• Acta Optica Sinica
  • Vol. 38, Issue 8, 0812002 (2018)
Chenglin Zheng1、3、*, Dingding He2、3, and Qingguo Fei1、3、*
Author Affiliations
  • 1 School of Mechanical Engineering, Southeast University, Nanjing, Jiangsu 211189, China
  • 2 School of Civil Engineering, Southeast University, Nanjing, Jiangsu 210096, China
  • 3 Institute of Aerospace Machinery and Dynamics, Southeast University, Nanjing, Jiangsu 211189, China
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    DOI: 10.3788/AOS201838.0812002 Cite this Article Set citation alerts
    Chenglin Zheng, Dingding He, Qingguo Fei. Improved Digital Image Correlation Method Based on Gray Gradient Denoised by Regularization Method[J]. Acta Optica Sinica, 2018, 38(8): 0812002 Copy Citation Text show less
    Numerical simulation of speckle image
    Fig. 1. Numerical simulation of speckle image
    Absolute relative error of gray gradient in image sub-region after adding noise
    Fig. 2. Absolute relative error of gray gradient in image sub-region after adding noise
    Calculation errors of three algorithms with different sub-pixel displacements. (a) Mean error; (b) standard deviation error
    Fig. 3. Calculation errors of three algorithms with different sub-pixel displacements. (a) Mean error; (b) standard deviation error
    Calculation errors of three algorithms with different noise levels. (a) Absolute value of mean error; (b) standard deviation error
    Fig. 4. Calculation errors of three algorithms with different noise levels. (a) Absolute value of mean error; (b) standard deviation error
    Anti-noise ability test system with digital image correlation method
    Fig. 5. Anti-noise ability test system with digital image correlation method
    Absolute error of three algorithms with theoretical shift of 0 pixel. (a) Finite difference; (b) spline interpolation; (c) Tikhonov regularization
    Fig. 6. Absolute error of three algorithms with theoretical shift of 0 pixel. (a) Finite difference; (b) spline interpolation; (c) Tikhonov regularization
    AlgorithmMean error /pixelStandard deviation /pixelComputation time /s
    Finite difference0.00790.01814.3
    Spline interpolation0.00860.01924.5
    Tikhonov regularization0.00240.01527.1
    Table 1. Calculation errors and computation time of three algorithms with theoretical displacement of 0.3 pixel
    AlgorithmMean value /pixelStandarddeviation /pixel
    Finite difference0.01560.0125
    Spline interpolation0.01600.0133
    Tikhonovregularization0.00970.0050
    Table 2. Calculation errors of three algorithms with theoretical displacement of 0 pixel
    Chenglin Zheng, Dingding He, Qingguo Fei. Improved Digital Image Correlation Method Based on Gray Gradient Denoised by Regularization Method[J]. Acta Optica Sinica, 2018, 38(8): 0812002
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