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Reseach Article

A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms

by K. S. Tamilselvan, G. Murugesan, M. Vinothsaravanan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 21
Year of Publication: 2013
Authors: K. S. Tamilselvan, G. Murugesan, M. Vinothsaravanan
10.5120/13040-0053

K. S. Tamilselvan, G. Murugesan, M. Vinothsaravanan . A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms. International Journal of Computer Applications. 74, 21 ( July 2013), 6-11. DOI=10.5120/13040-0053

@article{ 10.5120/13040-0053,
author = { K. S. Tamilselvan, G. Murugesan, M. Vinothsaravanan },
title = { A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 21 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number21/13040-0053/ },
doi = { 10.5120/13040-0053 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:43:04.587272+05:30
%A K. S. Tamilselvan
%A G. Murugesan
%A M. Vinothsaravanan
%T A Histogram based Hybrid Approach for Medical Image Denoising using Wavelet and Curvelet Transforms
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 21
%P 6-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical images are analyzed for the diagnosis of various diseases like cancer, tumor and fracture etc. . . But, they are susceptible to different types of noises called as Gaussian noise, Speckle noise, Uniform noise, Impulse noise, etc. . . Therefore it is an important task to remove the noise from medical images especially in MRI,CT, PET,SPECT, Digital Mammogram and Ultrasound images. Selection of appropriate filter is a tough task. In this paper, we propose a technique that uses Wavelet Transform and Curvelet Transform for denoising the medical images based on the Histogram equalization.

References
  1. Ashok Saini, "Reduction of Noise from Enhanced Image Using Wavelets",International Journal of Electronics Engineering, 3 (2), 2011, pp. 275– 277,"
  2. Sandeep Kumar, Puneet Verma, "Comparison of Different Enhanced Image Denoising with Multiple Histogram Techniques", International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-2, May 2012.
  3. S. Satheesh, Dr. KVSVR Prasad,"Medical Image Denoising using Adaptive Threshold based on Contourlet Transform", Advanced Computing: An International Journal ( ACIJ ), Vol. 2, No. 2, March 2011
  4. J. Fowler, "The redundant discrete wavelet transform and additive noise," IEEE Signal Processing Letters, vol. 12, no. 9, pp. 629–632,2005
  5. L. Parthiban and R. Subramanian, "MRI image denoising for telemedicine," 8th Int. Conf. on e-Health Networking,Applications and Services 2006 (HEALTHCOM 2006), pp. 188- 191, 17-19 Aug. 2006.
  6. M. Abdullah-Al-Wadud, Md. Hasanul Kabir, M. Ali Akber Dewan, and Oksam Chae, "A dynamic histogram equalization for image contrast enhancement", IEEE Transactions. Consumer Electron. , vol. 53, no. 2, pp. 593- 600, May 2007
  7. Sudha, G. R. Suresh, and R. Sukanesh , "Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance", International Journal of Computer Theory and Engineering, Vol. 1, No. 1, April 2009, 1793-8201
  8. Pei-yan FEI Bao-long GUO," Image Denoising based on the Dyadic Wavelet Transform," Proceedings of the Fifth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'03) 0-7695-1957-1/03 2003 IEEE
  9. Eric I. Balster and Yuan E Zheng, "Fast, Feature-Based Wavelet Shrinkage Algorithm for Image Denoising", KIMAS 2003. October 1-3,2003,B oston. MA,USA Copyright 0-7803-7958-6/03/$17. 0B0 2003 IEEE
  10. Jianwei Ma and Gerlind Plonka, "The Curvelet Transform-A review of recent applications",IEEE Signal Processing Magazine
  11. March 2010
  12. E. J. CANDÈS and L. DEMANET, "Curvelets and Fourier integral operators", C. R. Math. Acad. Sci. Paris 336 (2003), 395–398
Index Terms

Computer Science
Information Sciences

Keywords

Medical images Speckle noise Impulse noise MRI CT PET SPECT Digital Mammogram Ultrasound images Wavelet Transform Curvelet Transform and Histogram equalization