[4] [4] ZHANG Z Y, ZHENG L L, PIAO Y J, et al. Blind remote sensing image deblurring using local binary pattern prior［J］. Remote Sensing, 2022, 14(5): 1276.

[6] [6] LIM H, YU S, PARK K, et al. Texture-aware deblurring for remote sensing images using l0-based deblurring and l2-based fusion［J］. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 3094-3108.

[8] [8] KUPYN O, MARTYNIUK T, WU J R, et al. DeblurGAN-v2: deblurring (orders-of-magnitude) faster and better［C］//IEEE/CVF International Conference on Computer Vision (ICCV). Seoul: IEEE, 2019: 8878-8887.

[9] [9] LIN T Y, DOLLR P, GIRSHICK R, et al. Feature pyramid networks for object detection［C］//IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Honolulu: IEEE, 2017: 2117-2125.

[10] [10] SZEGEDY C, LIU W, JIA Y Q, et al. Going deeper with convolutions［C］//IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Boston: IEEE, 2015. doi:10.1109/CVPR.2015.7298594.

[11] [11] HOWARD A G, ZHU M L, CHEN B, et al. MobileNets: efficient convolutional neural networks for mobile vision applications［R］. Los Alamos: arXiv Preprint, 2017: arXiv: 1704. 04861.

[12] [12] CHO S-J, JI S-W, HONG J-P, et al. Rethinking coarse-to-fine approach in single image deblurring［C］//IEEE/CVF International Conference on Computer Vision(ICCV). Montreal: IEEE, 2021: 4621-4630.

[13] [13] LIU Y B, HARIDEVAN A, SCHOFIELD H, et al. Application of ghost-DeblurGAN to fiducial marker detection［C］//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Kyoto: IEEE, 2022: 6827-6832.

[14] [14] HAN K, WANG Y H, TIAN Q, et al. GhostNet: more features from cheap operations［C］//IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR). Seattle: IEEE, 2020: 1580-1589.

[15] [15] LI Z Y, GUO J Y, ZHANG Y T, et al. Reference-based multi-level features fusion deblurring network for optical remote sensing images［J］. Remote Sensing, 2022, 14(11): 2520.

[16] [16] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need［C］//NIPS'17: Proceedings of the 31st International Conference on Neural Information Processing Systems. Long Beach: NIPS, 2017: 6000-6010.

[17] [17] GAO H, YANG J, ZHANG Y, et al. A mountain-shaped single-stage network for accurate image restoration［R］. Los Alamos: arXiv Preprint, 2023: arXiv: 2305. 05146.

[18] [18] MAO X T, LIU Y M, SHEN W, et al. Deep residual Fourier transformation for single image deblurring［R］. Los Alamos: arXiv Preprint, 2021: arXiv: 2111. 11745.

[19] [19] KIM S-W, KOOK H-K, SUN J-Y, et al. Parallel feature pyramid network for object detection［C］//Computer Vision-ECCV 2018: 15th European Conference. Munich: ECCV, 2018: 239-256.

[20] [20] KUPYN O, BUDZAN V, MYKHAILYCH M, et al. DeblurGAN: blind motion deblurring using conditional adversarial networks［C］//IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Salt Lake City: IEEE, 2018: 8183-8192.

[21] [21] XIA G S, HU J W, HU F, et al. AID: a benchmark data set for performance evaluation of aerial scene classification［J］. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(7): 3965-3981.

[22] [22] NAH S, KIM H-T, LEE M-K. Deep multi-scale convolutional neural network for dynamic scene deblurring［C］//IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Honolulu: IEEE, 2017: 3883-3891.