An improved method of audio denoising based on wavelet transform

The recovery of original signals from the communication channel without any noise is a difficult task. Many denoising techniques have been proposed for the removal of noises from a digital signal. Wavelet denoising using threshold algorithm is a powerful method for suppressing noise in digital signals. In this paper, an audio denoising technique based on double-density dual-tree discrete wavelet transform (DDDTWT) using a level dependent threshold algorithm is implemented. Audio signal contaminated with Additive White Gaussian Noise is chosen for the implementation. The results in terms of signal to noise ratio (SNR) and root mean square error (RMSE) are compared with the values of dual-tree discrete wavelet transform (DTDWT) and double-density discrete wavelet transform (DDDWT) methods and also with global thresholding method. The results of MATLAB simulations show that the proposed method is more effective and gives better performance for denoising audio signals in terms of both SNR and RMSE.