Signal Denoising Using Simplified SURE-Based Linear Expansion of Thresholds in the Wavelet Domain
Qiang Guo, Songnian Yu, Ming Leng, Wei Liu · 2008
The purpose of signal denoising is to reduce the noise level, while preserving the signal features. Various denoising approaches exist, in which wavelet-based pointwise thresholding approaches are extensively adopted in many application fields. For signal denoising based on wavelet thresholding, there are two crucial aspects, namely, the use of a proper thresholding function and the estimate of the noise standard deviation. Both greatly influence the quality of the denoised signal. In this paper, a simple wavelet-based denoising approach is proposed, which uses the modified linear expansion of thresholds based on Stein’ s unbiased risk estimate (SURE) and the noise standard deviation’s estimation depending on the number of vanishing moments of the wavelet transform. Experimental results demonstrate that higher signal-to-noise ratio (SNR) can be obtained by this new approach as compared to other thresholding approaches.