NDLI: One-dimensional signal processing techniques for airborne laser bathymetry

Content Provider	IEEE Xplore Digital Library
Author	Wong, H. Antoniou, A.
Copyright Year	1980
Abstract	The application of one-dimensional signal processing techniques for the preprocessing of waveforms obtained in airborne laser bathymetry is investigated. Specifically, a special type of smoothing digital filter is used to remove noise in the waveforms while preserving the information content up to a desired degree. An algorithm, which incorporates a lowpass digital differentiator is then used to detect the bottom reflection. The optimal cutoff frequency of the differentiator is determined on the basis of the spectral content of the bottom reflection. After preprocessing, a waveform-decomposition technique recently described by the authors is used to separate the surface and bottom reflections for sea-depth estimation. In order to evaluate the effectiveness of the techniques developed, sea-depth estimates obtained are compared to corresponding estimates obtained by a local surveying company, and a high degree of agreement is observed between the two sets of results. When the resolution between the surface and bottom returns is low, the proposed techniques together with waveform decomposition offer a significant improvement in the sea-depth estimates.<>
Sponsorship	IEEE Geoscience and Remote Sensing Society IEEE URSI
Starting Page	35
Ending Page	46
Page Count	12
File Size	1096734
File Format	PDF
ISSN	01962892
Volume Number	32
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing Optical reflection Laser noise Signal processing algorithms Acoustic reflection Surface waves Sea surface Laser beam cutting Smoothing methods Digital filters
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Electrical and Electronic Engineering

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