改进的残差式3D-CNN和近邻注意力的高光谱遥感图像分类

潘增滢, 吴瑞姣, 林易丰, 翁谦, 林嘉雯

Hyperspectral remote sensing image classification using improved residual 3D-CNN and neighborhood attention

PAN Zengying, WU Ruijiao, LIN Yifeng, WENG Qian, LIN Jiawen

表2 不同方法在PU数据集上的分类结果

Tab.2 Classification results of different methods on the PU dataset

类别 1D-CNN 2D-CNN SSRN HybridSN A2S2K morphFormer LSGA IR3NAN 沥青路面 87.81 95.72 99.96 96.58 99.87 98.75 99.57 99.99 草地 90.85 97.50 99.60 99.77 99.97 99.91 99.88 99.98 碎石 57.84 69.74 92.47 86.49 94.52 89.45 89.90 97.49 树木 85.84 98.36 98.66 88.23 99.07 96.19 97.81 98.61 涂漆金属板 98.75 99.94 100.00 86.66 99.98 100.00 100.00 99.98 裸土 72.67 84.88 99.69 99.60 100.00 99.95 99.97 99.94 沥青 79.44 89.11 99.93 90.75 99.46 99.86 99.51 100.00 自阻砖 84.66 90.74 98.53 89.17 98.46 93.43 96.43 99.28 阴影 99.52 99.67 99.91 78.88 99.94 93.72 97.60 98.84 OA/% 85.82 93.72 99.18 95.71 99.48 98.26 98.85 99.67 AA/% 84.15 91.74 98.75 90.68 99.03 96.81 97.85 99.35 Kappa 0.812 3 0.916 1 0.989 2 0.943 0 0.993 1 0.976 9 0.984 8 0.995 6