The monogenic signal
By Michael Felsberg, G. Sommer. IEEE Transactions on Signal Processing, 2001
921 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Molecular Biology, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/2b6f69314806cefe583f77b3d27bc1dd92828376
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Michael Rubinstein
- Frédo Durand
- E. Barriga
- Kai Krajsek
- William T. Freeman
- Víctor Murray
- Steve Guyot
- Valérie Perrier
In Molecular Biology
- N. Petkov
- Giuseppe Papari
- Thomas Mulvaney
- J. Beton
- Michael Rubinstein
- Frédo Durand
- E. Barriga
- Kai Krajsek
In Statistical and Nonlinear Physics
- Michael Rubinstein
- Frédo Durand
- E. Barriga
- Kai Krajsek
- William T. Freeman
- Víctor Murray
- Steve Guyot
- Valérie Perrier
Citations in the corpus
- Image Processing: The Fundamentals: Petrou/Image Processing: The Fundamentals (2010, background): “Good sources on phase congruency are [39] and [46], while the monogenic signal was introduced in [18].”
- Texture analysis based on local analysis of the Bidimensional Empirical Mode Decomposition (2005, methodology): “The combination of an image with its Riesz Transform forms a 2D-generalization of the analytic signal, the monogenic signal [21], where the Riesz Transform replaces the Hilbert Transform.”
- Integrating model simulation tools and cryo‐electron microscopy (2022, background): “28,29 DeepRes is based on deep learning from filtered atomic models at different frequencies.”
- The Monogenic Synchrosqueezed Wavelet Transform: A tool for the Decomposition/Demodulation of AM-FM images (2012, methodology): “In [9] and [25], it is proved that the monogenic signal can be written as Mf = A eθ = A (cosφ+ nθ sinφ) with nθ = cos θ i + sin θ j , where A is a positive real valued function and φ and θ are two real valued functions defined in a unique way (under suitable assumptions).”
- Automated Vessel Segmentation Using Infinite Perimeter Active Contour Model with Hybrid Region Information with Application to Retinal Images (2015, methodology): “There are numerous quadrature filters that might be used [35], but here we will stay with the optimized log-norm filter with a view to optimal performance in both the spatial and frequency domains [36].”
- Riesz pyramids for fast phase-based video magnification (2014, methodology): “This processing is done entirely in the spatial domain, which gives an easy way of avoiding the spatial wraparound artifacts present in the frequency domain implementation of the eight-orientation complex steerable pyramid used by Wadhwa et al. [19].”
- Recent multiscale AM-FM methods in emerging applications in medical imaging (2012, methodology): “Other related work on image demodulation based on the Riesz transform extension has been reported by Mellor, Noble, Hahn, Felsberg, Sommer and collaborators in [48,52-57].”
- A Unified Theory for Steerable and Quadrature Filters (2006, methodology): “The Riesz transformation has been shown to be a rotational invariant generalization of the Hilbert transformation generalizing the analytic signal to the monogenic signal (Felsberg and Sommer, 2001).”
- Edge and line oriented contour detection: State of the art (2011, background): “More recently, an elegant generalization of the analytic signal has been proposed in [109], called the monogenic signal, which is based on the observation that vector functions can be both isotropic and antisymmetric.”
- Transforms and Operators for Directional Bioimage Analysis: A Survey. (2016, background): “The relation between the Riesz transform and steerable filters is studied in (Felsberg and Sommer 2001).”
- Computer Methods and Programs in Biomedicine (neutral): “In [97,108] the monogenic signal [191] is used to estimate the image motion vector field and track the temporal displacement of vessels in endoscopic images.”