Estimation of power spectral density using wavelet thresholding

Authors:
Petr Sysel;Jiri Misurec
Affiliations:
Brno University of Technology, Department of Telecommunications, Brno, Czech Republic;Brno University of Technology, Department of Telecommunications, Brno, Czech Republic
Venue:
CSECS'08 Proceedings of the 7th conference on Circuits, systems, electronics, control and signal processing
Year:
2008

Citing 2
Cited 0

Digital signal processing (3rd ed.): principles, algorithms, and applications

Digital signal processing (3rd ed.): principles, algorithms, and applications
Single-channel noise suppression by wavelets in spectral domain

COST 2102'07 Proceedings of the 2007 COST action 2102 international conference on Verbal and nonverbal communication behaviours

Quantified Score

Hi-index	0.00

Visualization

Abstract

The basic problem of the single-channel speech enhancement methods lies in a rapid and precise method for estimating noise, on which the quality of enhancement method depends. The paper describes a new method of power spectral density estimation using wavelet transform in spectral domain. To reduce periodogram variance the proposed method use the procedure of thresholding the wavelet coefficients of a periodogram. Then the smoothed estimate of power spectral density of noise is obtained using the inverse discrete wavelet transform.