The Monogenic Synchrosqueezed Wavelet Transform: A tool for the Decomposition/Demodulation of AM-FM images
By Marianne Clausel, Thomas Oberlin, Valérie Perrier. 2012
41 citations recorded by the source corpus.
The synchrosqueezing method aims at decomposing 1D functions as superpositions of a small number of ''Intrinsic Modes'', supposed to be well separated both in time and frequency. Based on the unidimensional wavelet transform and its reconstruction properties, the synchrosqueezing transform provides a powerful representation of multicomponent signals in the time-frequency plane, together with a reconstruction of each mode. In this paper, a bidimensional version of the synchrosqueezing transform is defined, by considering a well--adapted extension of the concept of analytic signal to images: the monogenic signal. The natural bidimensional counterpart of the notion of Intrinsic Mode is then the concept of ''Intrinsic Monogenic Mode'' that we define. Thereafter, we investigate the properties of its associated Monogenic Wavelet Decomposition. This leads to a natural bivariate extension of the Synchrosqueezed Wavelet Transform, for decomposing and processing multicomponent images. Numerical tests validate the effectiveness of the method for different examples.
Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Geophysics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Sylvain Meignen
- Ratikanta Behera
- Thomas Oberlin
- Chris Biemann
- Douglas B. Kell
- Constantinos S. Pattichis
- Andreas Holzinger
- Duong-Hung Pham
In Control and Systems Engineering
- Sylvain Meignen
- Ratikanta Behera
- Thomas Oberlin
- Douglas B. Kell
- Andreas Holzinger
- Duong-Hung Pham
- Gang Yu
In Geophysics
Citations in the corpus
- What do we need to build explainable AI systems for the medical domain? (2017, background): “Finding the components s (cid:96) from the bidimensional signal s is called the decomposition problem (Clausel et al., 2015).”
- Theoretical analysis of the second-order synchrosqueezing transform (2016, methodology): “First, an extension to the bidimensional case was proposed in [5], while a generalization of the wavelet approach by means of wavelet packets decomposition for both one dimensional and bidimensional cases is available in [26, 25].”