Opto-Electronic Engineering, Volume. 52, Issue 1, 240264(2025)

Smartphone image quality assessment method based on Swin-AK Transformer

Guopeng Hou, Wu Dong*, Likun Lu, Ziyi Zhou, Qian Ma, Zhen Bai, and Shenghui Zheng
Author Affiliations
  • Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment, Beijing Institute of Graphic Communication, Beijing 102600, China
  • show less
    Figures & Tables(19)
    Overall structure diagram of the proposed method
    Diagram of manual feature extraction
    ResNet50 architecture diagram
    Diagram of the sliding window operation in Swin Transformer
    Swin-AK Transformer architecture diagram
    Swin-AK blocks architecture diagram
    AKConv architecture diagram
    Structure diagram of the dual attention cross fusion module
    Channel attention network structure diagram
    Structure diagram of the spatial attention module
    Scatter plot of image attribute scores versus overall subjective quality scores in the SPAQ. (a) Brightness; (b) Colorfulness; (c) Sharpness
    Scatter plot on the LIVE-C dataset
    Scatter plot on the SPAQ dataset
    Comparison of attention heatmaps between Swin Transformer and Swin-AK Transformer
    MOS values of images in the SPAQ dataset and the quality prediction values of the proposed method
    MOS values of images in the LIVE-C dataset and the quality prediction values of the proposed method
    • Table 1. Comparison of the proposed method with other methods on the SPAQ dataset

      View table
      View in Article

      Table 1. Comparison of the proposed method with other methods on the SPAQ dataset

      MethodsPLCCSROCC
      BLINDS-II[21]0.5390.478
      DIIVINE[22]0.6030.596
      BRISQUE[23]0.8170.828
      CORNIA[24]0.7240.709
      IL-NIQE[25]0.7040.695
      HOSA[26]0.8240.817
      DIQaM-NR[27]0.8360.824
      WaDIQaM-NR[27]0.8430.821
      TS-CNN[28]0.8110.801
      TReS[29]0.9110.902
      DB-CNN[30]0.9130.909
      HyperIQA[31]0.9190.916
      CaHDC[32]0.8410.833
      ResNet50[7]0.9090.908
      MT-A[7]0.9160.916
      MUSIQ[2]0.9210.917
      DACNN[33]0.9210.915
      Re-IQA[34]0.9250.918
      DEIQT[35]0.9230.919
      LoDa[36]0.9280.925
      Ours0.9320.929
    • Table 2. Comparison of the proposed method with other methods on the LIVE-C dataset

      View table
      View in Article

      Table 2. Comparison of the proposed method with other methods on the LIVE-C dataset

      MethodsPLCCSROCC
      BLINDS-II[21]0.4970.456
      DIIVINE[22]0.5570.513
      BRISQUE[23]0.6370.616
      CORNIA[24]0.6590.617
      IL-NIQE[25]0.5160.539
      HOSA[26]0.6910.674
      DIQaM-NR[27]0.6450.633
      WaDIQaM-NR[27]0.6920.669
      TS-CNN[28]0.6670.655
      TReS[29]0.8770.846
      DB-CNN[30]0.8590.852
      HyperIQA[31]0.8700.855
      CaHDC[32]0.7380.734
      MUSIQ[2]0.8750.862
      DACNN[33]0.8820.861
      Re-IQA[34]0.8540.84
      Ours0.8850.865
    • Table 3. Results of the ablation experiment

      View table
      View in Article

      Table 3. Results of the ablation experiment

      ModelPLCCSROCC
      Swin Transformer0.9210.918
      Swin-AK Transformer0.9230.920
      Manual features+ Swin Transformer0.9240.922
      Manual features+ Swin-AK Transformer0.9290.925
      Ours0.9320.929
    Tools

    Get Citation

    Copy Citation Text

    Guopeng Hou, Wu Dong, Likun Lu, Ziyi Zhou, Qian Ma, Zhen Bai, Shenghui Zheng. Smartphone image quality assessment method based on Swin-AK Transformer[J]. Opto-Electronic Engineering, 2025, 52(1): 240264

    Download Citation

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

    Category: Article

    Received: Nov. 11, 2024

    Accepted: Dec. 23, 2024

    Published Online: Feb. 21, 2025

    The Author Email: Wu Dong (董武)

    DOI:10.12086/oee.2025.240264

    Topics