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.


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    Title :

    Signal Denoising Using Simplified SURE-Based Linear Expansion of Thresholds in the Wavelet Domain


    Contributors:
    Guo, Qiang (author) / Yu, Songnian (author) / Leng, Ming (author) / Liu, Wei (author)


    Publication date :

    2008-05-01


    Size :

    254206 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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