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M-Band Ridgelet Transform to Remove Speckle Noise from Medical Images

by Ramanjyot Kaur, Palvinder Singh Maan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 9
Year of Publication: 2014
Authors: Ramanjyot Kaur, Palvinder Singh Maan
10.5120/14866-2958

Ramanjyot Kaur, Palvinder Singh Maan . M-Band Ridgelet Transform to Remove Speckle Noise from Medical Images. International Journal of Computer Applications. 85, 9 ( January 2014), 1-5. DOI=10.5120/14866-2958

@article{ 10.5120/14866-2958,
author = { Ramanjyot Kaur, Palvinder Singh Maan },
title = { M-Band Ridgelet Transform to Remove Speckle Noise from Medical Images },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 9 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number9/14866-2958/ },
doi = { 10.5120/14866-2958 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:59.766016+05:30
%A Ramanjyot Kaur
%A Palvinder Singh Maan
%T M-Band Ridgelet Transform to Remove Speckle Noise from Medical Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 9
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes an improved image denoising algorithm based on M-Band Ridgelet Transform for speckle noise present in the medical images. NeighCoeff Thresholding algorithm is used to calculate the threshold values. The result of the improved method is tested on ultrasound and Magnetic Resonance Imaging (MRI) images affected with speckle noise. Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Edge Preservation Index (EPI) has been used as parameters for evaluation of results. The performance of new method is compared with existing methods such as Wavelets, Ridgelet, and Curvelet.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speckle noise Wavelet Curvelet Ridgelet.

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