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Proceedings Paper

Denoising using time-frequency and image processing methods
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Paper Abstract

We present a number of methods that use image and signal processing techniques for removal of noise from a signal. The basic idea is to first construct a time-frequency density of the noisy signal. The time-frequency density, which is a function of two variables, can then be treated as an 'image,' thereby enabling use of image processing methods to remove noise and enhance the image. Having obtained an enhanced time-frequency density, one then reconstructs the signal. Various time frequency-densities are used and also a number of image processing methods are investigated. Examples of human speech and whale sounds are given. In addition, new methods are presented for estimation of signal parameters from the time- frequency density.

Paper Details

Date Published: 2 November 1999
PDF: 18 pages
Proc. SPIE 3807, Advanced Signal Processing Algorithms, Architectures, and Implementations IX, (2 November 1999); doi: 10.1117/12.367673
Show Author Affiliations
Douglas J. Nelson, U.S. Department of Defense (United States)
Gabriel Cristobal, Instituto de Optica/CSIC (Spain)
Vitaly Kober, Instituto de Optica/CSIC (United States)
Fehret Cakrak, Univ. of Pittsburgh (United States)
Patrick J. Loughlin, Univ. of Pittsburgh (United States)
Leon Cohen, CUNY/Hunter College (United States)


Published in SPIE Proceedings Vol. 3807:
Advanced Signal Processing Algorithms, Architectures, and Implementations IX
Franklin T. Luk, Editor(s)

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