Signal de-noising using the wavelet transform and regularization

Abstract

This paper presents a new signal de-noising algorithm using wavelets. We have developed a filtering scheme in the wavelet domain, that involves selective smoothing at each scale of the time-frequency plot. The amount of smoothing is controlled by regularizing factors, and gradient-based switches are used to avoid distortion of signal features. The algorithm is seen to compare favorably to that of Mallat et al. (1992), as it is able to recover both the smooth portions as well as Brownian texture in the input, from the noisy signal.