Signal denoising based on wavelet transform using a multi-level threshold function
Mohammad Ashouri Golroudbari · 2013
Wavelet threshold denoising is a powerful method for suppressing noise in signals and images. For this purpose, various threshold functions, e.g. Hard-threshold and Soft-threshold, have been introduced. To overcome the shortcomings of hard and soft threshold functions, a new multi-level threshold function is presented in this paper. This threshold function can be applied adaptively to noisy data, and therefore better performance is provided in the wavelet domain. By using this method, more compatible threshold functions are obtained, which has many advantages over soft and hard threshold functions. The results of MATLAB simulations show that the denoising effect of this method is better than the other conventional threshold functions. Numerical results also show that the new threshold function is more effective and gives better SNR gains.