 国家自然科学基金(批准号: 61875257)和陕西省自然科学基金(批准号: 2017JM6035)资助的课题.
      Corresponding author: Cheng Zhi-Yuan, czy@opt.ac.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61875257) and the Natural Science Foundation of Shaanxi Province, China (Grant No. 2017JM6035).
    [1]

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    Zhu M M, Shi D F, Hu S S, Wang Y J 2017 Chinese Journal of Quantum Electronics 34 145

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    邓慧, 张蓉竹, 孙年春 2016 应用光学 36 0129002

    Deng H, Zhang R Z, Sun N C 2016 Journal of Applied Optics 36 0129002

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    Tian X P, Cheng X, Wu C M, Liu Y B 2015 Journal of Xi’an University of Posts and Telecommunications. 20 51

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    Zhang Y Y, Chen S T, Ge J X, Wan F Y, Mei Y, Zhou X Y 2017 Acta Phys. Sin. 66 129501Google Scholar

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    陈晔曜, 蒋刚毅, 邵华, 姜浩, 郁梅 2018 光电工程 45 180083Google Scholar

    Chen Y Y, Jiang G Y, Shao H, Jian H, Yu M 2018 Opto-Electronic Engineering 45 180083Google Scholar

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    Chiang J C, Kao P H, Chen Y S, et al. 2017 Circ. Syst. Signal Pr. 36 2786Google Scholar

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    Zhang K, Zuo W, Chen Y, Meng D, Zhang L 2017 IEEE Trans. Image Process. 26 3142Google Scholar

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    郝红星, 吴玲达, 宋晓瑞 2018 计算机学报 41 1Google Scholar

    Hao H X, Wu L D, Song X R 2018 Chienese Journal of Computers 41 1Google Scholar

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    沈晨, 张旻 2018 探测与控制学报 40 128

    Shen C, Zhang M 2018 Journal of Detection & Control 40 128

    [18]

    詹曙, 王俊, 杨福猛, 方琪 2015 电子学报 43 523Google Scholar

    Zhan S, Wang J, Yang F M, Fang Q 2015 Acta Electronic Sinica 43 523Google Scholar

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    Mairal J, Bach F, Ponce J 2012 IEEE Transactions on Pattern Analysis and Machine Intelligence 34 791Google Scholar

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    程志远, 马彩文, 罗秀娟, 张羽, 朱香平, 夏爱利 2015 物理学报 64 124203Google Scholar

    Cheng Z Y, Ma C W, Luo X J, Zhang Y, Zhu X P, Xia A L 2015 Acta Phys. Sin. 64 124203Google Scholar

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    程志远, 马彩文, 马青 2017 物理学报 66 244202Google Scholar

    Cheng Z Y, Ma C W, Ma Q 2017 Acta Phys. Sin. 66 244202Google Scholar

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    Rhodes W T 2012 Appl. Opt. 51 A11

    [23]

    程志远 2015 博士学位论文(西安: 中国科学院大学)

    Cheng Z Y 2015 Ph.D. Dissertation (Xi’an: Chinese Academy Sciences University) (in Chinese)

  • 图 1  激光相干场成像原理示意图

    Fig. 1.  Schematic diagram of laser coherent field imaging.

    图 2  激光相干场成像信号去噪信息流程图

    Fig. 2.  Flow chart of denoising information for laser coherent field imaging signal.

    图 3  相位闭合示意图

    Fig. 3.  Schematic diagram of phase closure technique.

    图 4  不同算法去噪效果图 (a)原始模板图像; (b)由图像算法直接重构未去噪的图像; (c)由稀疏去噪算法去加性噪声后得到的图像; (d)由同态滤波去乘性散斑噪声后得到的图像; (e)由同态滤波和稀疏复合去噪后得到的图像

    Fig. 4.  Denoising effect diagram of different algorithms: (a) Original template image; (b) direct reconstruction of undenoised images by image algorithms; (c) image obtained by sparse denoising algorithm after additive noise removal; (d) image obtained by removing multiplicative speckle noise by homomorphic filtering; (e) image obtained by homomorphic filtering and sparse combined denoising.

    图 5  室外成像去噪实验效果对比图 (a) 室外成像目标; (b)直接重构成像; (c)去噪后重构成像

    Fig. 5.  Comparison of outdoor imaging de-noising experiment: (a) Ooutdoor imaging target; (b) direct reconstruction imaging; (c) reconstruction imaging after de-noising.

    表 1  不同去噪方法指标对比表

    Table 1.  Comparison indicators table of different de-noising methods.

    对比项直接重建法稀疏去噪法同态滤波法复合去噪法
    斯特列尔比46.3%50.1%52.7%63.5%
    图像对比度0.250.270.420.46
    平均梯度5.986.116.287.13
    下载: 导出CSV
  • [1]

    朱曼曼, 时东锋, 胡顺星, 王英俭 2017 量子电子学报 34 145

    Zhu M M, Shi D F, Hu S S, Wang Y J 2017 Chinese Journal of Quantum Electronics 34 145

    [2]

    邓慧, 张蓉竹, 孙年春 2016 应用光学 36 0129002

    Deng H, Zhang R Z, Sun N C 2016 Journal of Applied Optics 36 0129002

    [3]

    陈艳, 李中梁, 南楠, 步扬, 王瑄, 潘柳华, 王向朝 2015 光学学报 38 0811004

    Chen Y, Li Z L, Nan N, Bu Y, Wang X, Pan L H, Wang X C 2015 Acta Optic. Sin. 38 0811004

    [4]

    吴育民, 段海燕, 文永富, 程灏波, 王谭 2018 影像科学与光化学 36 187Google Scholar

    Wu Y M, Duan H Y, Wen Y F, Cheng H B, Wang T 2018 Imaging Science and Photochemistry 36 187Google Scholar

    [5]

    杨鹏程, 刘洋, 朱新栋, 胥光申, 肖渊 2017 应用光学 38 221

    Yang P C, Liu Y, Zhu X D, Xu G S, Xiao Y 2017 Journal of Applied Optics 38 221

    [6]

    陈波, 杨靖, 杨旭, 李小阳 2015 中国激光 42 1012002

    Chen B, Yang J, Yang X, Li X Y 2015 Chinese Journal of Lasers 42 1012002

    [7]

    袁治灵, 陈俊波, 黄伟源, 魏波, 唐志列 2018 光学学报 38 0511002

    Yuan Z L, Chen J B, Huang W Y, Wei B, Tang Z L 2018 Acta Optical Sinica 38 0511002

    [8]

    王大勇, 王云新, 郭莎, 戎路, 张亦卓 2014 物理学报 63 154205Google Scholar

    Wang D Y, Wang Y X, Guo S, Rong L, Zhang Y Z 2014 Acta Phys. Sin. 63 154205Google Scholar

    [9]

    田小平, 程新, 吴成茂, 刘一博 2015 西安邮电大学学报 20 51

    Tian X P, Cheng X, Wu C M, Liu Y B 2015 Journal of Xi’an University of Posts and Telecommunications. 20 51

    [10]

    Kuechel M US Patent 6 804 011 [2004-10-12]

    [11]

    Yu H C, Gao J L, Li A T 2016 Opt. Lett. 41 994Google Scholar

    [12]

    张艳艳, 陈苏婷, 葛俊祥, 万发雨, 梅永, 周晓彦 2017 物理学报 66 129501Google Scholar

    Zhang Y Y, Chen S T, Ge J X, Wan F Y, Mei Y, Zhou X Y 2017 Acta Phys. Sin. 66 129501Google Scholar

    [13]

    陈晔曜, 蒋刚毅, 邵华, 姜浩, 郁梅 2018 光电工程 45 180083Google Scholar

    Chen Y Y, Jiang G Y, Shao H, Jian H, Yu M 2018 Opto-Electronic Engineering 45 180083Google Scholar

    [14]

    Chiang J C, Kao P H, Chen Y S, et al. 2017 Circ. Syst. Signal Pr. 36 2786Google Scholar

    [15]

    Zhang K, Zuo W, Chen Y, Meng D, Zhang L 2017 IEEE Trans. Image Process. 26 3142Google Scholar

    [16]

    郝红星, 吴玲达, 宋晓瑞 2018 计算机学报 41 1Google Scholar

    Hao H X, Wu L D, Song X R 2018 Chienese Journal of Computers 41 1Google Scholar

    [17]

    沈晨, 张旻 2018 探测与控制学报 40 128

    Shen C, Zhang M 2018 Journal of Detection & Control 40 128

    [18]

    詹曙, 王俊, 杨福猛, 方琪 2015 电子学报 43 523Google Scholar

    Zhan S, Wang J, Yang F M, Fang Q 2015 Acta Electronic Sinica 43 523Google Scholar

    [19]

    Mairal J, Bach F, Ponce J 2012 IEEE Transactions on Pattern Analysis and Machine Intelligence 34 791Google Scholar

    [20]

    程志远, 马彩文, 罗秀娟, 张羽, 朱香平, 夏爱利 2015 物理学报 64 124203Google Scholar

    Cheng Z Y, Ma C W, Luo X J, Zhang Y, Zhu X P, Xia A L 2015 Acta Phys. Sin. 64 124203Google Scholar

    [21]

    程志远, 马彩文, 马青 2017 物理学报 66 244202Google Scholar

    Cheng Z Y, Ma C W, Ma Q 2017 Acta Phys. Sin. 66 244202Google Scholar

    [22]

    Rhodes W T 2012 Appl. Opt. 51 A11

    [23]

    程志远 2015 博士学位论文(西安: 中国科学院大学)

    Cheng Z Y 2015 Ph.D. Dissertation (Xi’an: Chinese Academy Sciences University) (in Chinese)

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出版历程
  • 收稿日期:  2018-08-22
  • 修回日期:  2018-11-17
  • 上网日期:  2019-03-01
  • 刊出日期:  2019-03-05

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