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A Comparative Analysis of Thresholding Techniques for Denoising of MRI Image Using Wavelets


Affiliations
1 Electronics and Telecomm. Engg. Chhatrapati Shivaji Institute of Technology, Shivaji Nagar, Balod Road, Durg - 491001,Chhattisgarh, India
2 Department of Electronics and Telecommunication, SSEC, Bhilai, (C.G), 490020, India
     

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The image de-noising naturally corrupted by noise is a classical problem in the field of signal or image processing. Additive random noise can easily be removed using simple threshold methods. Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using Discrete Wavelet Transform (DWT).Numerical results show that the algorithm can obtained higher peak signal to noise ratio (PSNR) through wavelet based denoising algorithm for MR images corrupted with random noise.

Index Terms- Image Processing, Denoising, DWT, MRI, Thresholding, Random Noise. PSNR, MSE And MAE.


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  • A Comparative Analysis of Thresholding Techniques for Denoising of MRI Image Using Wavelets

Abstract Views: 286  |  PDF Views: 1

Authors

Shashikant Agrawal
Electronics and Telecomm. Engg. Chhatrapati Shivaji Institute of Technology, Shivaji Nagar, Balod Road, Durg - 491001,Chhattisgarh, India
Yogesh Bahendwar
Department of Electronics and Telecommunication, SSEC, Bhilai, (C.G), 490020, India

Abstract


The image de-noising naturally corrupted by noise is a classical problem in the field of signal or image processing. Additive random noise can easily be removed using simple threshold methods. Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using Discrete Wavelet Transform (DWT).Numerical results show that the algorithm can obtained higher peak signal to noise ratio (PSNR) through wavelet based denoising algorithm for MR images corrupted with random noise.

Index Terms- Image Processing, Denoising, DWT, MRI, Thresholding, Random Noise. PSNR, MSE And MAE.