• Laser & Optoelectronics Progress
  • Vol. 51, Issue 10, 102801 (2014)
Duan Yihao1、2、*, Zhang Aiwu1、2, Liu Zhao1, Wang Shumin3, Wang Jingmeng1、2, and Ye Qiuhong1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.3788/lop51.102801 Cite this Article Set citation alerts
    Duan Yihao, Zhang Aiwu, Liu Zhao, Wang Shumin, Wang Jingmeng, Ye Qiuhong. A Gaussian Inflexion Points Matching Method for Gaussian Decomposition of Airborne LiDAR Waveform Data[J]. Laser & Optoelectronics Progress, 2014, 51(10): 102801 Copy Citation Text show less

    Abstract

    Estimation of Gaussion components′ number is a core problem in the procedure of Gaussian decomposition of small- footprint full- waveform airborne LiDAR waveform data. A new approach named Gaussian inflexion points matching method (GIPM) is proposed to solve it. GIPM algorithm uses the quick locating algorithm for turning points in discrete point set of plane curve (QLATP) method for detecting the inflexion points (IFPs). The slope of the line between the detected IFP and its adjacent point is calculated. The detected IFPs are classified as left IFPs and right IFPs according to the slope. A left IFP and its neighboring right IFP comprise a Gaussian component, thus getting the number of the Gaussian components of waveform data. GIPM method is used to decompose the simulated and the measured waveform data, comparing with two traditional pulses detection method (center of gravity and Gaussian pulse fitting). The results demonstrate that the GIPM method can tremendously retain the impact of the pseudo IFPs, and quickly and accurately detect and decompose Gaussian components of the waveform data, and then immensely speed up the decomposition of waveform data. Meanwhile, it can get more Gaussian components than others, thus improving the density of point cloud.
    Duan Yihao, Zhang Aiwu, Liu Zhao, Wang Shumin, Wang Jingmeng, Ye Qiuhong. A Gaussian Inflexion Points Matching Method for Gaussian Decomposition of Airborne LiDAR Waveform Data[J]. Laser & Optoelectronics Progress, 2014, 51(10): 102801
    Download Citation