一种城区LiDAR点云数据的抽稀算法
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陈佩奇,赖旭东,李咏旭
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A Thinning Algorithm of LiDAR Point Cloud Data in Urban Area
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Peiqi Chen,Xudong Lai,Yongxu Li
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表2 实验结果
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Table 2 The experimental result
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| 编号 | 碟半径 /m | 计算耗时/s | 点云密度 （点/m2) | 实际抽稀率/% | 建筑物角 点数/个 | 建筑物角点保留率/% |
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| 1-1 | 1 | 3.01 | 1.99 | 94.73 | 180 | 98.90 | | 1-5 | 5 | 2.86 | 0.44 | 98.84 | 158 | 86.81 | | 1-10 | 10 | 2.94 | 0.22 | 99.41 | 128 | 70.33 | | 2-1 | 1 | 3.30 | 2.39 | 93.35 | 184 | 100.00 | | 2-5 | 5 | 3.16 | 0.53 | 98.53 | 161 | 87.50 | | 2-10 | 10 | 3.10 | 0.27 | 99.26 | 133 | 72.28 | | 3-1 | 1 | 2.17 | 1.46 | 94.40 | 50 | 83.33 | | 3-5 | 5 | 2.25 | 0.32 | 98.86 | 41 | 68.33 | | 3-10 | 10 | 2.15 | 0.16 | 99.42 | 35 | 58.33 | | 4-1 | 1 | 2.27 | 1.59 | 92.70 | 156 | 100.00 | | 4-5 | 5 | 2.23 | 0.43 | 98.03 | 130 | 83.33 | | 4-10 | 10 | 2.2 | 0.22 | 99.00 | 104 | 66.67 | | 平均-1 | 1 | 10.75 | 2.48 | 93.80 | / | 97.59 | | 平均-5 | 5 | 10.5 | 0.57 | 98.57 | / | 84.19 | | 平均-10 | 10 | 10.39 | 0.29 | 99.27 | / | 68.73 |
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