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Research Journal of Pharmacy and Technology
Year : 2016, Volume : 9, Issue : 7
First page : ( 919) Last page : ( 924)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2016.00176.1

Noise Reduction in MR brain image via various transform domain schemes

Goyal Bhawna1,*, Agrawal Sunil1, Sohi B.S.2, Dogra Ayush1

1Department of Electronics and Communications, UIET, Panjab University, Chandigarh

2Vice Chancellor, Chandigarh University, Chandigarh

*Corresponding Author E-mail: bhawnagoyal28@gmail.com

Online published on 15 October, 2016.


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.



Curvelet, Shearlet, Tetrolet, Magnetic Resonance image, Denoising, thresholding.


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