Laser & Optoelectronics Progress, Volume. 60, Issue 10, 1010017(2023)

Single-Image Super-Resolution Reconstruction Aggregating Residual Attention Network

Yanfei Peng... Manting Zhang*, Pingjia Zhang, Jian Li and Lirui Gu |Show fewer author(s)
Author Affiliations
  • School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, Liaoning , China
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    Figures & Tables(14)
    Comparison of ResNet and ResNeXt. (a) ResNet structure; (b) ResNeXt structure; (c) proposed residual structure
    Attention mechanism
    Flowchart of improved network
    Generator network structure
    Discriminator network structure
    Effect of cardinality number on module performance
    Experimental comparison result for image on BSD100 dataset. (a) Original image; (b) ResNeXt; (c) ResNeXt+SE; (d) ResNeXt+SimAM
    Comparison of reconstruction effect of "baby" on Set5 dataset
    Comparison of reconstruction effect of “foreman” on Set14 dataset
    Comparison of reconstruction effect of “3096” on BSD100 dataset
    • Table 1. PSNR and SSIM of different module combinations on Set14 dataset

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      Table 1. PSNR and SSIM of different module combinations on Set14 dataset

      MethodPSNR /dBSSIM
      Baseline27.330.7517
      Baseline +ResNeXt27.830.7767
      Baseline +SimAM27.520.7651
      Baseline +SN27.570.7763
      Baseline+Charbonnier27.440.7672
      Ours28.500.7848
    • Table 2. PSNR value of different module combinations on BSD100 dataset

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      Table 2. PSNR value of different module combinations on BSD100 dataset

      MethodPSNR /dB
      ResNeXt27.047
      ResNeXt+SE27.125
      ResNeXt+SimAM27.168
    • Table 3. Average PSNR of different SR algorithms on three test sets at 4× magnification factor

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      Table 3. Average PSNR of different SR algorithms on three test sets at 4× magnification factor

      DatasetScaleBicubicSRCNNESPCNSRGANESRGANXLSROurs
      Set5428.4129.1529.6629.8230.4730.8731.62
      Set14426.0926.3226.8627.3326.6127.6928.50
      BSD100425.9526.3226.4526.6425.3227.0727.34
    • Table 4. Average SSIM of different SR algorithms on three test sets at 4× magnification factor

      View table

      Table 4. Average SSIM of different SR algorithms on three test sets at 4× magnification factor

      DatasetScaleBicubicSRCNNESPCNSRGANESRGANXLSROurs
      Set540.81280.82910.83360.84710.85180.87380.8880
      Set1440.71840.73610.73010.75170.71390.77290.7848
      BSD10040.67120.69210.67540.70110.65050.71920.7277
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    Yanfei Peng, Manting Zhang, Pingjia Zhang, Jian Li, Lirui Gu. Single-Image Super-Resolution Reconstruction Aggregating Residual Attention Network[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1010017

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    Paper Information

    Category: Image Processing

    Received: Feb. 16, 2022

    Accepted: Apr. 6, 2022

    Published Online: May. 10, 2023

    The Author Email: Zhang Manting (1016422506@qq.com)

    DOI:10.3788/LOP220752

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