Journals Articles Conferences News About CLP
Submit a paper Email Alert
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
2D MaterialsTransformation opticsQuantum PhotonicsSmall lasersSemiconductor UV PhotonicsSupersymmetric microring laser arrays

Acta Optica Sinica, Volume. 38, Issue 10, 1010001(2018)

Adaptive Image Denoising Based on Improved Stacked Sparse Denoising Auto-Encoder

Hongqiang Ma1、*, Shiping Ma1、*, Yuelei Xu1, Chao Lü2, and Mingming Zhu1
Author Affiliations
  • 1 Aeronautics Engineering College, Air Force Engineering University, Xi'an, Shaanxi 710038, China
  • 2 Unit 95876 of PLA, Shandan, Gansu 734100, China
    • show less
    AbstractGet PDF(in Chinese)
    Figures&Tables (7)
    Equations (0)
    References (0)
    Cited By (3)
    Tools
    Paper Information
    Topics
    Figures & Tables(7)
    Algorithm flow of DAE

    Fig. 1. Algorithm flow of DAE

    Download full size
    Network diagram of SSDA

    Fig. 2. Network diagram of SSDA

    Download full size
    Network diagram of SRDA

    Fig. 3. Network diagram of SRDA

    Download full size
    Network model of ASRDA

    Fig. 4. Network model of ASRDA

    Download full size
    Comparison of convergence effects

    Fig. 5. Comparison of convergence effects

    Download full size
    Comparison of denoising performance of different algorithms. (a) Noisy; (b) G-SRDA; (c) S&P-SRDA; (d) MC-SRDA; (e) ASRDA; (f) BM3D

    Fig. 6. Comparison of denoising performance of different algorithms. (a) Noisy; (b) G-SRDA; (c) S&P-SRDA; (d) MC-SRDA; (e) ASRDA; (f) BM3D

    Download full size

    • Table 1. Average PSNR/SSIM of the experimental results of different algorithms on the Set12 data set

      View table

      Table 1. Average PSNR/SSIM of the experimental results of different algorithms on the Set12 data set

      Noisy typeG-SRDAS&P-SRDAS-SRDAMC-SRDAASRDABM3D
      G127.63/0.815625.39/0.750425.41/0.756127.44/0.807529.87/0.851729.88/0.8486
      G225.39/0.723323.13/0.619422.78/0.600325.38/0.717125.44/0.732125.39/0.7232
      S&P128.27/0.840634.90/0.985123.9/0.679526.62/0.800236.87/0.986319.50/0.4326
      S&P225.75/0.799831.66/0.966122.92/0.628423.79/0.734733.66/0.971113.71/0.1646
      S123.87/0.685124.45/0.697128.58/0.841124.91/0.702928.22/0.839619.40/0.4743
      S223.6/0.659623.85/0.664427.75/0.814724.24/0.671327.77/0.813616.64/0.3769
      P123.79/0.684524.44/0.742023.90/0.687724.26/0.672028.83/0.847927.13/0.8289
      P223.4/0.652023.77/0.656122.92/0.631023.40/0.646325.63/0.751720.61/0.7454
      U123.65/0.677024.11/0.673825.05/0.673924.14/0.681525.05/0.666916.98/0.3098
      U219.28/0.636819.41/0.636620.21/0.650019.88/0.644321.10/0.661014.13/0.3036
      Average24.46/0.721025.51/0.739124.80/0.701424.35/0.708328.25/0.812220.34/0.5208
    Tools

    Get Citation

    Copy Citation Text

    Hongqiang Ma, Shiping Ma, Yuelei Xu, Chao Lü, Mingming Zhu. Adaptive Image Denoising Based on Improved Stacked Sparse Denoising Auto-Encoder[J]. Acta Optica Sinica, 2018, 38(10): 1010001

    Download Citation

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

    Category: Image Processing

    Received: Mar. 6, 2018

    Accepted: May. 8, 2018

    Published Online: May. 9, 2019

    The Author Email:

    DOI:10.3788/AOS201838.1010001

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology