Research Article
Local and Global Geometric Structure Preserving and Application to Hyperspectral Image Classification
Table 2
Classified performance for Indian Pine scene (%).
|
Item | Measurement | Overall accuracy | Kappa coefficient | Average accuracy |
| 1NN | | | | PCA | 67.37 | 62.72 | 71.02 | MFA | 28.57 | 19.25 | 26.51 | LapLDA | 48.29 | 40.96 | 50.68 | RP | 62.88 | 57.65 | 65.16 | LPP | 59.49 | 53.84 | 64.02 | LGSPP | 61.88 | 56.49 | 65.49 | JGLDA | 55.20 | 48.73 | 54.57 | LGGSP | 75.80 | 72.41 | 81.77 | 5NN | | | | PCA | 66.52 | 61.66 | 67.63 | MFA | 33.37 | 23.72 | 29.76 | LapLDA | 53.37 | 46.17 | 50.91 | RP | 64.34 | 58.99 | 65.21 | LPP | 60.98 | 55.13 | 62.35 | LGSPP | 63.63 | 58.19 | 64.36 | JGLDA | 58.51 | 51.84 | 51.47 | LGGSP | 76.62 | 73.33 | 80.99 | 9NN | | | | PCA | 66.32 | 61.26 | 67.27 | MFA | 36.14 | 25.98 | 29.39 | LapLDA | 55.66 | 48.32 | 49.08 | RP | 63.15 | 57.50 | 61.61 | LPP | 60.45 | 54.40 | 59.32 | JGSPP | 62.98 | 57.21 | 63.44 | JGLDA | 59.63 | 52.70 | 49.52 | LGGSP | 75.75 | 72.28 | 79.31 | Linear SVM | | | | PCA | 57.13 | 48.55 | 52.00 | MFA | 36.93 | 20.20 | 16.92 | LapLDA | 50.89 | 40.82 | 28.52 | RP | 52.32 | 41.90 | 31.22 | LPP | 54.47 | 45.59 | 46.36 | JGSPP | 54.87 | 45.35 | 41.65 | JGLDA | 47.88 | 35.26 | 33.52 | LGGSP | 63.08 | 55.95 | 48.33 | Polynomial SVM | | | | PCA | 62.40 | 55.74 | 60.29 | MFA | 41.78 | 30.94 | 29.77 | LapLDA | 51.97 | 43.37 | 37.87 | RP | 55.14 | 45.60 | 43.32 | LPP | 58.83 | 51.67 | 55.61 | LGSPP | 60.05 | 52.66 | 57.36 | JGLDA | 58.25 | 50.49 | 51.65 | LGGSP | 72.64 | 68.14 | 72.57 | RBF-SVM | | | | PCA | 73.69 | 69.92 | 76.21 | MFA | 24.26 | 0.12 | 6.35 | LapLDA | 56.31 | 48.94 | 50.06 | RP | 71.90 | 67.76 | 72.54 | LPP | 68.45 | 63.90 | 71.64 | LGSPP | 67.33 | 62.33 | 66.76 | JGLDA | 54.79 | 49.46 | 58.71 | LGGSP | 79.04 | 75.86 | 76.95 |
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