Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1828005(2022)
Extraction and Simplification of three-dimensional Point Cloud Topological Features Using Piecewise Linear Morse Theory
Fig. 1. Computation of index function
Fig. 2. Weight computation of feature points
Fig. 3. Homomorphic shrinkage algorithm. (a) Before simplification; (b) after simplification
Fig. 4. Schematic of retention index
Fig. 5. Flow chart of the proposed algorithm
Fig. 6. Raw data. (a) kerolamp model; (b) helix model
Fig. 7. Delaunay triangulation construction. (a) kerolamp model; (b) helix model
Fig. 8. Piecewise linear falling Morse complex extracted by the proposed algorithm. (a) kerolamp model; (b) helix model
Fig. 9. Piecewise linear falling Morse complex extracted by the method in Ref.[24]. (a) kerolamp model; (b) helix model
Fig. 10. Feature extraction results for kerolamp model in different thresholds. (a) λ=0.8,XT =0.23; (b) λ=0.8,XT =0.3; (c) λ=0.8,XT =0.32
Fig. 11. Feature extraction results for helix model in different thresholds. (a) λ=0.7,XT
Fig. 12. Feature extraction results for model 1 in different noise levels. (a) 0 dB; (b) 10 dB; (c) 20 dB; (d) 50 dB
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Yongyu Wei, Chunkang Zhang, Xiaomei Shao, Yutian Ji, Yao Yin. Extraction and Simplification of three-dimensional Point Cloud Topological Features Using Piecewise Linear Morse Theory[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1828005
Category: Remote Sensing and Sensors
Received: Jun. 30, 2021
Accepted: Aug. 25, 2021
Published Online: Aug. 31, 2022
The Author Email: Zhang Chunkang (chkang_chd@163.com)