Airborne LiDAR point cloud filtering using saliency division

Fajie Feng; Yazhou Ding; Junping Li; Xingbei Huang; Xinyi Liu

doi:10.3788/IRLA20190439

Journals >Infrared and Laser Engineering >Volume 49 >Issue 8 >Page 20190439 > Article

Infrared and Laser Engineering
Vol. 49, Issue 8, 20190439 (2020)

Airborne LiDAR point cloud filtering using saliency division

Fajie Feng¹, Yazhou Ding¹, Junping Li¹, Xingbei Huang², and Xinyi Liu^2、*

Author Affiliations

¹Power China Hubei Electric Engineering Corporation Limited, Wuhan 430040, China

²School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

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DOI: 10.3788/IRLA20190439 Cite this Article

Fajie Feng, Yazhou Ding, Junping Li, Xingbei Huang, Xinyi Liu. Airborne LiDAR point cloud filtering using saliency division[J]. Infrared and Laser Engineering, 2020, 49(8): 20190439 Copy Citation Text

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Fig. 1. Virtual grid

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Fig. 2. Elevation mutations detection in multiple directions

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Fig. 3. Ground saliency calculating

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Fig. 4. Layered map of point cloud elevation(a) and gray rendering map of ground saliency(b)

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Fig. 5. Roofs of special shape building

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Fig. 6. Ground saliency distribution of center sunken buildings area

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Fig. 7. Comparison of filtering result of site 1 and 9. (a) Filtering result of site 1; (b) original point clouds; (c) filtering result of site 9; (d) original point clouds

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Area	Terrain properties
Area	Topographic relief	Objects
1	Smooth	Buildings, vegetation, waterbody
2	Smooth	Complicated buildings, vegetation
3	Smooth	Complicated buildings, viaduct
4	Smooth	Complicated buildings, vegetation
5	Large	Buildings, waterbody, terrain fault
6	Large	Vegetation, buildings, viaduct
7	Smooth	Buildings and vegetation
8	Large	Buildings, power line, viaduct
9	Large	Slope, vegetation, steep, viaduct

Table 1.

Landform in each subarea

各子测区地形

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Data type	Filtering results		Sum
Data type	Ground	Non-ground	Sum
Ground	a	b	e = a + b
Non-ground	c	d	f = c + d
Sum	g = a + c	h = b + d	n = e + f

Table 2.

Assessment criteria of crosstab method

交叉表法评价指标

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γ₁	γ₂	Site1			Site2
γ₁	γ₂	E1	E2	Et	E1	E2	Et
0.375	0.5	4.0	4.6	4.3	4.7	7.4	5.4
0.375	0.625	4.0	4.7	4.4	4.8	7.4	5.5
0.375	0.75	4.0	4.7	4.4	5.0	7.3	5.7
0.375	0.875	4.0	4.7	4.4	5.3	7.3	5.8
0.5	0.625	4.0	3.6	3.8	5.2	7.1	5.6
0.5	0.75	4.0	3.6	3.8	5.3	7.0	5.8
0.5	0.875	4.0	3.6	3.8	5.5	7.0	5.9
0.625	0.75	4.0	3.3	3.6	6.3	6.3	6.3
0.625	0.875	4.0	3.3	3.6	6.5	6.3	6.4
0.75	0.875	4.0	3.2	3.6	8.7	5.2	7.8

Table 3.

Error rate in different terrains using different threshold γ(%)

在不同区域使用不同γ阈值的错误率(%)

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Area	PM				PTD				CSF				Proposed
Area	E1	E2	Et	K	E1	E2	Et	K	E1	E2	Et	K	E1	E2	Et	K
1	4.29	3.62	3.93	92.09	3.45	5.49	4.54	90.89	3.99	4.02	4.00	90.63	4.00	3.15	3.55	92.87
2	5.65	7.57	6.72	86.41	3.17	8.43	6.11	87.68	6.06	6.46	6.29	85.54	3.76	7.00	5.57	88.75
3	4.50	3.90	4.19	91.60	2.01	4.27	3.19	93.60	4.64	3.86	4.23	90.97	3.61	3.12	3.36	93.27
4	6.77	6.01	6.38	87.23	3.34	5.58	4.50	90.99	4.67	6.81	5.78	86.32	5.27	5.11	5.19	89.61
5	3.41	4.61	4.19	90.90	3.80	4.47	4.23	90.78	7.38	3.89	5.11	88.76	3.31	3.96	3.73	91.88
6	6.58	3.99	4.88	89.22	6.22	3.25	4.27	90.53	2.92	5.25	4.45	88.60	3.30	3.24	3.26	92.82
7	11.58	9.35	10.67	78.17	3.22	9.09	5.62	88.29	3.62	11.53	6.86	83.62	4.98	10.51	7.24	84.93
8	9.06	3.16	6.05	87.89	2.85	4.35	3.61	92.76	2.29	6.02	4.20	90.03	3.11	3.30	3.21	93.58
9	6.81	3.34	4.71	90.12	3.32	5.05	4.37	90.93	4.93	12.89	9.74	79.37	2.53	5.70	4.45	90.80

Table 4.

Comparison and analysis of filtering accuracy

滤波精度对比分析

Fajie Feng, Yazhou Ding, Junping Li, Xingbei Huang, Xinyi Liu. Airborne LiDAR point cloud filtering using saliency division[J]. Infrared and Laser Engineering, 2020, 49(8): 20190439

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