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Laser & Optoelectronics Progress, Volume. 56, Issue 19, 192805(2019)

Synthetic Aperture Radar Image Change Detection Based on Intuitionistic Fuzzy C-Core Mean Clustering Algorithm

Qiang Su1,2,3、*, Jingyu Yang1,2,3、**, and Yangping Wang1,2,3、***
Author Affiliations
  • 1School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
  • 2Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, Lanzhou, Gansu 730070, China;
  • 3Gansu Provincial Key Lab of System Dynamics and Reliability of Rail Transport Equipment, Lanzhou, Gansu 730070, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (7)
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    References (20)
    Cited By (5)
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    Figures & Tables(7)
    Flow chart of proposed algorithm

    Fig. 1. Flow chart of proposed algorithm

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    SAR images of river drying in region of Namibia. (a) Image in 2013; (b) image in 2015

    Fig. 2. SAR images of river drying in region of Namibia. (a) Image in 2013; (b) image in 2015

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    SAR images of change of river island in a river in Brazil. (a) Image in 2013; (b) image in 2015

    Fig. 3. SAR images of change of river island in a river in Brazil. (a) Image in 2013; (b) image in 2015

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    Change detection results of experiment 1. (a) FCM; (b) PCA K-means; (c) KFCM; (d) FCM-neighborhood; (e) proposed method; (f) standard result

    Fig. 4. Change detection results of experiment 1. (a) FCM; (b) PCA K-means; (c) KFCM; (d) FCM-neighborhood; (e) proposed method; (f) standard result

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    Change detection results of experiment 2. (a) FCM; (b) PCA K-means; (c) KFCM; (d) FCM-neighborhood; (e) proposed method; (f) standard result

    Fig. 5. Change detection results of experiment 2. (a) FCM; (b) PCA K-means; (c) KFCM; (d) FCM-neighborhood; (e) proposed method; (f) standard result

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    • Table 1. Quantitative analysis on change detection results of different algorithms in experiment 1

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      Table 1. Quantitative analysis on change detection results of different algorithms in experiment 1

      AlgorithmPfa /%Pma /%Poe /%Kappacoefficient /%
      FCM11.08571.776312.862071.82
      PCA K-means4.01881.63285.651686.81
      KFCM4.61271.71106.323785.31
      FCM-neighborhood3.42481.28324.708088.99
      Proposed method3.15050.91374.064290.50

    • Table 2. Quantitative analysis on change detection results of different algorithms in experiment 2

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      Table 2. Quantitative analysis on change detection results of different algorithms in experiment 2

      AlgorithmPfa /%Pma /%Poe /%Kappacoefficient /%
      FCM5.85460.96986.824480.90
      PCA K-means4.55710.70725.264385.01
      KFCM5.28500.67075.955783.26
      FCM-neighborhood3.84220.55944.401687.34
      Proposed method3.57580.47634.052188.32
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    Qiang Su, Jingyu Yang, Yangping Wang. Synthetic Aperture Radar Image Change Detection Based on Intuitionistic Fuzzy C-Core Mean Clustering Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(19): 192805

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Mar. 17, 2019

    Accepted: Apr. 17, 2019

    Published Online: Oct. 23, 2019

    The Author Email: Su Qiang (736449389@qq.com), Yang Jingyu (16587472@qq.com), Wang Yangping (1328396793@qq.com)

    DOI:10.3788/LOP56.192805

    Topics

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