CFP last date
20 January 2025
Reseach Article

Robust Noise Filtering in Image Sequences

by Soumaya Hichri, Faouzi Benzarti, Hamid Amiri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 18
Year of Publication: 2012
Authors: Soumaya Hichri, Faouzi Benzarti, Hamid Amiri
10.5120/7871-1156

Soumaya Hichri, Faouzi Benzarti, Hamid Amiri . Robust Noise Filtering in Image Sequences. International Journal of Computer Applications. 50, 18 ( July 2012), 18-23. DOI=10.5120/7871-1156

@article{ 10.5120/7871-1156,
author = { Soumaya Hichri, Faouzi Benzarti, Hamid Amiri },
title = { Robust Noise Filtering in Image Sequences },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 18 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 18-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number18/7871-1156/ },
doi = { 10.5120/7871-1156 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:48:38.131175+05:30
%A Soumaya Hichri
%A Faouzi Benzarti
%A Hamid Amiri
%T Robust Noise Filtering in Image Sequences
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 18
%P 18-23
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image sequences filtering have recently become a very important technical problem especially with the advent of new technology in multimedia and video systems applications. Often image sequences are corrupted by some amount of noise introduced by the image sensor and therefore inherently present in the imaging process. The main problem in the image sequences is how to deal with spatio-temporal and non stationary signals. In this paper, we propose a robust method for noise removal of image sequence based on coupled spatial and temporal anisotropic diffusion. The idea is to achieve an adaptive smoothing in both spatial and temporal directions, by solving a nonlinear diffusion equation. This allows removing noise while preserving all spatial and temporal discontinuities.

References
  1. Perona, P. and Malik, J. 1999. Scale space and edge detection using anisotropic diffusion. IEEE transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 7, pp. 629-639.
  2. Alvarez, L. , Lions, P. L. , and Morel, J. M. 1992 Image selective smoothing and edge detection by non linear diffusion. SIAM Journal on Numerical Analysis, vol. 29, no. 3, pp. 845-866.
  3. Bourdon, P. , Augereau, B. , Olivier, C. , and chatellier, C. 2002. Colour image sequence denoising using coupled spatial and temporal anisotropic diffusions. IRCOM-SIC, UMR-CNRS 6615, University of Poitiers.
  4. Dekeyser, F. 2001. Restauration de séquences d'images par des approches spatio- temporelles : filtrage et super résolution par le mouvement. University of Rennes1.
  5. Dubois, E. , and Sabri, S. 1984. Noise reduction in image sequences using motion compensated temporal filtering. IEEE transactions on communications, vol . 32, no. 7, pp. 826-831.
  6. Kornprobst, P. , Deriche R. , and Aubert, G. Image sequence restoration: A pde based coupled method for image restoration and motion segmentation. In Proceedings of the 5th European Conference on Computer Vision, Hans Burkhardt and Bernd Neumann, Eds. , Freiburg, Germany, June 1998, vol. II of Lecture Notes in Computer Science, pp. 548–562, Springer-Verlag.
  7. Koederink, J. J. 1984. The structure of images. Biologcal Cybernetics, vol. 50, pp. 363-370.
  8. Benzarti, F. , and Amiri, H. 2012. Blind Photographic Images Restoration with Discontinuities Preservation. International Journal of Computer Information Systems and Industrial Management Applications (IJCISIM) Volume 4 pp. 609-619.
  9. Deriche, R. , and Faugeras, O. 1996. Les EDP en Traitement des Images et Vision par Ordinateur. Traitement du signal, vol. 13, no. 6.
  10. Hichri, S. , Benzarti, F. , and Hamrouni, K. 2010. Image sequence filtering using coupled anisotropic diffusion, 6th, International Conference on Electrical Systems and Automatic Control, Hammamet, Tunisia.
  11. Manzanera, A. , and Richefeu, J. 2004. A robust and computationally efficient motion detection algorithm based on Sigma/delta background estimation. In ICVGIP, Kolkata, India.
  12. Schreier, R. , and Temes, G. C. 2005. Delta Sigma Data Converters. Wiley, Piscataway, New Jersey.
Index Terms

Computer Science
Information Sciences

Keywords

Image sequence PDE Anisotropic Diffusion Spatio-temporal filtering Motion Detection