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Laser & Optoelectronics Progress, Volume. 56, Issue 5, 052801(2019)

Cloud Detection of ZY-3 Satellite Remote Sensing Images Based on Improved Fully Convolutional Neural Networks

Liang Pei1, Yang Liu1,2、*, Hai Tan2, and Lin Gao1
Author Affiliations
  • 1 School of Geomatics, Liaoning Technical University, Fuxin, Liaoning 123000, China
  • 2 Satellite Surveying and Mapping Application Center, NASG, Beijing 100048, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
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    References (18)
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    Figures & Tables(10)
    Schematic of FCNN

    Fig. 1. Schematic of FCNN

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    Schematic of principles of FCNN

    Fig. 2. Schematic of principles of FCNN

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    Schematic of principle of improved FCNN

    Fig. 3. Schematic of principle of improved FCNN

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    Structure diagram of improved FCNN

    Fig. 4. Structure diagram of improved FCNN

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    Input images and label pictures. (a) Input image 1; (b) label picture 1; (c) input image 2; (d) label picture 2

    Fig. 5. Input images and label pictures. (a) Input image 1; (b) label picture 1; (c) input image 2; (d) label picture 2

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    Convergence curves of Adam algorithm. (a) Loss; (b)accuracy

    Fig. 6. Convergence curves of Adam algorithm. (a) Loss; (b)accuracy

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    Convergence curves of SGD algorithm. (a) Loss; (b) accuracy

    Fig. 7. Convergence curves of SGD algorithm. (a) Loss; (b) accuracy

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    Comparison of detection results of different methods. (a) Original images; (b) label picture; (c) FCN-2s; (d) FCN-8s;(e) FCN-16s; (f) FCN-32s; (g) FCM+SVM

    Fig. 8. Comparison of detection results of different methods. (a) Original images; (b) label picture; (c) FCN-2s; (d) FCN-8s;(e) FCN-16s; (f) FCN-32s; (g) FCM+SVM

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    • Table 1. Accuracy comparison of different network structures

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      Table 1. Accuracy comparison of different network structures

      Types ofnetworkOverallaccuracyMeanaccuracyMeanIU
      FCN-8s0.89880.80100.7396
      FCN-16s0.89650.79630.7339
      FCN-32s0.88910.78670.7185

    • Table 2. Average accuracy and speed of detection results in different cloud areas

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      Table 2. Average accuracy and speed of detection results in different cloud areas

      Types of networkAccuracy /%Precision /%Recall /%F1-measure /%Detection time /s
      FCN-2s90.1196.9290.3693.530.46
      FCN-8s83.9694.1585.3589.532.24
      FCN-16s80.3692.4881.9486.892.30
      FCN-32s76.5288.2979.6783.762.36
      FCM+SVM83.7284.8984.6184.75>60.00
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    Liang Pei, Yang Liu, Hai Tan, Lin Gao. Cloud Detection of ZY-3 Satellite Remote Sensing Images Based on Improved Fully Convolutional Neural Networks[J]. Laser & Optoelectronics Progress, 2019, 56(5): 052801

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jul. 19, 2018

    Accepted: Sep. 12, 2018

    Published Online: Jul. 31, 2019

    The Author Email: Yang Liu (764039378@qq.com)

    DOI:10.3788/LOP56.052801

    Topics

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