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Bootstrap Empirical Mode Decomposition with Application to CIELAB Color Images

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posted on 13.09.2021, 18:29 by Kai-Yew LumKai-Yew Lum
This paper proposes an alternative optimization-based EMD based on the notions of: 1. local mean points that impose mode symmetry via a Tikhonov regularized least-square (RLS) problem, and 2. efficient bootstrap sifting that guarantees asymptotic convergence of the mean envelope to the local mean points, regardless of regularization. Mathematical proof of convergence and a straightforward extension to the 2D-multivariate setting and CIELAB color image sare presented. Performance is demonstrated with a univariate signal and two images. Spectral analysis confirms coordinated feature extraction among image components, and separation of spatial spectra among the intrinsic mode functions.

History

Email Address of Submitting Author

kylum@ncnu.edu.tw

ORCID of Submitting Author

https://orcid.org/0000-0002-5594-0142

Submitting Author's Institution

National Chi Nan Univesity

Submitting Author's Country

Taiwan