Research Article | OPEN ACCESS
An Image Denoising Framework with Multi-resolution Bilateral Filtering and Normal Shrink Approach
Shivani Sharma and Gursharanjeet Singh Kalra
Lovely Professional University, Punjab, India
Research Journal of Applied Sciences, Engineering and Technology 2014 6:1240-1246
Received: March 29, 2013 | Accepted: April 22, 2013 | Published: February 15, 2014
Abstract
In this study, an image denoising algorithm is presented, which takes into account wavelet thresholding and bilateral filtering in transform domain. The proposed algorithm gives an extension of the bilateral filter i.e., multiresolution bilateral filter, in which bilateral filtering is applied to the approximation sub bands and normal shrink is used for thresholding the wavelet coefficients of the detail sub bands of an image decomposed using a wavelet filter bank up to 2-level of decomposition. The algorithm is tested against ultrasound image of gall bladder corrupted by different types of noise namely, gaussian, speckle, poisson and impulse. The result shows that with increase in decomposition levels the proposed method is effective in eliminating noise but gives overly smoothed image. The algorithm outperforms with speckle and poisson noise at 2- level decomposition in terms of PSNR.
Keywords:
Bilateral filter, MBF, MSE, NormalShrink, PSNR, wavelet thresholding,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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