Denoising using time-frequency and image processing methods
Douglas J. Nelson, Gabriel Cristóbal, Vitaly Kober, Fehret Cakrak, Patrick J. Loughlin, Leon W. Cohen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1999
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.