Orientation-Independent Empirical Mode Decomposition for Images Based on Unconstrained Optimization

This paper introduces a 2D extension of the empirical mode decomposition (EMD), through a novel approach based on unconstrained optimization. EMD is a fully data-driven method that locally separates, in a completely data-driven and unsupervised manner, signals into fast and slow oscillations. The pr...

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Veröffentlicht in:	IEEE transactions on image processing 2016-05, Vol.25 (5), p.2288-2297
Hauptverfasser:	Colominas, Marcelo A., Humeau-Heurtier, Anne, Schlotthauer, Gaston
Format:	Artikel
Sprache:	eng
Schlagworte:	Computational efficiency data-driven Decomposition Empirical Mode Decomposition Engineering Sciences Frequency modulation Interpolation non-stationary image Optimization Oscillations Proposals Signal and Image processing Sparse matrices Splines (mathematics) State of the art Transaction processing Two dimensional unconstrained optimization
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