Evaluation of wavelet-based methods for denoising ultrasonic echo signals

Ultrasound images are severely affected by noise present in ultrasonic signals. There are several methods for noise reduction in ultrasonic signals, among them wavelet denoising is a powerful tool for removing noise from signals. The overall denoising performance of a wavelet denoising procedure depends on several processing parameters, including the type of wavelet, thresholding method, and threshold selection rules. Two thresholding procedures, VisuShrink and BayesShrink, and threshold selection rules are discussed in this paper using the discrete wavelet transform and decomposition level dependent thresholds.