• INFRARED
  • Vol. 44, Issue 4, 33 (2023)
Yuan-yuan WAN1, Zhuo-da SONG1, Xiao-lin CHEN1, and Xin-xin ZHU2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    DOI: 10.3969/j.issn.1672-8785.2023.04.005 Cite this Article
    WAN Yuan-yuan, SONG Zhuo-da, CHEN Xiao-lin, ZHU Xin-xin. on Image Deblurring Based on Multi-ScaleOptimization and Dynamic Feature Fusion[J]. INFRARED, 2023, 44(4): 33 Copy Citation Text show less
    References

    [1] Fergus R, Singh B, Hertzmann A, et al. Removing camera shake from a single photograph [C]. Boston: SIGGRAPH 2006 Conference, 2006.

    [2] Sun J, Cao W F, Xu Z B, et al. Learning a convolutional neural network for non-uniform motion blur removal [C]. Boston: 28th IEEE Conference on Computer Vision and Pattern Recognition, 2015.

    [3] Nah S, Kim T H, Lee K M. Deep multi-scale convolutional neural network for dynamic scene deblurring [C]. Honolulu: 30th IEEE Conference on Computer Vision and Pattern Recognition, 2017.

    [4] Cho S J, Ji S W, Hong J P, et al. Rethinking coarse-to-fine approach in single image deblurring [C]. Montreal: 2021 IEEE/CVF International Conference on Computer Vision, 2021.

    [5] Kupyn O, Volodymyr B, Mykola M, et al. Deblurgan: Blind motion deblurring using conditional adversarial networks [C]. Salt Lake City: 2018 IEEE Conference on Computer Vision and Pattern, 2018.

    [6] Kupyn O, Tetiana M, Junru W, et al. Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better [C]. Seoul: 2019 International Conference on Computer Vision, 2019.

    [7] Zhang J W, Pan J S, Jimmy S J, et al. Dynamic scene deblurring using spatially variant recurrent neural networks [C]. Salt Lake City: 2018 IEEE Conference on Computer Vision and Pattern, 2018.

    [8] Tao X, Gao H Y, Shen X Y, et al. Scale-recurrent network for deep image deblurring [C]. Salt Lake City: 2018 IEEE Conference on Computer Vision and Pattern, 2018.

    [9] Zhang H G, Dai Y C, Li H D, et al. Deep stacked hierarchical multi-patch network for image deblurring [C]. Long Beach: 2019 IEEE Conference on Computer Vision and Pattern, 2019.

    [10] Park D W, Kang D U, Kim J, et al. Multi-temporal recurrent neural networks for progressive non-uniform single image deblurring with incremental temporal training [C]. Glasgow: 16th European Conference on Computer Vision, 2020.

    [11] Zhang K H, Luo W H, Zhong Y R, et al. Deblurring by realistic blurring [C]. Seattle: 2020 IEEE Conference on Computer Vision and Pattern, 2020.

    [12] Zou W, Jiang M,Zhang Y,et al. SDWNet: A straight dilated network with wavelet transformation for image deblurring [C]. Montreal: 2021 International Conference on Computer Vision, 2021.

    [13] Rim J, Lee H, Won J, et al. Real-world blur dataset for learning and benchmarking deblurring algorithms [C]. Glasgow: 16th European Conference on Computer Vision, 2020.

    [14] Ilya L,Frank H. Sgdr: Stochastic gradient descent with warm restarts [C]. Puerto Rico: 4th International Conference on Learning Representations, 2016.

    [15] Gao S H, Cheng M M, Zhao K, et al. Res2Net: A new multi-scale backbone architecture [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2021, 43(2): 652-662.

    WAN Yuan-yuan, SONG Zhuo-da, CHEN Xiao-lin, ZHU Xin-xin. on Image Deblurring Based on Multi-ScaleOptimization and Dynamic Feature Fusion[J]. INFRARED, 2023, 44(4): 33
    Download Citation