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针对光栅图像的快速盲去噪方法

张申华 杨延西 秦峤孟

张申华, 杨延西, 秦峤孟. 针对光栅图像的快速盲去噪方法[J]. 中国光学. doi: 10.37188/CO.2020-0166
引用本文: 张申华, 杨延西, 秦峤孟. 针对光栅图像的快速盲去噪方法[J]. 中国光学. doi: 10.37188/CO.2020-0166
ZHANG Shen-hua, YANG Yan-xi, QIN Qiao-meng. A fast blind denoising method for grating image[J]. Chinese Optics. doi: 10.37188/CO.2020-0166
Citation: ZHANG Shen-hua, YANG Yan-xi, QIN Qiao-meng. A fast blind denoising method for grating image[J]. Chinese Optics. doi: 10.37188/CO.2020-0166

针对光栅图像的快速盲去噪方法

doi: 10.37188/CO.2020-0166
基金项目: 国家重点研发计划专项(No. 2018YFB1703000);陕西省重点研发计划项目(No. 2020ZDLGR07-06);陕西省现代装备绿色制造协同创新中心项目(No. 304-210891702)
详细信息
    作者简介:

    张申华(1982—),河南信阳人,2010年于西北大学获得硕士学位,现为西安理工大学博士研究生,主要研究方向为光学测量。E-mail:zhang_shenhua@126.com

    杨延西(1975),山东郓城人,博士,教授,2003年于西安理工大学获得博士学位,现为西安理工大学教授、博士生导师,主要研究方向为复杂系统控制、机器视觉和智能机器人。E-mail:yangyanxi@xaut.edu.cn

  • 中图分类号: O439

A fast blind denoising method for grating image

Funds: Supported by National Key R&D Program of China (No. 2018YFB1703000); Key R&D Program of Shaanxi province (No. 2020ZDLGR07-06); Collaborative Innovation Center of Shaanxi Province for Green Manufacturing of Modern Equipment (No. 304-210891702)
  • 摘要: 基于正弦光栅条纹投影的三维测量技术是当前研究的热点问题。然而,由于受噪声的影响,采集到的光栅条纹图像质量降低,导致提取的相位发生扰动,而相位的提取结果直接决定着测量结果的准确性。实际测量中噪声未知,针对这一问题,本文提出了一种盲去噪方法。首先,根据残差模型,完成光栅条纹图像的真值图像与噪声图像的分离,然后,引入主成分分析技术估计出噪声图像的方差值。最后,根据噪声方差的估计值,利用基于相图的高斯滤波方法,将针对多帧光栅图像的噪声滤波,转换到提取的相位图上完成。由实验结果可知,和对比方法相比,本文方法的均方根相位误差最高下降了88.5%,所提方法处理后的相位更加接近测量体的真值相位。本文方法可在最短的执行时间内实现对噪声导致的相位扰动抑制。所提方法能够快速处理光栅图像噪声引起的相位误差,在光栅投影测量中具有较强的实用性。
  • 图  1  PCA方法对仿真噪声的估计

    Figure  1.  The estimation of simulation noise by PCA method

    图  2  主成分分量占比

    Figure  2.  Proportion of principal component

    图  3  测量系统结构图

    Figure  3.  Framework of measuring system

    图  4  采集的光栅图像

    Figure  4.  Captured grating image

    图  5  几种不同方法的滤波效果

    Figure  5.  Filtering effect of different methods

    图  6  各种方法的相位差

    Figure  6.  Phase errors of different methods

    表  1  仪器设备型号和参数

    Table  1.   The instrument types and parameters

    仪器设备型号主要性能及参数
    投影仪DLP4500分辨率912×1140
    工业相机MV-UB130M分辨率1024×1280
    曝光时间:200 ms
    帧率:30 fps
    信噪比:45 dB
    电脑Intel Core (TM)
    i5-8250U CPU
    主频:1.6 GHz
    下载: 导出CSV

    表  2  各种方法的噪声方差估计值

    Table  2.   The estimated noise variances of different methods

    估计方法文献[5]方法文献[7]方法文献[8]方法本文方法
    估计值3.37371.60252.7823
    下载: 导出CSV

    表  3  几种算法的量化指标对比

    Table  3.   Comparison of quantitative indicators for different methods

    中值滤波
    方法
    Ref.[10]
    方法
    Ref.[12]
    方法
    Ref.[13]
    方法
    本文方法
    MPE0.38569.23431.82681.73010.7003
    RMSE0.09610.51220.10290.10380.0591
    下载: 导出CSV

    表  4  几种算法的执行时间对比

    Table  4.   Comparison of computing time for different methods (s)

    对比方法中值滤波
    方法
    Ref.[10]
    方法
    Ref.[12]
    方法
    Ref.[13]
    方法
    本文方法
    执行时间16.12758.367.1811.676.74
    下载: 导出CSV
  • [1] 王建华, 杨延西. 基于彩色编码光栅投影的双N步相移轮廓术[J]. 中国光学,2019,12(3):616-627. doi: 10.3788/co.20191203.0616

    WANG J H, YANG Y X. Double N-step phase-shifting profilometry using color-encoded grating projection[J]. Chinese Optics, 2019, 12(3): 616-627. (in Chinese) doi: 10.3788/co.20191203.0616
    [2] 张申华, 杨延西. 一种针对投影仪gamma效应的相位误差补偿方法[J]. 仪器仪表学报,2019,40(11):1-8.

    ZHANG SH H, YANG Y X. A phase error compensation method for the gamma effect of projector[J]. Chinese Journal of Scientific Instrument, 2019, 40(11): 1-8. (in Chinese)
    [3] 邓吉, 李健, 封皓, 等. 不连续相位跳变点的三维深度分割[J]. 光学 精密工程,2019,27(11):2459-2466. doi: 10.3788/OPE.20192711.2459

    DENG J, LI J, FENG H, et al. Three-dimensional depth segmentation technique utilizing discontinuities of wrapped phase sequence[J]. Optics and Precision Engineering, 2019, 27(11): 2459-2466. (in Chinese) doi: 10.3788/OPE.20192711.2459
    [4] 丁超, 唐力伟, 曹立军, 等. 深孔内表面结构光图像几何畸变校正[J]. 光学 精密工程,2018,26(10):2555-2564. doi: 10.3788/OPE.20182610.2555

    DING CH, TANG L W, CAO L J, et al. Geometric distortion correction for structured-light image of deep-hole inner-surface[J]. Optics and Precision Engineering, 2018, 26(10): 2555-2564. (in Chinese) doi: 10.3788/OPE.20182610.2555
    [5] 韩玉兰, 赵永平, 王启松, 等. 稀疏表示下的噪声图像超分辨率重构[J]. 光学 精密工程,2017,25(6):1619-1626. doi: 10.3788/OPE.20172506.1619

    HAN Y L, ZHAO Y P, WANG Q S, et al. Reconstruction of super resolution for noise image under the sparse representation[J]. Optics and Precision Engineering, 2017, 25(6): 1619-1626. (in Chinese) doi: 10.3788/OPE.20172506.1619
    [6] 谢斌, 黄安, 黄辉. 本征图像分解的稀疏表示彩色图像去噪算法[J]. 液晶与显示,2019,34(11):1104-1114. doi: 10.3788/YJYXS20193411.1104

    XIE B, HUANG A, HUANG H. Color image denoising algorithm based on intrinsic image decomposition and sparse representation[J]. Chinese Journal of Liquid Crystals and Displays, 2019, 34(11): 1104-1114. (in Chinese) doi: 10.3788/YJYXS20193411.1104
    [7] 马逸东, 周顺勇. 基于连通性检测的图像椒盐噪声滤波算法[J]. 液晶与显示,2020,35(2):167-172. doi: 10.3788/YJYXS20203502.0167

    MA Y D, ZHOU SH Y. Salt and pepper noise filtering algorithm based on connectivity detection[J]. Chinese Journal of Liquid Crystals and Displays, 2020, 35(2): 167-172. (in Chinese) doi: 10.3788/YJYXS20203502.0167
    [8] WANG J H, YANG Y X. An efficient phase error self-compensation algorithm for nonsinusoidal gating fringes in phase-shifting profilometry[J]. Review of Scientific Instrument, 2018, 89(6): 063115. doi: 10.1063/1.5025593
    [9] WANG H X, QIAN K M, GAO W J, et al. Fringe pattern denoising using coherence-enhancing diffusion[J]. Optics Letters, 2009, 34(8): 1141-1143. doi: 10.1364/OL.34.001141
    [10] TANG CH, HAN L, REN H W, et al. Second-order oriented partial-differential equations for denoising in electronic-speckle-pattern interferometry fringes[J]. Optics Letters, 2008, 33(19): 2179-2181. doi: 10.1364/OL.33.002179
    [11] ZHOU Q L, TANG CH, LI B Y, et al. Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns[J]. Optics and Lasers in Engineering, 2018, 100: 111-117. doi: 10.1016/j.optlaseng.2017.07.018
    [12] DONOHO D L, JOHNSTONE I M. Ideal spatial adaptation by wavelet shrinkage[J]. Biometrika, 1994, 81(3): 425-455. doi: 10.1093/biomet/81.3.425
    [13] PYATYKH S, HESSER J, ZHENG L. Image noise level estimation by principal component analysis[J]. IEEE Transactions on Image Processing, 2013, 22(2): 687-699. doi: 10.1109/TIP.2012.2221728
    [14] LIU X H, TANAKA M, OKUTOMI M. Single-image noise level estimation for blind denoising[J]. IEEE Transactions on Image Processing, 2013, 22(12): 5226-5237. doi: 10.1109/TIP.2013.2283400
    [15] 汪浩然, 夏克文, 任苗苗, 等. 结合PCA及字典学习的高光谱图像自适应去噪方法[J]. 计算机应用,2016,36(12):3411-3417, 3422. doi: 10.11772/j.issn.1001-9081.2016.12.3411

    WANG H R, XIA K W, REN M M, et al. Adaptive denoising method of hyperspectral remote sensing image based on PCA and dictionary learning[J]. Journal of Computer Applications, 2016, 36(12): 3411-3417, 3422. (in Chinese) doi: 10.11772/j.issn.1001-9081.2016.12.3411
    [16] 肖进胜, 朱力, 赵博强, 等. 基于主成分分析的分块视频噪声估计[J]. 自动化学报,2018,44(9):1618-1625.

    XIAO J SH, ZHU L, ZHAO B Q, et al. Block-based video noise estimation algorithm via principal component analysis[J]. Acta Automatica Sinica, 2018, 44(9): 1618-1625. (in Chinese)
    [17] 乔双, 吴晓阳, 赵辰一, 等. 基于PCA和BM3D的噪声估计方法及其在中子图像去噪中的应用[J]. 原子能科学技术,2018,52(4):729-736. doi: 10.7538/yzk.2017.youxian.0457

    QIAO SH, WU X Y, ZHAO CH Y, et al. Noise level estimation method based on PCA and BM3D for neutron image denoising[J]. Atomic Energy Science and Technology, 2018, 52(4): 729-736. (in Chinese) doi: 10.7538/yzk.2017.youxian.0457
    [18] 杨华. 基于稀疏主成分分析的图像噪声估计方法[J]. 液晶与显示,2019,34(9):913-920. doi: 10.3788/YJYXS20193409.0913

    YANG H. Image noise estimation method based on sparse principal component analysis[J]. Chinese Journal of Liquid Crystals and Displays, 2019, 34(9): 913-920. (in Chinese) doi: 10.3788/YJYXS20193409.0913
    [19] 叶杨, 徐志伟, 陈仁文, 等. 基于KPCA和SVM的直升机旋翼桨叶损伤源定位[J]. 电子测量与仪器学报,2020,34(4):118-123.

    YE Y, XU ZH W, CHEN R W, et al. Damage source location of helicopter rotor blade based on KPCA and SVM[J]. Journal of Electronic Measurement and Instrumentation, 2020, 34(4): 118-123. (in Chinese)
    [20] 吴疆, 尤飞, 蒋平. 基于回归分析和主成分分析的噪声方差估计方法[J]. 电子与信息学报,2018,40(5):1195-1201. doi: 10.11999/JEIT170624

    WU J, YOU F, JIANG P. Noise variance estimation method based on regression analysis and principal component analysis[J]. Journal of Electronics &Information Technology, 2018, 40(5): 1195-1201. (in Chinese) doi: 10.11999/JEIT170624
    [21] ZUO CH, HUANG L, ZHANG M L, et al. Temporal phase unwrapping algorithms for fringe projection profilometry: a comparative review[J]. Optics and Lasers in Engineering, 2016, 85: 84-103. doi: 10.1016/j.optlaseng.2016.04.022
    [22] JIANG P, WANG Q, WU J. Efficient noise-level estimation based on principal image texture[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020, 30(7): 1987-1999.
    [23] TOWERS C E, TOWERS D P, JONES J D C. Absolute fringe order calculation using optimised multi-frequency selection in full-field profilometry[J]. Optics and Lasers in Engineering, 2005, 43(7): 788-800. doi: 10.1016/j.optlaseng.2004.08.005
    [24] ZUO CH, FENG SH J, HUANG L, et al. Phase shifting algorithms for fringe projection profilometry: a review[J]. Optics and Lasers in Engineering, 2018, 109: 23-59. doi: 10.1016/j.optlaseng.2018.04.019
    [25] MAO C L, LU R S, LIU Z J. A multi-frequency inverse-phase error compensation method for projector nonlinear in 3D shape measurement[J]. Optics Communications, 2018, 419: 75-85. doi: 10.1016/j.optcom.2018.03.006
    [26] ZHANG CH W, ZHAO H, ZHANG L, et al. Full-field phase error detection and compensation method for digital phase-shifting fringe projection profilometry[J]. Measurement Science and Technology, 2015, 26(3): 035201. doi: 10.1088/0957-0233/26/3/035201
    [27] GAI SH Y, DA F P, LIU CH. Multiple-gamma-value based phase error compensation method for phase measuring profilometry[J]. Applied Optics, 2018, 57(35): 10290-10299. doi: 10.1364/AO.57.010290
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出版历程
  • 收稿日期:  2020-09-11
  • 修回日期:  2020-10-21
  • 网络出版日期:  2021-04-09

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