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Internal Wave Packet Characterization from SAR Images Using Empirical Mode Decomposition (EMD)

Authors: Xilin Gan; Weigen Huang; Jingsong Yang; Bin Fu;

Internal Wave Packet Characterization from SAR Images Using Empirical Mode Decomposition (EMD)

Abstract

This paper addresses the problem of the characterization of oceanic internal wave packets from SAR images. Empirical Mode Decomposition (EMD) provides a new strategy for extracting internal wave signatures, and offers the precision, flexibility and accuracy which are proved by Huang et al. in 1998. The EMD is employed in a scale-space analysis of SAR image profiles to locate and characterize the wave parameters of internal waves. First, the EMD is applied for the nonlinear internal wave temporal series of synthetic aperture radar (SAR) decomposition. Second, a criterion based on the theory that the max normalized deflection stands for the largest energy is introduced to detect the internal wave component. The results show that EMD is an excellent tool to detect internal waves against background noise, and to estimate, with a good degree of precision, soliton wavelengths from SAR ocean image profiles.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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