Image Denoising using Bilateral Filter and Wavelet Thresholding

Authors(3) :-Sirisha B., K. Dhilli, E. Govinda

In this work a hybrid denoising algorithm which combines spatial domain bilateral filter and hybrid thresholding function in the wavelet domain is beingproposed. The wavelet transform is used to decompose the noisy image into its different subbands namely LL, LH, HL, and HH. A two stage spatial bilateral filter is applied. The first stage is applied on the noisy image before wavelet decomposition. This stage will be called a pre-processing stage. The second stage spatial bilateral filtering is applied on the low frequency subband of the decomposed noisy image namely subbands LL. This stage will tend to cancel or at least attenuate any residual low frequency noise components. The intermediate stage deal with high frequency noise components by thresholding detail subbands LH, HL, and HH using hybrid thresholding function. The performance of the proposed denoising algorithm will be superior to that of the conventional denoising approach which may be proved after experimental analysis.

Authors and Affiliations

Sirisha B.
Department ECE, Avanthi Institute of Engineering and Technology, Narsipatnam, Visakhapatanam, Andhra Pradesh, India
K. Dhilli
Department ECE, Avanthi Institute of Engineering and Technology, Narsipatnam, Visakhapatanam, Andhra Pradesh, India
E. Govinda

Bilateral Filter, Wavelet Thresholding, Image Denoising

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 48-54
Manuscript Number : CSEIT172115
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sirisha B., K. Dhilli, E. Govinda, "Image Denoising using Bilateral Filter and Wavelet Thresholding", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.48-54 , January-February.2017
URL : http://ijsrcseit.com/CSEIT172115

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