Chinese Journal of Lasers, Volume. 47, Issue 1, 0114001(2020)

Application of Wavelet Denoising in Terahertz Nondestructive Detection

Jiyang Zhang1,2, Jiaojiao Ren1,2, Sihong Chen1,2, Lijuan Li1,2、*, and Changshuang Zhao3
Author Affiliations
  • 1Key Laboratory of Photoelectric Measurement and Control and Optical Information Transmission Technology,Ministry of Education, College of Optoelectronic Engineering, Changchun University of Science and Technology,Changchun, Jilin 130022, China
  • 2National Experimental Teaching and Demonstration Center of Optoelectronic Engineering, College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, Jilin 130022, China
  • 393367 troops of the Chinese People's Liberation Army, Siping, Jilin 136000, China
  • show less
    Figures & Tables(9)
    Photograph and schematic of terahertz time-domain spectroscopy system. (a) Photograph; (b) working principle
    Schematic of tomographic short-time integral imaging
    Photograph of phenolic plastic plate and comparison of defect detection images of two tomographic methods. (a) Photograph of phenolic plastic plate; (b) defect size design; (c) detection result of tomographic imaging method; (d) detection result of tomographic short-time integral imaging method
    Implementation process of wavelet threshold denoising
    Schematic of interval setting of δ-σ evaluation rule
    Photograph and defect size design of phenolic plastic samples. (a) Photograph; (b) defect size design
    Pseudo-color maps of power spectral imaging. (a) Before preprocessing; (b) sym7, three layers, soft-threshold preprocessing; (c) sym7, five layers, hard-threshold preprocessing; (d) sym7, five layers, soft-threshold preprocessing
    Nondestructive detection signals of samples before and after preprocessing. (a) Before preprocessing; (b) sym7, three layers, soft-threshold preprocessing; (c) sym7, five layers, hard-threshold preprocessing (d) sym7, five layers, soft-threshold preprocessing
    • Table 1. Evaluation results of nondestructive detection images of different prefabricated defects in phenolic plastic samples

      View table

      Table 1. Evaluation results of nondestructive detection images of different prefabricated defects in phenolic plastic samples

      Phenolic plastic sampleSubjective evaluationObjective evaluation
      Identify number of defectsDefect recognition rate /%Weber contrast
      Before pretreatment4660.292
      Soft threshold, 3 layers5830.321
      Hard threshold, 5 layers61000.388
      Soft threshold, 5 layers61000.415
    Tools

    Get Citation

    Copy Citation Text

    Jiyang Zhang, Jiaojiao Ren, Sihong Chen, Lijuan Li, Changshuang Zhao. Application of Wavelet Denoising in Terahertz Nondestructive Detection[J]. Chinese Journal of Lasers, 2020, 47(1): 0114001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: terahertz technology

    Received: Jul. 4, 2019

    Accepted: Oct. 9, 2019

    Published Online: Jan. 9, 2020

    The Author Email: Lijuan Li (custjuan@126.com)

    DOI:10.3788/CJL202047.0114001

    Topics