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Article Information:
An Image Denoising Framework with Multi-resolution Bilateral Filtering and Normal Shrink Approach
Shivani Sharma and Gursharanjeet Singh Kalra
Corresponding Author: Shivani Sharma
Submitted: March 29, 2013
Accepted: April 22, 2013
Published: February 15, 2014 |
Abstract:
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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.
Key words: Bilateral filter, MBF, MSE, NormalShrink, PSNR, wavelet thresholding,
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Cite this Reference:
Shivani Sharma and Gursharanjeet Singh Kalra, . An Image Denoising Framework with Multi-resolution Bilateral Filtering and Normal Shrink Approach. Research Journal of Applied Sciences, Engineering and Technology, (6): 1240-1246.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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