• Laser & Optoelectronics Progress
  • Vol. 58, Issue 2, 0210021 (2021)
Yuxiong Xu1, Xiaojun Yang1、*, Yongda Cai1, Xiaoyan Du2, and Xin Zhang1
Author Affiliations
  • 1College of Information Engineering, Guangdong University of Technology, Guangzhou, Guangdong 510006, China
  • 2Chinese People's Liberation Army 96630 Troops, Beijing 102206, China
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    DOI: 10.3788/LOP202158.0210021 Cite this Article Set citation alerts
    Yuxiong Xu, Xiaojun Yang, Yongda Cai, Xiaoyan Du, Xin Zhang. Hyperspectral Fast Clustering Algorithm Based on Binary Tree Anchor Points[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210021 Copy Citation Text show less
    Schematic of selecting anchor points for binary tree
    Fig. 1. Schematic of selecting anchor points for binary tree
    Flow chart of FHC-BTA algorithm
    Fig. 2. Flow chart of FHC-BTA algorithm
    Clustering map of each algorithm on Indian Pines dataset. (a) Ground map; (b) K-means; (c) FCM; (d) FCM_S1; (e) SC; (f) FHC-BTA_K; (g) FHC-BTA_R; (h) FHC-BTA
    Fig. 3. Clustering map of each algorithm on Indian Pines dataset. (a) Ground map; (b) K-means; (c) FCM; (d) FCM_S1; (e) SC; (f) FHC-BTA_K; (g) FHC-BTA_R; (h) FHC-BTA
    Clustering map of each algorithm on Salinas dataset. (a) Ground map; (b) K-means; (c) FCM; (d) FCM_S1; (e) FHC-BTA_K; (f) FHC-BTA_R; (g) FHC-BTA
    Fig. 4. Clustering map of each algorithm on Salinas dataset. (a) Ground map; (b) K-means; (c) FCM; (d) FCM_S1; (e) FHC-BTA_K; (f) FHC-BTA_R; (g) FHC-BTA
    Test results under Indian Pines dataset. (a) Different numbers of anchor points; (b) different numbers of nearest neighbors
    Fig. 5. Test results under Indian Pines dataset. (a) Different numbers of anchor points; (b) different numbers of nearest neighbors
    Test results under Salinas dataset. (a) Different numbers of anchor points; (b) different numbers of nearest neighbors
    Fig. 6. Test results under Salinas dataset. (a) Different numbers of anchor points; (b) different numbers of nearest neighbors
    ParameterK-meansFCMFCM_S1SCFHC-BTA_KFHC-BTA _RFHC-BTA
    AA/%36.3636.7934.3432.8138.4135.4639.14
    OA/%34.8935.5436.1734.1038.8235.7037.31
    Kappa0.27670.2880.29140.28240.31170.28680.3039
    Time/s3.872.354.007.863.300.611.10
    Table 1. Comparison of all algorithms on Indian Pines dataset
    ParameterK-meansFCMFCM_S1FHC-BTA _KFHC-BTA _RFHC-BTA
    AA/%65.5365.9066.3766.1064.2266.47
    OA/%66.6663.9067.0566.6067.6268.60
    Kappa0.62840.60060.63260.62730.64050.6511
    Time/s23.7112.4420.9661.627.5111.33
    Table 2. Comparison of all algorithms on Salinas dataset
    Yuxiong Xu, Xiaojun Yang, Yongda Cai, Xiaoyan Du, Xin Zhang. Hyperspectral Fast Clustering Algorithm Based on Binary Tree Anchor Points[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210021
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