Signal Denoising with Soft Threshold by using Chui-Lian (CL) Multiwavelet
Bittu Kumar, R. Vidhya Lavanya · 2011
The wavelet transform is the efficient transform of the last decade. The scalar wavelet transform has been widely used in many applications like signal denoising, Image compression and in medical applications. For best performance in these applications, wavelet transforms require filters that combine a number of desirable properties such as compact support, regularity, orthogonality and symmetry. Due to many constraints in implementation scalar wavelets do not possess all the properties which are needed for better performance in denoising. This leads to the evolution of the new chapter of wavelet called ‘Multiwavelets’ which possess more than one scaling filters overcomes this problem. The research in this domain is just started in simulation level. The CL Multiwavelet is the most common Multiwavelet used in the area of signal processing applications. In this paper, CL Multiwavelet is used with soft thresholding by Universal threshold selection rule for denoising the real time signals. This approach is incorporated with time domain and frequency domain analysis. Results are measured objectively by Signal to Noise Ratio (SNR) and Minimum Mean Square Error (MMSE). Overall results indicate that the tested signals have good enhancement quality when compared with existing methods.