CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

A New Nonlinear Anisotropic Wiener Method for Speckle Noise Reduction in Optical Coherence Tomography

by Ahmed H. Samak
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 12
Year of Publication: 2013
Authors: Ahmed H. Samak
10.5120/10975-6116

Ahmed H. Samak . A New Nonlinear Anisotropic Wiener Method for Speckle Noise Reduction in Optical Coherence Tomography. International Journal of Computer Applications. 65, 12 ( March 2013), 10-15. DOI=10.5120/10975-6116

@article{ 10.5120/10975-6116,
author = { Ahmed H. Samak },
title = { A New Nonlinear Anisotropic Wiener Method for Speckle Noise Reduction in Optical Coherence Tomography },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 12 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 10-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number12/10975-6116/ },
doi = { 10.5120/10975-6116 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:21:03.711877+05:30
%A Ahmed H. Samak
%T A New Nonlinear Anisotropic Wiener Method for Speckle Noise Reduction in Optical Coherence Tomography
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 12
%P 10-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Removing noise from the original medical image is still a challenging research in image processing. This paper presents a new method for speckle noise reduction in Optical coherence Tomography (OCT). Stationary wavelet transform (SWT) is employed to provide effective representation of the noisy coefficients. Nonlinear Anisotropic filtering of the Details coefficients improves the denoising efficiency and effectively preserves the edge features while wiener filter improves to denoising approximate coefficients. The performance of the proposed method is compared with Nonlinear Anisotropic filter, Wiener filter, Lee filter and Frost filter and analyzed based on the peak signal-to-noise ratio (PSNR).

References
  1. W. Drexler. Ultrahigh-resolution optical coherence tomography. J. Biomed. Opt. , Volume 9(1) Pages 47- 74, January 2004.
  2. D. C. Adler, T. H. Ko, and J. G. Fujimoto. Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter. Optics Letters, Volume 29(24) Pages 2878- 2880, 2004.
  3. J. M. Schmitt, S. H. Xiang, and K. M. Yung. Speckle in optical coherence tomography. Journal of Biomedical Optics, Volume 4(1) Pages 95-105, 1999.
  4. D. C. Adler, T. H. Ko, and J. G. Fujimoto. Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter. Optics Letters, Volume 29(24) Pages 2878- 2880, 2004.
  5. Y. H. Lu, , S. Y. Tan, T. S. Yeo, W. E. Ng, I. Lim, and C. B. Zhang. Adaptive filtering algorithms for sar speckle reduction. In Proc. IEEE 1996 International Geoscience and Remote Sensing Symposium, pages 67- 69, New York, USA, May 1996.
  6. D. C. Fernandez and H. M. Salinas. Evaluation of a nonlinear diffusion process for segmentation and quantification of lesions in optical coherence tomography images. In Proc. Society Of Photo Optical Engineers. 5747, pages 1834-1843,San Jose, CA, 2005.
  7. D. C. Fernandez, H. M. Salinas, and C. A. Puliafito. Automated detection of retinal layer structures on optical coherence tomography images. Opt. Express, Volume 13 Pages 10200- 10216, 2005.
  8. Bo Chong, Yong-Kai Zhu, Speckle reduction in optical coherence tomography images of human finger skin by wavelet modified BM3D filter. Original Research Article Optics Communications, Volume 291, 15, Pages 461-469 March 2013.
  9. Mashaly, A. S. ; AbdElkawy, E. E. F. ; Mahmoud, T. A. ," Speckle noise reduction in SAR images using adaptive morphological filter ", 10th Conference International on Intelligent Systems Design and Applications (ISDA), 2010
  10. Starck J-L, Fadili J, Murtagh F. The undecimated wavelet decomposition and its reconstruction. IEEE Trans Imag Process; Volume 16(2), Pages 297–309,2007
  11. Gonzalez RC. Digital image processing. 2nd ed. Upper Saddle River, NJ: Pearson Education; 2004.
  12. Nason GP, Silverman BW. The stationary wavelet transform and some statistical applications, Tech. rep. Bristol, UK: Department of Mathematics. University of Bristol; 1995.
  13. P. Perona, J. Malik, Scale space and edge detection using anisotropic diffusion, IEEE Trans. Pattern Anal. Mach. Intell. Volume 12 Pages 629–639. 1990
  14. Yoshikazu Washizawa, Yukihiko Yamashita, Non-linear Wiener filter in reproducing kernel Hilbert space, in: Proceedings of the 18th International Conference on Pattern Recognition, ICPR'06
  15. V. Frost, J. Stiles, K. Shanmugan, and J. Holtzman, "A model for radar images and its application to adaptive digital filtering and multiplicative noise," IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume . 4, Pages . 157-166, Mar. 1982.
Index Terms

Computer Science
Information Sciences

Keywords

image denoising wavelet transform Optical coherence Tomography Nonlinear Anisotropic filter

Powered by PhDFocusTM