递归滤波与KNN的高光谱遥感图像分类方法
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涂兵, 张晓飞, 张国云, 王锦萍, 周瑶
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Hyperspectral image classification via recursive filtering and KNN
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Bing TU, Xiaofei ZHANG, Guoyun ZHANG, Jinping WANG, Yao ZHOU
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表4 Salinas高光谱图像不同算法分类精度(0.2%训练样本)
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Tab.4 Salinas data set classification accuracy of different algorithms (0.2% of training samples)
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| 指标 类别 | 训练样
本/个 | 测试样
本/个 | SVM | SRC | JSRC | EMP | EPF | IFRF | LMLL | RF-KNN | | CA | Weeds_1 | 4 | 2 005 | 99.97
(0.04) | 96.22
(1.21) | 100.00
(0.00) | 95.22
(9.57) | 100.00
(0.00) | 95.83
(5.08) | 99.56
(0.41) | 94.54
(8.02) | | Weeds_2 | 8 | 3 718 | 94.87
(5.09) | 97.60
(1.88) | 99.70
(0.32) | 98.95
(0.47) | 99.96
(0.08) | 99.77
(0.49) | 99.74
(0.13) | 99.09
(3.72) | | Fallow | 4 | 1 972 | 86.58
(4.53) | 81.85
(13.07) | 92.11
(9.31) | 75.79
(17.54) | 88.15
(1.26) | 98.00
(2.63) | 99.62
(0.18) | 100.00
(0.00) | | Fallow_P | 3 | 1 391 | 97.17
(0.48) | 99.07
(0.49) | 56.96
(18.30) | 99.01
(0.53) | 97.47
(0.62) | 91.10
(8.78) | 56.70
(2.61) | 76.62
(8.58) | | Fallow_S | 5 | 2 673 | 97.94
(0.80) | 90.47
(4.61) | 79.07
(6.65) | 94.52
(2.44) | 93.95
(7.58) | 98.54
(2.22) | 99.13
(0.38) | 93.52
(4.98) | | Stubble | 8 | 3 951 | 99.98
(0.06) | 99.59
(0.10) | 99.83
(0.14) | 97.05
(2.45) | 99.97
(0.04) | 100.00
(0.00) | 99.52
(0.21) | 97.77
(1.28) | | Celery | 7 | 3 572 | 95.19
(3.65) | 98.55
(1.62) | 96.41
(1.60) | 99.34
(0.21) | 97.79
(3.06) | 99.39
(0.69) | 99.73
(0.09) | 98.64
(1.49) | | Graps | 21 | 11 250 | 64.31
(4.69) | 69.24
(5.61) | 89.36
(2.82) | 85.68
(7.31) | 70.03
(7.78) | 95.22
(5.66) | 88.20
(1.35) | 93.77
(4.58) | | Soil | 11 | 6 192 | 99.59
(0.03) | 96.97
(0.59) | 99.61
(0.67) | 99.26
(0.64) | 92.56
(10.95) | 98.58
(3.35) | 99.01
(1.16) | 100.00
(0.00) | | Corn | 3 | 3 275 | 77.73
(8.42) | 54.75
(20.40) | 79.57
(1.88) | 73.97
(16.68) | 91.63
(4.47) | 98.94
(0.70) | 90.02
(3.62) | 97.92
(1.69) | | Lettuce_4wk | 3 | 1 065 | 64.29
(6.73) | 93.12
(3.49) | 80.56
(9.38) | 94.80
(1.60) | 76.28
(28.19) | 98.75
(0.40) | 92.94
(0.75) | 88.26
(5.87) | | Lettuce_5wk | 4 | 1 923 | 92.36
(3.56) | 97.32
(3.13) | 71.45
(13.17) | 99.95
(0.12) | 96.28
(6.13) | 92.19
(3.75) | 100.00
(0.00) | 80.09
(14.87) | | Lettuce_6wk | 2 | 914 | 89.61
(10.32) | 97.19
(1.66) | 56.09
(13.08) | 98.49
(0.44) | 86.04
(8.46) | 83.58
(16.15) | 97.55
(0.65) | 71.66
(19.57) | | Lettuce_7wk | 2 | 1 068 | 71.56
(18.02) | 81.08
(4.11) | 94.41
(1.47) | 92.57
(3.86) | 98.83
(0.77) | 81.37
(17.11) | 96.66
(1.97) | 60.28
(22.83) | | Vinyard_U | 13 | 7 255 | 45.34
(4.69) | 53.50
(6.93) | 70.38
(8.04) | 72.99
(8.62) | 87.61
(10.47) | 89.90
(6.73) | 72.37
(2.60) | 96.61
(1.49) | | Vinyard_T | 4 | 1 803 | 93.56
(10.78) | 73.55
(11.52) | 96.14
(4.08) | 86.88
(8.76) | 99.93
(0.09) | 99.63
(1.17) | 96.04
(5.00) | 99.80
(0.45) | | OA | — | — | 79.33
(1.99) | 81.14
(1.39) | 87.44
(1.02) | 89.32
(2.00) | 86.23
(2.51) | 94.40
(2.08) | 91.48
(0.87) | 94.93
(1.26) | | AA | — | — | 85.63
(1.86) | 86.25
(1.21) | 85.10
(0.88) | 91.53
(1.38) | 92.28
(1.89) | 94.05
(1.98) | 92.93
(0.91) | 94.69
(1.40) | | Kappa | — | — | 77.14
(2.15) | 78.97
(1.52) | 85.99
(1.14) | 88.08
(2.22) | 84.55
(2.88) | 94.18
(2.32) | 90.50
(0.97) | 94.41
(3.05) |
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