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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
  1. Lee, J. S. (1980) "Digital Image Enhancement and Noise Filtering by use of Local Statistics", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-2, No. 2, pp. 165-168.
  2. Frost, V. S. , Stiles, J. A. , Shanmugan, K. S. and Holtzman, J. C. (1982) "A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-4, No. 2, pp. 157–165.
  3. Windyga, P. S. (2001) "Fast Impulsive Noise Removal", IEEE Transactions on Image Processing, Vol. 10. No. 1, pp. 173-178.
  4. Yu, Y. and Action, S. T. (2002) "Speckle Reducing Anisotropic Diffusion", IEEE Transactions on Image Processing, Vol. 11, No. 11, pp. 1260- 1270.
  5. Starck, J. L. , Candes, E. J. and Donoho, D. L. (2002) "The Curvelet Transform for Image Denoising", IEEE Transactions on Image Processing, Vol. 11, No. 6, pp. 670-684.
  6. Do, M. N and Vetterli, M. (2003) "The Finite Ridgelet Transform for Image Representation", IEEE Transactions on Image Processing, Vol. 12, No. 1.
  7. Deans, S. R. (1983) "The Radon Transform and Some of its applications", John Wiley Sons, New York.
  8. Xu, Y. B. , Xie, C. S. and Zheng, C. Y. (2007) "An Application of the á Trous Algorithm in Detecting Infrared Targets," IEEE Conference on Wavelet Analysis and Pattern Recognition, Beijing, China, pp. 1015-1019.
  9. Elad, M. and Aharon, M. (2006) "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries", IEEE Transactions on Image Processing, Vol. 15, No. 12, pp. 3736-3745.
  10. Joshi, K. R. and Kamathe, R. S. (2008) "SDI: New Metric for Quantification of Speckle Noise in Ultrasound Imaging" IEEE, pp. 122-126.
  11. Hongqiao, L. , Shengqian, W. (2009) "A New Image Denoising Method Using Wavelet Transform", IEEE International Forum on Information Technology and Applications, pp. 111-114.
  12. Rayudu, D. K. V. , Murala, S. and Kumar, V. (2010) "Denoising of Ultrasound Images using Curvelet Transform", The 2nd International Conference on Computer and Automation Engineering (ICCAE 2010), Singapore, Vol. 3, pp. 447–451.
  13. Qiao, Y. L. Song, C. Y. and Zhao, C. H. (2010) "M-band Ridgelet Transform Based Texture Classification," Pattern Recognition Letters, Vol. 31, pp. 244–249.
  14. Gonde, A. B. , Maheshwari, R. P. and Balasubramanian, R. (2011) "Multiscale Ridgelet Transform for Content Based Image Retrieval," IEEE 2nd International Advance Computing Conference (IACC 2010), Thapar University, Patiala, India, pp. 139–144.
  15. Murala, S. , Maheshwari, R. P. and Balasubramanian, R. (2011)"Directional Binary Wavelet Patterns for Biomedical Image Indexing and Retrieval", Springer Science.
  16. Li, S. , Fang, L. and Yin, H. (2012)"An Efficient Dictionary Learning Algorithm and Its Application to 3-D Medical Image Denoising", IEEE Transactions on Biomedical Engineering, Vol. 59, No. 2, pp. 417-427.
  17. A. Lopes, R. Touzi, and E. Nezry,(1990) "Adaptive speckle filters and scene heterogeneity," IEEE Transactions Geoscience Remote Sensing, Vol. 28, pp. 992–1000.
Index Terms

Computer Science
Information Sciences

Keywords

Speckle noise Wavelet Curvelet Ridgelet.

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