Multiridge detection and time-frequency reconstruction

The ridges of the wavelet transform, the Gabor transform, or any time-frequency representation of a signal contain crucial information on the characteristics of the signal. Indeed, they mark the regions of the time-frequency plane where the signal concentrates most of its energy. We introduce a new...

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Bibliographic Details
Published in:IEEE transactions on signal processing 1999-02, Vol.47 (2), p.480-492
Main Authors: Carmona, R.A., Hwang, W.L., Torresani, B.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Chirp
Detection algorithms
Exact sciences and technology
Information, signal and communications theory
Mathematical methods
Monte Carlo methods
Noise robustness
Reconstruction
Reconstruction algorithms
Representations
Ridges
Robust stability
Skeleton
Speech enhancement
Telecommunications and information theory
Time frequency analysis
Transforms
Wavelet transforms
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Summary:The ridges of the wavelet transform, the Gabor transform, or any time-frequency representation of a signal contain crucial information on the characteristics of the signal. Indeed, they mark the regions of the time-frequency plane where the signal concentrates most of its energy. We introduce a new algorithm to detect and identify these ridges. The procedure is based on an original form of Markov chain Monte Carlo algorithm especially adapted to the present situation. We show that this detection algorithm is especially useful for noisy signals with multiridge transforms. It is a common practice among practitioners to reconstruct a signal from the skeleton of a transform of the signal (i.e., the restriction of the transform to the ridges). After reviewing several known procedures, we introduce a new reconstruction algorithm, and we illustrate its efficiency on speech signals and its robustness and stability on chirps perturbed by synthetic noise at different SNRs.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.740131