Abstract:Signals representation in dyadic wavelet domain is very redundant. Compared with wavelet series reconstruction, signals dyadic wavelet reconstruction dependency on the individual coefficients in transform domain will be decreased. Therefore, with the same error decision probability, the better reconstruction can be expected. Based on this idea, this paper extends the existing wavelet-based denoising approaches to the dyadic wavelet-based denoising. Numerical experiments show that the dyadic wavelet-based denoising can significantly improve the signal-to-noise rate (SNR).