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Laser & Optoelectronics Progress, Volume. 62, Issue 6, 0637011(2025)

Image Super-Resolution Reconstruction with Spatial/High-Frequency Dual-Domain Feature Saliency

Yue Hou*, Ziwei Hao, Zhihao Zhang, and Jie Yin
Author Affiliations
  • School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730000, Gansu , China
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    [1] Peng Y F, Zhang M T, Zhang P J et al. Single-image super-resolution reconstruction aggregating residual attention network[J]. Laser & Optoelectronics Progress, 60, 1010017(2023).

    [2] Ge X X, Cui H H, Xu Z L et al. Super-resolution image reconstruction method for micro defects of metal engine blades[J]. Acta Optica Sinica, 43, 0210001(2023).

    [3] Li Q, Wang X Y, He J W. Improved algorithm for super-resolution reconstruction of remote-sensing images based on generative adversarial networks[J]. Laser & Optoelectronics Progress, 60, 1028010(2023).

    [4] Georgescu M I, Ionescu R T, Miron A I et al. Multimodal multi-head convolutional attention with various kernel sizes for medical image super-resolution[C], 2194-2204(2023).

    [5] Liu X M, Zhao D B, Zhou J T et al. Image interpolation via graph-based Bayesian label propagation[J]. IEEE Transactions on Image Processing, 23, 1084-1096(2014).

    [6] Rasti P, Demirel H, Anbarjafari G. Image resolution enhancement by using interpolation followed by iterative back projection[C](2013).

    [7] Timofte R, De V, Gool L V. Anchored neighborhood regression for fast example-based super-resolution[C], 1920-1927(2013).

    [8] Indyk P, Xu H K. Worst-case performance of popular approximate nearest neighbor search implementations: guarantees and limitations[EB/OL]. https://arxiv.org/abs/2310.19126

    [9] Ding Z X, Zhang J, Li X et al. Lightweight attention-guided network for image super-resolution[J]. Laser & Optoelectronics Progress, 60, 1410010(2023).

    [10] Ravasi M, Luiken N. Why projection over convex sets works and how to make it better[J]. Geophysics, 89, A1-A5(2024).

    [11] Liu C, Sun D Q. On Bayesian adaptive video super resolution[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 346-360(2014).

    [12] Irani M, Peleg S. Improving resolution by image registration[J]. CVGIP: Graphical Models and Image Processing, 53, 231-239(1991).

    [13] Iqbal S, Qureshi A N, Aurangzeb K et al. Hybrid parallel fuzzy CNN paradigm: unmasking intricacies for accurate brain MRI insights[J/OL]. IEEE Transactions on Fuzzy Systems, 1-17. https://ieeexplore.ieee.org/document/10459150

    [14] Dong C, Loy C C, He K M et al. Learning a deep convolutional network for image super-resolution[M]. Computer vision-ECCV 2014, 8692, 184-199(2014).

    [15] Shi W Z, Caballero J, Huszár F et al. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network[C], 1874-1883(2016).

    [16] Kim J, Lee J K, Lee K M. Accurate image super-resolution using very deep convolutional networks[C], 1646-1654(2016).

    [17] Ahn N, Kang B, Sohn K A. Fast, accurate, and lightweight super-resolution with cascading residual network[M]. Computer vision-ECCV 2018, 11214, 256-272(2018).

    [18] Zhang Y L, Li K P, Li K et al. Image super-resolution using very deep residual channel attention networks[M]. Computer vision–ECCV 2018, 11211, 294-310(2018).

    [19] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Computer vision-ECCV 2018, 11211, 3-19(2018).

    [20] Zhao H Y, Kong X T, He J W et al. Efficient image super-resolution using pixel attention[M]. Computer vision-ECCV 2020 workshops, 12537, 56-72(2020).

    [21] Guo M H, Lu C Z, Liu Z N et al. Visual attention network[J]. Computational Visual Media, 9, 733-752(2023).

    [22] Liang J Y, Cao J Z, Sun G L et al. SwinIR: image restoration using Swin Transformer[C], 1833-1844(2021).

    [23] Choi H, Lee J, Yang J. N-gram in Swin Transformers for efficient lightweight image super-resolution[C], 2071-2081(2023).

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    Yue Hou, Ziwei Hao, Zhihao Zhang, Jie Yin. Image Super-Resolution Reconstruction with Spatial/High-Frequency Dual-Domain Feature Saliency[J]. Laser & Optoelectronics Progress, 2025, 62(6): 0637011

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    Paper Information

    Category: Digital Image Processing

    Received: Jul. 1, 2024

    Accepted: Aug. 29, 2024

    Published Online: Mar. 10, 2025

    The Author Email:

    DOI:10.3788/LOP241598

    CSTR:32186.14.LOP241598

    Topics

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