• Acta Optica Sinica
  • Vol. 38, Issue 5, 0511002 (2018)
Zhiling Yuan1, Junbo Chen1, Weiyuan Huang1, Bo Wei1, and Zhilie Tang1、2、*
Author Affiliations
  • 1 School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, Guangdong 510006, China
  • 2 National Exemplary Center for Experiment Teaching of Basic Courses in Physics, South China Normal University, Guangzhou, Guangdong 510006, China
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    DOI: 10.3788/AOS201838.0511002 Cite this Article Set citation alerts
    Zhiling Yuan, Junbo Chen, Weiyuan Huang, Bo Wei, Zhilie Tang. Speckle Noise Reduction of Optical Coherence Tomography Based on Robust Principle Component Analysis Algorithm[J]. Acta Optica Sinica, 2018, 38(5): 0511002 Copy Citation Text show less
    Data processing flow chart of the RPCA algorithm employed to reduce speckle noise in OCT images
    Fig. 1. Data processing flow chart of the RPCA algorithm employed to reduce speckle noise in OCT images
    Signal plots describing the one-dimensional depth information of the green lines corresponding to the original image and denoised image. (a) Original image; (b) signal plots describing the one-dimensional depth information of the original image; (c) denoised image; (d) signal plots describing the one-dimensional depth information of the denoised image
    Fig. 2. Signal plots describing the one-dimensional depth information of the green lines corresponding to the original image and denoised image. (a) Original image; (b) signal plots describing the one-dimensional depth information of the original image; (c) denoised image; (d) signal plots describing the one-dimensional depth information of the denoised image
    Selected regional markings for quantitative analysis of image quality. (a) Original image; (b) denoised image
    Fig. 3. Selected regional markings for quantitative analysis of image quality. (a) Original image; (b) denoised image
    Effect comparison of original image and denoised images processed by two algorithms. (a) Original image; (b) denoised image processed by PNLM algorithm; (c) denoised image processed by RPCA algorithm
    Fig. 4. Effect comparison of original image and denoised images processed by two algorithms. (a) Original image; (b) denoised image processed by PNLM algorithm; (c) denoised image processed by RPCA algorithm
    ImagePSNR /dBCNR /dBENLTime /s
    Original image26.754.7971.81
    Denoised image processed by PNLM algorithm34.225.73123.512.92
    Denoised image processed by RPCA algorithm29.286.94500.273.07
    Table 1. Quantitative analysis results of original image and denoised images processed by two algorithms
    Zhiling Yuan, Junbo Chen, Weiyuan Huang, Bo Wei, Zhilie Tang. Speckle Noise Reduction of Optical Coherence Tomography Based on Robust Principle Component Analysis Algorithm[J]. Acta Optica Sinica, 2018, 38(5): 0511002
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