Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 9,
  • Issue 5,
  • pp. 050101-
  • (2011)

Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition

Not Accessible

Your library or personal account may give you access

Abstract

Although the empirical mode decomposition (EMD) method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios (SNRs). The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function (IMF) by the EMD-based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.

© 2011 Chinese Optics Letters

PDF Article
More Like This
Mean estimation empirical mode decomposition method for terahertz time-domain spectroscopy de-noising

Xiaoli Qiao, Xinming Zhang, Jiaojiao Ren, Dandan Zhang, Guohua Cao, and Lijuan Li
Appl. Opt. 56(25) 7138-7145 (2017)

Empirical mode decomposition based background removal and de-noising in polarization interference imaging spectrometer

Chunmin Zhang, Wenyi Ren, Tingkui Mu, Lili Fu, and Chenling Jia
Opt. Express 21(3) 2592-2605 (2013)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved