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Adaptive wavelet thresholding for time varying SNR signal denoising

The wavelet transform has become a powerful tool for signal analysis and is widely used in many applications, including signal detection and denoising. This paper deals with signal detection and denoising using wavelet transforms for a class of time varying signal-to-noise-ratio (SNR) signals in B-type ultrasonic echoes. A new threshold estimator is proposed in order to enhance the SNR in time varying signals. With the estimator used on real B-type ultrasonic echo data, the results show that the proposed estimator is superior to the existing threshold estimator in SNR enhancement.