Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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A Sequential LiDAR Waveform Decomposition Algorithm

  • Jung, Jin-Ha (Laboratory for Applications of Remote Sensing, Purdue University) ;
  • Crawford, Melba M. (Laboratory for Applications of Remote Sensing, Purdue University) ;
  • Lee, Sang-Hoon (Department of Industrial Engineering, Kyungwon University)
  • Received : 2010.12.10
  • Accepted : 2010.12.26
  • Published : 2010.12.30
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Abstract

LiDAR waveform decomposition plays an important role in LiDAR data processing since the resulting decomposed components are assumed to represent reflection surfaces within waveform footprints and the decomposition results ultimately affect the interpretation of LiDAR waveform data. Decomposing the waveform into a mixture of Gaussians involves two related problems; 1) determining the number of Gaussian components in the waveform, and 2) estimating the parameters of each Gaussian component of the mixture. Previous studies estimated the number of components in the mixture before the parameter optimization step, and it tended to suggest a larger number of components than is required due to the inherent noise embedded in the waveform data. In order to tackle these issues, a new LiDAR waveform decomposition algorithm based on the sequential approach has been proposed in this study and applied to the ICESat waveform data. Experimental results indicated that the proposed algorithm utilized a smaller number of components to decompose waveforms, while resulting IMP value is higher than the GLA14 products.

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References

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