Signal denoising using neighbouring dual-tree complex wavelet coefficients

Denoising is a very important preprocessing step in signal/image processing. In this study, a new signal denoising algorithm is proposed by using neighbouring wavelet coefficients. The dual-tree complex wavelet transform is employed because of its property of approximate shift invariance, which is very important in signal denoising. Both translation-invariant (TI) and non-TI versions of the denoising algorithm are considered. Experimental results show that the proposed method outperforms other existing methods in the literature for denoising both artificial and real-life noisy signals.