Two-dimensional Variational Mode Decomposition

Variationally decompose a 2D signal into k band-separated modes.
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Updated 18 Mar 2014

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Spectrum-based decomposition of a 2D input signal into k band-separated modes. Here, we propose an entirely non-recursive variational mode decomposition model, where the modes are extracted concurrently. The model looks for an ensemble of modes and their respective center frequencies, such that the modes collectively reproduce the (2D) input signal, while each being smooth after demodulation into baseband. The variational model is efficiently optimized using an alternating direction method of multipliers approach.
This is a generalization of 1D VMD:
http://www.mathworks.com/matlabcentral/fileexchange/44765-variational-mode-decomposition
See: K. Dragomiretskiy and D. Zosso, Variational Mode Decomposition, IEEE Trans. Signal Processing 62(3):531-544, 2014. http://dx.doi.org/10.1109/TSP.2013.2288675

and

K. Dragomiretskiy and D. Zosso, Two-Dimensional Variational Mode Decomposition, IEEE Int. Conf. Image Proc. 2014, (submitted). Preprint: ftp://ftp.math.ucla.edu/pub/camreport/cam14-16.pdf

Cite As

Dominique Zosso (2024). Two-dimensional Variational Mode Decomposition (https://www.mathworks.com/matlabcentral/fileexchange/45918-two-dimensional-variational-mode-decomposition), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012a
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Version Published Release Notes
1.1.0.0

Fixed the visualization bug described in comments.

Fixed a wrong "division by 2" in the computation of the Hilbert-frequency mask.

1.0.0.0