激光与光电子学进展, 2018, 55 (1): 012803, 网络出版: 2018-09-10 复制并引用该论文  本文已被引 3 次  被引通知

图 & 表

图 1. 有遮挡缺失的机载激光扫描点云及其重建DSM。(a)原始点云;(b)重建TIN模型;(c)重建DSM

Fig. 1. Airborne laser scanning point cloud with missing due to blocking and its reconstructed DSM. (a) Original laser point cloud; (b) reconstructed TIN model; (c) reconstructed DSM

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图 2. 建筑物顶面边缘点及顶点的提取结果。(a)矩形顶面;(b)圆形顶面

Fig. 2. Extraction of edge points and vertexes for top surface of building. (a) Rectangular top surface; (b) round top surface

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图 3. 模拟地形激光扫描点云及补充前后点云重建DSM。(a)模拟地形原始点云;(b)原始点云重建TIN模型;(c)原始点云重建DSM

Fig. 3. Laser scanning point cloud of simulative terrain and reconstructed DSM with point cloud before and after supplementation. (a) Original laser point cloud of simulative terrain; (b) reconstructed TIN model with original point cloud; (c) reconstructed DSM with original point cloud

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图 4. 补充边缘点前后不同插值方法得到的网格采样点高程值及其DSM。(a) cubic插值高程;(b) linear插值高程;(c) nearest 插值高程;(d)原始点云cubic插值DSM;(e)原始点云linear插值DSM;(f)原始点云nearest插值DSM;(g)补充边缘点后的cubic插值DSM;(h)补充边缘点后的linear插值DSM;(i)补充边缘点后的nearest插值DSM

Fig. 4. Elevations of points using different interpolation methods and reconstructed DSMs with point clouds before and after supplementation. (a) Interpolation elevations using cubic method; (b) interpolation elevations using linear method; (c) interpolation elevations using nearest method; (d) reconstructed DSM from original point cloud using cubic method; (e) reconstructed DSM from original point cloud using linear method; (f) reconstructed DSM from original point cloud using nearest method; (g) recon

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表 1不同插值算法下DSM各项精度指标

Table1. Precision of DSM at different interpolation methods

Point cloud Flightheight/m Cubic Linear Nearest em /m ds /m erms /m em /m ds /m erms /m em /m ds /m erms /m 300 4.5745 16.6057 17.2243 4.6206 16.5837 17.2154 4.2588 20.5453 20.9820 Original point cloud 375 2.8362 13.2277 13.5284 2.8780 13.2162 13.5260 2.6700 16.4284 16.6439 450 1.7436 10.6227 10.7649 1.7754 10.6052 10.7528 1.6477 13.2047 13.3071 300 -0.7149 6.8991 6.9360 -0.1272 6.1806 6.1819 0.4211 8.9990 9.0089 Supplementarypoint cloud 375 -0.5450 5.8088 5.8343 -0.1846 5.1922 5.1954 0.1708 7.6287 7.6306 450 -0.6522 5.9879 6.0233 -0.3766 5.4603 5.4733 -0.3478 6.8959 6.9046

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表 2不同差值算法下e_m、d_s和e_rms的误差降低比例

Table2. Proportional reduction of error of e_m, d_s and e_rms at different interpolation methods

Flight height/m PRE of cubic /% PRE of linear /% PRE of nearest /% em ds erms em ds erms em ds erms 300 84.37 58.45 59.73 97.25 62.73 64.09 90.11 56.20 57.71 375 80.78 56.09 56.87 93.59 60.71 61.59 93.60 53.56 54.15 450 62.59 43.63 44.05 78.79 48.51 49.10 78.89 47.78 48.11

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苗松, 王建军, 李云龙, 范媛媛. 基于建筑物激光点云边缘线自动提取提高DSM精度[J]. 激光与光电子学进展, 2018, 55(1): 012803. Miao Song, Wang Jianjun, Li Yunlong, Fan Yuanyuan. Digital Surface Model Accuracy Improvement Based on Edge Line Automatic Extraction of Building Laser Point Cloud[J]. Laser & Optoelectronics Progress, 2018, 55(1): 012803.