Author(s): Bhawna Goyal, Sunil Agrawal, B.S. Sohi, Ayush Dogra

Email(s): bhawnagoyal28@gmail.com

DOI: 10.5958/0974-360X.2016.00176.1   

Address: Bhawna Goyal1*, Sunil Agrawal1, B.S. Sohi2, Ayush Dogra1
1Department of Electronics and Communications, UIET, Panjab University, Chandigarh
2Vice Chancellor, Chandigarh University, Chandigarh
*Corresponding Author

Published In:   Volume - 9,      Issue - 7,     Year - 2016


ABSTRACT:
Despite the phenomenal progress in the field of image denoising it continues to be an active area of research and still holds margin in improving the standard of the denoising techniques. Image denoising has emerged as a significant tool in medical imaging specifically. In this article we have compared and evaluated three transform domain techniques on an MRI test image subjectively and objectively. The performance of Curvelet, Shearlet, and Tetrolet transform with a selective thresholding is evaluated. Shearlet is able to yield the best quality of image denoising. The study aims at analysing the performance of transform domain methods on MRI image at low and high levels of noise.


Cite this article:
Bhawna Goyal, Sunil Agrawal, B.S. Sohi, Ayush Dogra. Noise Reduction in MR brain image via various transform domain schemes. Research J. Pharm. and Tech. 2016; 9(7):919-924. doi: 10.5958/0974-360X.2016.00176.1


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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