An Algorithm for Thresholding in the Context of Signal Denoising with Wavelets

The problem of estimating a signal corrupted by additive noise has been of interest to many researchers for practical as well as theoretical reasons. Wavelet based methods have become increasingly popular, due to a number of advantages over the linear methods. A simulation-based analysis of some thresholding functions in the context of denoising application of wavelet transform was investigated. A probability based function to compute the threshold parameter is described and implemented in the Matlab-Simulink simulation environment, by using an estimation of the probability density function of the wavelet coefficients. The obtained results are at the same quality level with other procedures currently used in denoising.