Improved Method for LiDAR Point Cloud Data Filtering Based on Hierarchical Pseudo-Grid

Zuowei Huang; Feng Liu; Guangwei Hu

doi:10.3788/AOS201737.0828004

Acta Optica Sinica, Volume. 37, Issue 8, 0828004(2017)

Improved Method for LiDAR Point Cloud Data Filtering Based on Hierarchical Pseudo-Grid

Zuowei Huang^1、*, Feng Liu², and Guangwei Hu¹

Author Affiliations

¹ School of Architecture and Urban Planning, Hunan University of Technology, Zhuzhou, Hunan 412000, China

² School of Geosciences and Information-Physics, Central South University, Changsha, Hunan 410083, China

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Abstract Get PDF(in Chinese)

Figures & Tables(13)

Fig. 1. Schematic diagram of pseudo-grid. (a) Three-dimensional display; (b) two-dimensional display

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Fig. 2. Construction process of pseudo-grid

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Fig. 3. Flow chart of improved filtering algorithm

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Fig. 4. Filtering flow chart based on CUDA

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Fig. 5. Filtering result of sample 11. (a) DSM of sample data; (b) result after filtering with slope method; (c) result after filtering with the improved method; (d) real DEM provide by ISPRS; (e) error distribution map

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Fig. 6. Comparison of type II error with different algorithms

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Fig. 7. Comparison of processing time with different algorithms

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Fig. 8. Experimental data. (a) Original point cloud data; (b) DSM grey-scale map of after meshing

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Fig. 9. Experiment results. (a) Filtering result of this method; (b) filtering result of progressive TIN filtering algorithm; (c) filtering result of slope filtering algorithm; (d) DEM after filtering

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Table 1. Attributes of filtering data
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Table 1. Attributes of filtering data
Data Data 1 Data 2 Data 3
Sensor ALS50-Ⅱ ALS50-Ⅱ ALS60
Time 2012.4 2012.5 2012.4
Altitude /m 1250 1250 2000
Number 185673 267859 381623
Mean point density /m^-2 1.6 2.5 3.2
Coverage /km² 0.12 0.17 0.19

Table 2. Parameters of data filtering
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Table 2. Parameters of data filtering
Number Max grid scale /m Slope threshold S_t S_i S_m
1 75 15 20 15 40
2 75 15 25 15 40
3 75 15 20 20 40
4 75 15 15 15 40

Table 3. Filtering error statistics of three groups data under different parameters

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Table 3. Filtering error statistics of three groups data under different parameters

Experiential data	Number				Gross error /%
Data 1	1	10.56	5.78	7.78
	2	11.23	5.89		8.12
	3	12.35	5.23		10.11
	4	14.68	7.43		12.35
Data 2	1	9.56	5.51	5.88
	2	10.45	6.34		8.12
	3	13.45	5.68		9.34
	4	15.67	8.67		9.58
Data 3	1	10.34	6.45	9.17
	2	11.57	7.78		9.35
	3	14.56	5.69		9.09
	4	15.67	4.93		8.74

Table 4. Comparison table of filtering error and efficiency of different algorithms

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Table 4. Comparison table of filtering error and efficiency of different algorithms

Data	Filtering method	Type I error /%	Type II error /%	Gross error /%	Efficiency /s
	Progressive TIN	13.58	7.32	9.12	18.4
Data 1	Slope filtering	14.78	8.56	9.56	11.5
	This method	10.56	5.78	7.78	2.3
	Progressive TIN	11.85	4.60	9.89	17.7
Data 2	Slope filtering	13.43	6.78	10.67	10.4
	This method	9.56	5.51	5.88	1.3
	Progressive TIN	12.58	4.47	10.01	19.7
Data 3	Slope filtering	13.45	7.89	12.56	11.5
	This method	10.34	6.45	9.17	0.9

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Zuowei Huang, Feng Liu, Guangwei Hu. Improved Method for LiDAR Point Cloud Data Filtering Based on Hierarchical Pseudo-Grid[J]. Acta Optica Sinica, 2017, 37(8): 0828004

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Paper Information

Category: Remote Sensing and Sensors

Received: Jan. 10, 2017

Accepted: --

Published Online: Sep. 7, 2018

The Author Email: Huang Zuowei (huangzuowei4@126.com)

DOI:10.3788/AOS201737.0828004

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Attributes of filtering data

Table 1. Attributes of filtering data

Table 2. Parameters of data filtering

Table 2. Parameters of data filtering

Table 3. Filtering error statistics of three groups data under different parameters

Table 3. Filtering error statistics of three groups data under different parameters

Table 4. Comparison table of filtering error and efficiency of different algorithms

Table 4. Comparison table of filtering error and efficiency of different algorithms