改进Transformer的高光谱图像地物分类方法——以黄河三角洲为例

李薇, 樊彦国, 周培希

Improved Transformer-based hyperspectral image classification method for surface features: A case study of the Yellow River Delta

LI Wei, FAN Yanguo, ZHOU Peixi

表1 NC16数据集的不同方法的分类结果

Tab.1 Classification results of different methods for NC16 datasets(%)

类别 查全率 SVM 1DCNN CDCNN SSRN HybridSN ViT 本文方法 碱蓬 93.91 99.76 99.63 99.64 96.23 98.78 99.87 水泥路 94.46 88.02 92.19 87.61 78.10 64.34 81.59 沥青柏油路 93.12 87.09 87.02 87.97 74.33 80.28 91.56 水域 89.97 99.10 91.67 98.38 96.41 97.75 99.99 石块 71.45 93.19 95.15 93.40 76.00 95.48 78.23 草地 80.52 76.74 73.33 73.71 91.53 74.47 74.44 铁杆 0 0 0 12.50 0 31.25 33.50 柽柳 0 60.46 85.98 55.81 49.87 54.56 82.29 枯萎的芦苇 50.16 57.40 66.24 53.03 79.66 70.28 66.25 芦苇 47.15 52.76 78.23 73.18 54.18 63.69 71.19 互花米草 98.72 94.11 95.36 86.54 92.00 95.74 96.37 苔藓 31.50 67.89 71.50 76.42 98.02 73.72 72.16 旱田 84.93 82.00 88.64 92.74 96.57 96.07 94.94 湿地 97.36 91.92 91.68 94.64 99.93 94.15 97.40 滩涂 65.41 82.19 93.91 68.20 93.91 88.01 94.87 标准反射板 0 100.00 57.60 43.80 31.00 93.75 100.00 OA 85.76 92.63 92.72 94.99 94.18 94.62 96.24 AA 62.42 77.04 79.25 74.85 75.48 79.52 83.42 Kappa 80.82 89.86 90.01 93.12 92.11 92.62 94.80