• Journal of Applied Optics
  • Vol. 40, Issue 5, 786 (2019)
HONG Hanyu1,*, SUN Jianguo1, LUAN Ling2, WANG Shuo1, and ZHENG Xinbo2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.5768/jao201940.0502001 Cite this Article
    HONG Hanyu, SUN Jianguo, LUAN Ling, WANG Shuo, ZHENG Xinbo. Aerial image de-roping based on U-net model[J]. Journal of Applied Optics, 2019, 40(5): 786 Copy Citation Text show less
    References

    [1] BURNS J B, HANSON A R, RISEMAN E M.Extracting straight lines[J].IEEE Trans. Pattern Analysis and Machine Intelligence, 1986, 8(4): 425-455.

    [2] XU L, OJA E, KULTANEN P. A new curve detection method: randomized Hough transform (RHT)[J]. Pattern Recognition Letters, 1990, 11(5): 331-338.

    [3] QIAO Yinqi, XIAO Jianhua, HUANG Yin, et al. Random Hough transform line detection based on least squares correction[J]. Journal of Computer Applications, 2015, 35(11): 3312-3315.

    [4] HONG Hanyu. Modern image graphics processing and analysis [M]. Wuhan: China University of Geosciences Press, 2011.

    [5] XU Wei, TANG Zhenmin, LYU Jianyong. Detection of pavement crack based on image saliency[J]. Journal of Image and Graphics, 2013, 18(1): 69-77.

    [6] ALEXANDRU T.An image inpainting technique based on the fast marching method[J]. Journal of Graphics Tools, 2004, 9(1): 23-34.

    [7] GAO Kaiwei, SUN Yiyuan, YAO Guangshun, et al. Semantic segmentation of night vision images of unmanned vehicles based on deep learning[J]. Journal of Applied Optics, 2017, 38(3): 421-427.

    [8] LONG J , SHELHAMER E , DARRELL T . Fully convolutional networks for semantic segmentation[J].IEEE Transactions on Pattern Analysis & Machine Intelligence, 2014, 39(4): 640-651.

    [9] BADRINARAYANAN V, KENDALL A, CIPOLLA R. Segnet: A deep convolutional encoder-decoder architecture for image segmentation[J]. ArXiv Preprint ArXiv, 2015, 1511: 00561.

    [10] RONNEBERGER O, FISCHER P, BROX T. U-net: Convolutional networks for biomedical image segmentation[C]//International Conference on MedicalImage Computing and Computer-assistedIntervention. Cham: Springer, 2015: 234-241.

    [11] LIU Zhe, ZHANG Xiaolin, SONG Yuqing, et al. Combined liver segmentation of U-Net and morphsnakes[J]. Journal of Image and Graphics, 2018, 23(8): 1254-1262.

    [12] OTSU N . A threshold selection method from Gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2007, 9(1): 62-66.

    [13] BEN P, SUBHANEIL L, MAITHRA R, et al. Exponential expressivity in deep neural networks through transient chaos[C]//Advances in Neural Information Processing Systems.[S.l]: arXiv, 2016: 3360-3368.

    [14] IOFFE S, SZEGEDY C. Batch normalization: accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the 32nd International Conference on International Conference on Machine Learning.[S.l]: arXiv, 2015: 448-456.

    [15] CHOLLET F. Xception: Deep learning with depthwise separable convolutions[C]// IEEE Conference on Computer Vision and Pattern Recognition.USA: IEEE, 2016: 1800-1807.

    [16] HE K, ZHANG X, REN S, et al. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification[C]//Proceedings of the IEEE International Conference on Computer Vision.USA: IEEE, 2015: 1026-1034.

    [17] ZHANG Hongying, PENG Qizhen. Overview of digital image restoration technology [J]. Journal of Image and Graphics, 2007, 12(1): 1-10.

    HONG Hanyu, SUN Jianguo, LUAN Ling, WANG Shuo, ZHENG Xinbo. Aerial image de-roping based on U-net model[J]. Journal of Applied Optics, 2019, 40(5): 786
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