Method of DTM Extraction and Visualization using Threshold Segmentation and Mathematical Morphology

doi:10.23940/ijpe.19.03.p21.919929

Int J Performability Eng ›› 2019, Vol. 15 ›› Issue (3): 919-929.doi: 10.23940/ijpe.19.03.p21.919929

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Method of DTM Extraction and Visualization using Threshold Segmentation and Mathematical Morphology

Tianyong Wu^a, Yunsheng Zhao^{a, *}, and Xiang Li^b

a Faculty of Engineering, China University of Geosciences, Wuhan, 430074, China;
b School of Computer Science, China University of Geosciences, Wuhan, 430074, China

Submitted on ; Revised on ;
Contact: 421575900@qq.com
About author:Tianyong Wu is a faculty member at the China University of Geosciences. His research interests include machine learning and neural network algorithms.Yunsheng Zhao graduated from the China University of Geosciences with a bachelor's degree, Master's degree, and Ph.D. He is currently a professor at the China University of Geosciences and the director of the Department of Safety Engineering. His current research interests include system security theory and applications, safety information engineering, and occupational safety and health.Xiang Li is a professor in the School of Computer Science at the China University of Geosciences. His research interests include neural network algorithms, remote sensing classification, and recognition.

Abstract

Abstract: LiDAR (Light Detection and Ranging) is a laser ranging technology that provides an efficient and convenient way to obtain the original data from DSM (Demand Side Management). The basic task of LiDAR is to separate the high quality DTM (Digital Terrain Model) from the DSM, and the accuracy and quality of the generated image are determined by the different filtering and interpolation algorithms. According to this, this paper presents a filtering algorithm based on the optimal threshold segmenting optimized by the erosion operation (OTS-EO) to improve the problem that the manually-set-height difference threshold is empirically affected. In order to overcome the deficiency of the distance-based IDP (Inverse Distance to a Power) interpolation algorithm, an interpolation algorithm based on elevation and distance weighting is proposed to obtain the DSM to be further filtered. In this paper, the original laser point cloud data near the Xinyan rode in Beijing is taken as an example, and the data is processed by the algorithm based on threshold segmentation and mathematical morphology (TSMM) to extract the DTM. Finally, the 3D visualization of DTM is realized by the program based on MFC and OpenGL. The experimental data and practices in engineering show that the TSMM algorithm can successfully separate and display the surface points and surface features and extract the DTM close to the real ground to provide the foundation for further research.

Key words: LiDAR, threshold segmentation, mathematical morphology, digital terrain model, 3D visualization

Tianyong Wu, Yunsheng Zhao, and Xiang Li. Method of DTM Extraction and Visualization using Threshold Segmentation and Mathematical Morphology [J]. Int J Performability Eng, 2019, 15(3): 919-929.

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Method of DTM Extraction and Visualization using Threshold Segmentation and Mathematical Morphology

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