Journal of Infrared and Millimeter Waves, Volume. 42, Issue 2, 250(2023)
Spaceborne photon counting lidar point cloud denoising method with the adaptive mountain slope
Fig. 3. Schematic diagram of slope angle calculation of point cloud data and data segmentation processing diagram,(a) the angle of the elliptical domain under different slope angles, (b) slope angle calculation, (c) data segmentation, (d) consolidation of data segments
Fig. 7. ICESat-2 satellite transit area in the Area of Yellowstone National Park and Great Smoky Mountains Forest Park in the United States
Fig. 8. The spaceborne photon counting lidar matches the NEON data
Fig. 10. Denoising results of different denoising algorithms: (a) (d) (g) (j) the result of the algorithm of this paper processing Data1-4, (b) (e) (h) (k) the result of the LOF algorithm processing Data1-4, (c) (f) (i) (l) the result of the DBSCAN algorithm processing Data1-4
Fig. 13. The algorithm in this paper is compared with ATL08 data,(a)、(c)、(e)、(g) the results of processing and classifying Data1-4 for the algorithm herein, (b)、(d)、(f)、(h) the ATL08 data corresponding to Data1-4
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Guang-Hui HE, Hong WANG, Qiang FANG, Yong-An ZHANG, Dan-Lu ZHAO, Ya-Ping ZHANG. Spaceborne photon counting lidar point cloud denoising method with the adaptive mountain slope[J]. Journal of Infrared and Millimeter Waves, 2023, 42(2): 250
Category: Research Articles
Received: Sep. 6, 2022
Accepted: --
Published Online: Jul. 19, 2023
The Author Email: Hong WANG (wanghongee@163.com)