Speckle Noise Reduction of Optical Coherence Tomography Based on Robust Principle Component Analysis Algorithm

Zhiling Yuan; Junbo Chen; Weiyuan Huang; Bo Wei; Zhilie Tang

doi:10.3788/AOS201838.0511002

Acta Optica Sinica, Volume. 38, Issue 5, 0511002(2018)

Speckle Noise Reduction of Optical Coherence Tomography Based on Robust Principle Component Analysis Algorithm

Zhiling Yuan¹, Junbo Chen¹, Weiyuan Huang¹, Bo Wei¹, and Zhilie Tang^1,2、*

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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Fig. 1. Data processing flow chart of the RPCA algorithm employed to reduce speckle noise in OCT images

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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

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Fig. 3. Selected regional markings for quantitative analysis of image quality. (a) Original image; (b) denoised image

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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

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Table 1. Quantitative analysis results of original image and denoised images processed by two algorithms
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Table 1. Quantitative analysis results of original image and denoised images processed by two algorithms
Image PSNR /dB CNR /dB ENL Time /s
Original image 26.75 4.79 71.81
Denoised image processed by PNLM algorithm 34.22 5.73 123.51 2.92
Denoised image processed by RPCA algorithm 29.28 6.94 500.27 3.07

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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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