A comparison of signal deconvolution algorithms based on small-footprint LiDAR waveform simulation

Jiaying Wu, J. A.N. Van Aardt, Gregory P. Asner

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

A raw incoming (received) Light Detection And Ranging (LiDAR) waveform typically exhibits a stretched and relatively featureless character, e.g., the LiDAR signal is smeared and the effective spatial resolution decreases. This is attributed to a fixed time span allocated for detection, the sensor's variable outgoing pulse signal, receiver impulse response, and system noise. Theoretically, such a loss of resolution can be recovered by deconvolving the system response from the measured signal. In this paper, we present a comparative controlled study of three deconvolution techniques, namely, Richardson-Lucy, Wiener filter, and nonnegative least squares, in order to verify which method is quantitatively superior to others. These deconvolution methods were compared in terms of two use cases: 1) ability to recover the true cross-sectional profile of an illuminated object based on the waveform simulation of a virtual 3-D tree model and 2) ability to differentiate herbaceous biomass based on the waveform simulation of virtual grass patches. All the simulated waveform data for this study were derived via the "Digital Imaging and Remote Sensing Image Generation" radiative transfer modeling environment. Results show the superior performance for the Richardson-Lucy algorithm in terms of small root mean square error for recovering the true cross section, low false discovery rate for detecting the unobservable local peaks in the stretched raw waveforms, and high classification accuracy for differentiating herbaceous biomass levels.

Original languageEnglish (US)
Article number5714011
Pages (from-to)2402-2414
Number of pages13
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume49
Issue number6 PART 2
DOIs
StatePublished - Jun 1 2011
Externally publishedYes

Fingerprint

Deconvolution
deconvolution
footprint
Biomass
Signal receivers
Radiative transfer
Impulse response
Mean square error
simulation
Remote sensing
biomass
Imaging techniques
radiative transfer
Sensors
spatial resolution
cross section
grass
sensor
filter
remote sensing

Keywords

  • Deconvolution
  • Light Detection And Ranging (LiDAR)
  • nonnegative least squares (NNLS)
  • Richardson-Lucy (RL)
  • simulation
  • waveform
  • Wiener filter (WF)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

Cite this

A comparison of signal deconvolution algorithms based on small-footprint LiDAR waveform simulation. / Wu, Jiaying; Van Aardt, J. A.N.; Asner, Gregory P.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 6 PART 2, 5714011, 01.06.2011, p. 2402-2414.

Research output: Contribution to journalArticle

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