2 November 1999 Denoising using time-frequency and image processing methods
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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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Douglas J. Nelson, Douglas J. Nelson, Gabriel Cristobal, Gabriel Cristobal, Vitaly Kober, Vitaly Kober, Fehret Cakrak, Fehret Cakrak, Patrick J. Loughlin, Patrick J. Loughlin, Leon Cohen, Leon Cohen, "Denoising using time-frequency and image processing methods", Proc. SPIE 3807, Advanced Signal Processing Algorithms, Architectures, and Implementations IX, (2 November 1999); doi: 10.1117/12.367673; https://doi.org/10.1117/12.367673


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