| Paper Details: | Downloads: 2083 |
| Serial Number: | P1151751597
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| Title: | An efficientArtifact Free Denoising Technique for MR Images relying onTotal Variation Thresholding in Wavelet Domain
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| Authors: | Dr. Yousef Hasan F. Jbara and Dr. S. Hyder Ali
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| Corresponding Author: |
Dr. Hyder Ali Segu Mohamed
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| Abstract: | The process of removing different noises in magnetic resonance images is an important and challenging issue in clinical practices for the diagnosis using medical imaging. Various medical image restoration techniques using denoising algorithms with the help of wavelet transform are emerging out to a very abundant range in recent years. It has been apparent that different methods were deployed to perform a threshold operation on the wavelet coefficient of noise corrupted medical image, which restore the precise image as the original one. However, the primary demerit of wavelet denoising is pseudo-Gibb’s phenomenon, while reconstructing the smoothened medical image. The Total Variation method is very useful for the recovery of blocky, possibly discontinuous images, from a noisy background. Our approach optimized the threshold value of the wavelet decomposed image by TV minimization and then denoised by soft or hard thresholding. The TV method eliminates Gibb’s phenomena and thus restores sharp discontinuities. In this algorithm, we perform the TV minimization technique on the wavelet threshold coefficient before thresholding. The proposed method increases the SNR by more than 32 dB without distorting the image, whereas standard wavelet denoising methods improve the SNR by less than 20 dB and with some distortion. In addition, its computation time is more than six times faster.
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| Keywords: | Wavelets, Total Variation, Denoising, Magnetic Resonance Images, Medical Images
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| Journal/Conference: | International Journal of Graphics, Vision and Image Processing
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| Volume: | 18
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| Issue: | 1
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| Submission Date: | 12/16/2017 12:00:00 AM
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| Review Date: | 1/22/2018 12:00:00 AM
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| Publishing Date: | 2/13/2018 12:00:00 AM
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| Article Downloads: | 2083
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