CFP last date
20 May 2024
Reseach Article

Image Restoration using a Combinational Trivaritate Shrinkage Filter and PSO

by Prabhjot Kaur, Sukhwinder Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 16
Year of Publication: 2014
Authors: Prabhjot Kaur, Sukhwinder Kaur
10.5120/15072-3508

Prabhjot Kaur, Sukhwinder Kaur . Image Restoration using a Combinational Trivaritate Shrinkage Filter and PSO. International Journal of Computer Applications. 86, 16 ( January 2014), 26-28. DOI=10.5120/15072-3508

@article{ 10.5120/15072-3508,
author = { Prabhjot Kaur, Sukhwinder Kaur },
title = { Image Restoration using a Combinational Trivaritate Shrinkage Filter and PSO },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 16 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number16/15072-3508/ },
doi = { 10.5120/15072-3508 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:24.321634+05:30
%A Prabhjot Kaur
%A Sukhwinder Kaur
%T Image Restoration using a Combinational Trivaritate Shrinkage Filter and PSO
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 16
%P 26-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image restoration in digital image processing is a technique through which corrupted images are modified to increase the quality of the image. A lot of research work has been done in this contrast to make the image quality efficient enough. When the noise level in the image is low , it is easy to rectify the image using general filter but the procedure is not effective enough when the noise in the image is high. To rectify highly noised images we need combinational filter which divides the images into section and perform the threshold operation according to the sections divided. In this paper, we propose a unique methodology to perform image restoration using a combinational trivaraiate shrinkage filter &PSO within the wavelet domain for 512*512 pixel size image.

References
  1. Raman Maini and Himanshu Aggarwal A Comprehensive Review of Image Restoration Techniques Journal Of Computing, Volume 2, Issue 3, March 2010, Issn 2151-9617 Https://Sites. Google. Com/Site/Journalofcomputing.
  2. Sumit A. . Raokhande Image Denoising Using Trivariate Shrinkage Filter In Wavelet Domain`International Journal of Emerging Technology and Advanced Engineering Website: www. ijetae. com (ISSN 2250-2459, Volume 2, Issue 3, March 2012)
  3. S. Mohamed Mansoor Roomi, P. L. Muthu Karuppi A Particle Swarm Optimization Based Edge Preserving Impulse Noise Filter Journal of Computer Science 6 (9): 1014-1020, 2010 ISSN 1549-3636 © 2010 Science Publications
  4. L. Sendur and I. W. Selesnick, "Bivariate shrinkage with local variance estimation," IEEE Signal Process. Lett, vol. 9, no. 12, pp. 438–441, Dec. 2002.
  5. J. Portilla, V. Strela, M. J. Wainwright, and E. P. Simoncelli, "Image denoising using scale mixtures of gaussians in the wavelet domain," IEEE Trans. Image Process. , vol. 12, no. 11, pp. 1338–1351, Nov. 2003.
  6. M. Elad and M. Aharon, "Image denoising via learned dictionaries and sparse representation," IEEE Comput. Vis. Pattern Recognit. , Jun. 2006.
  7. M. Elad and M. Aharon, "Image denoising via sparse and redundant representations over learned dictionaries," IEEE Trans. Image Process. , vol. 15, no. 12, pp. 3736–3745, Dec. 2006.
  8. C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," in Proc. Int. Conf. Computer Vision, 1998, pp. 839–846.
Index Terms

Computer Science
Information Sciences

Keywords

Noise Removal Trivariate Shrinkage Filter PSO Digital Image Processing