De-Noising with Spline Wavelets and SWT

De-Noising with Spline Wavelets and SWT
Authors : Tilak T. N. , Krishnakumar. S
Publication Date: 01-12-2015


Author(s):  Tilak T. N. , Krishnakumar. S

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Volume. 4 - Issue. 12 , December - 2015

e-ISSN:   2278-0181

 DOI:  http://dx.doi.org/10.17577/IJERTV4IS120026


This paper explores the difference in performance of spline wavelets of the bi-orthogonal type in de-noising images corrupted by Additive White Gaussian Noise. The dependence of the peak signal-to-noise ratio and the mean squared error on the filter characteristics of the wavelets, when stationary wavelet transform is used in the de-noising process, is investigated. It is found that the de-noising action augments with use of wavelet of lower effective length for its high pass reconstruction filter. For wavelets with equal effective lengths for their high pass reconstruction filters, a relation similar to the above, exists for the high pass decomposition filters. ‘Bior1.1’ (bi-orthogonal spline wavelet 1.1) is found to be the most suitable wavelet in the family, for de-noising. ‘Bior 3.1’ is found to be an odd member in the family and is not at all suitable for de-noising, the reason for which is traced to the lack of smoothness of its decomposition scaling function.


Number of Citations for this article:  Data not Available


Key Word(s):    


Number of Downloads:     174

Call for Papers - May - 2017



                 Call for Thesis - 2017 

     Publish your Ph.D/Master's Thesis Online

              Publish Ph.D Master Thesis Online as Book