Signal denoising using neighbouring dual-tree complex wavelet coefficients PROJECT TITLE :Signal denoising using neighbouring dual-tree complex wavelet coefficientsABSTRACT: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. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Bridging gap between multi-dimensional scalingbased and optimum network localisation via efficient refinement Image denoising by random walk with restart kernel and non-subsampled contourlet transform
