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