Laser & Optoelectronics Progress, Volume. 60, Issue 16, 1610010(2023)

Hyperspectral Image Classification Based on Hyperpixel Segmentation and Convolutional Neural Network

Rujun Chen1, Yunwei Pu1,2、*, Fengzhen Wu1, Yuceng Liu1, and Qi Li1
Author Affiliations
  • 1Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
  • 2Computing Center, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
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    Figures & Tables(13)
    Proposed CNN
    Pseudo-color image and ground object truth map of the WHU-Hi-Longkou dataset. (a) Pseudo-color image; (b) real image
    Pseudo-color image and ground object truth map of the WHU-Hi-HongHu dataset. (a) Pseudo-color image; (b) real image
    Spectral information segmentation results on WHU-Hi-Longkou dataset. (a) KNN; (b) SVM; (c) RF; (d) CNN; (e) ground truth
    Spectral information segmentation results on WHU-Hi-HongHu dataset. (a) KNN; (b) SVM; (c) RF; (d) CNN; (e) ground truth
    Segmentation results of different hyperpixel algorithms on WHU-Hi-Longkou dataset. (a) SLICO; (b) PCA-SLICO; (c) SLIC; (d) PCA-SLIC; (e) MSLIC; (f) PCA-MSLIC
    Segmentation results of different hyperpixel algorithms on WHU-Hi-HongHu dataset. (a) SLICO; (b) PCA-SLICO; (c) SLIC; (d) PCA-SLIC; (e) MSLIC; (f) PCA-MSLIC
    Classification results of different methods on WHU-Hi-Longkou dataset. (a) PMS-KNN; (b) PMS-SVM; (c) PMS-RF;(d) PMS-CNN; (e) grouth truth
    Classification results of different methods on WHU-Hi-Longkou dataset. (a) PMS-KNN; (b) PMS-SVM; (c) PMS-RF;(d) PMS-CNN; (e) grouth truth
    • Table 1. CA of different algorithms on WHU-Hi-Longkou dataset

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      Table 1. CA of different algorithms on WHU-Hi-Longkou dataset

      CategoryKNNSVMRFCNN
      Corn94.9398.4188.5398.45
      Cotton76.8092.0276.8095.45
      Sesame82.9698.2582.2198.70
      Round leaf soybean69.0089.6057.1690.83
      Long leaf soybean88.3096.0569.8097.91
      Rice99.2499.4864.2098.68
      Wave99.8799.8892.1899.83
      Houses and roads87.8295.3782.3494.58
      Mixed weeds85.2896.1374.1897.41
      OA /%89.8896.7782.5197.18
      Kappa coefficient /%86.9795.7878.0096.31
    • Table 2. CA of different algorithms on WHU-Hi-HongHu dataset

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      Table 2. CA of different algorithms on WHU-Hi-HongHu dataset

      CategoryKNNSVMRFCNN
      Roof84.3776.0278.6792.17
      Road81.9783.5683.3978.81
      Exposed soil63.1574.4565.5073.66
      Cotton49.9067.6462.7587.36
      Cotton wood60.2178.7068.0564.24
      Rape66.5481.4072.5692.47
      Chinese cabbage45.3353.1046.3449.05
      Pakchoi38.8039.5620.9358.84
      Cabbage88.3889.1884.8188.28
      Mustard tuber38.7047.2040.4766.60
      Cauliflower31.9040.2230.3660.92
      Green vegetables56.9554.8154.3361.74
      Small green vegetables45.5649.1252.0471.80
      Asparagus lettuce61.5456.8244.3350.75
      Lettuce87.3080.4273.9182.85
      Film is covered with lettuce76.6769.8580.1482.85
      Thin film covered with lettuce78.5377.8270.3075.83
      Carrot68.3773.4068.3184.24
      Ternip68.6875.5671.6679.01
      Garlic bolt77.1380.3676.2076.94
      Bean71.1871.1076.6889.47
      Persimmon tree64.0277.3474.4787.46
      OA /%63.0272.6868.2685.43
      Kappa coefficient /%56.7867.0462.0282.10
    • Table 3. CA on WHU-Hi-Longkou dataset

      View table

      Table 3. CA on WHU-Hi-Longkou dataset

      CategoryPMS-KNNPMS-SVMPMS-RFPMS-CNN
      Corn97.7499.6494.3799.85
      Cotton83.5396.0366.1599.94
      Sesame89.9098.0683.0398.35
      Round leaf soybean76.5792.5270.8899.08
      Long leaf soybean93.8497.0276.1099.15
      Rice99.629.54099.0899.67
      Wave99.8899.8799.8599.72
      Houses and roads91.1594.7588.0495.36
      Mixed weeds86.4197.6481.5097.61
      OA /%92.7697.8089.3599.45
      Kappa coefficient /%90.6397.1086.3099.27
    • Table 4. CA on WHU-Hi-HongHu dataset

      View table

      Table 4. CA on WHU-Hi-HongHu dataset

      CategoryPMS-KNNPMS-SVMPMS-RFPMS-CNN
      Roof95.6280.3393.5898.38
      Road94.6083.6787.6294.02
      Exposed soil87.3691.3686.1396.33
      Cotton87.5484.4682.0098.10
      Cotton wood92.3484.3991.1899.45
      Rape87.9987.7986.4096.57
      Chinese cabbage74.9465.2672.0892.17
      Pakchoi86.6017.6077.2099.95
      Cabbage96.2891.7794.7397.60
      Mustard tuber73.4366.8676.9396.85
      Cauliflower78.0459.0087.9895.36
      Green vegetables86.7856.7585.8496.27
      Small green vegetables74.9673.1676.1497.06
      Asparagus lettuce86.9064.8087.9897.22
      Lettuce94.6667.8099.00100
      Film is covered with lettuce94.9585.5886.5599.10
      Thin film covered with lettuce95.2060.4096.84100
      Carrot94.4278.5495.6499.40
      Ternip87.0481.5486.5195.24
      Garlic bolt97.4480.7096.7398.58
      Bean99.70099.7099.70
      Persimmon tree95.8576.8699.2399.24
      OA /%88.9782.9086.8497.60
      Kappa coefficient /%86.3078.6783.8097.07
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    Rujun Chen, Yunwei Pu, Fengzhen Wu, Yuceng Liu, Qi Li. Hyperspectral Image Classification Based on Hyperpixel Segmentation and Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2023, 60(16): 1610010

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    Paper Information

    Category: Image Processing

    Received: Sep. 15, 2022

    Accepted: Nov. 8, 2022

    Published Online: Aug. 18, 2023

    The Author Email: Pu Yunwei (puyunwei@126.com)

    DOI:10.3788/LOP222551

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