Estimation of Different Thersholding Techniques for Signal Denoising

Shruti Bhargava; Abhishek Choubey

In almost every area of science and technology, signals must be processed to facilitate the extraction of information. Thus, the development of signal processing techniques and systems is of great importance. These techniques usually take the form of a transformation of a signal into another signal that is in some sense more desirable than the original. In this paper, when we decompose a data set using wavelet, we use filters that act as averaging filters & others that produce details. Some of resulting wavelet wavelet coefficients corresponds to detail in data set. If details are small, they might be omitted without substantially affecting the main features of data set. Then thresholding is used to set to zero all coefficients that are less than particular threshold. These coefficients are used in an inverse wavelet transformation to reconstruct data set. Hence with the help of WT the noise is removed from the signal

Select Volume / Issues:

• Volume 8,Issue 3, May 2017

Year:

2017

Type of Publication:

Article

Keywords:

DT; SNR; PSNR; ST; HT

Journal:

IJECCE

Volume:

8

Number:

3

Pages:

153-155

Month:

May

ISSN:

2249-071X