A NOVEL APPROACH FOR NOISE REDUCTION IN THE GABOR TIME-FREQUENCY DOMAIN
Behnaz Pourebrahimi, Jan C. A. van der Lubbe
2009
Abstract
In this paper, a noise reduction technique is introduced based on the Gabor time-frequency transform. In the proposed approach, noise is removed using low pass filters locally in the transform domain. Finding the cut-off frequency for the low pass filters in such a way that image does not loose its features, is an important issue. The optimal cut-off frequency of the low pass filters are computed in an iterative method for each sub-block of the image. The followed approach, besides showing a good performance in removing noise, it also performs well in preserving image features.
References
- Barthel, K. U., Cycon, H. L., and Marpe, D. (2003). Image denoising using fractal and wavelet-based methods. In SPIE Proc, pages 10-18.
- Buades, A., Coll, B., and Morel, J. M. (2004). On image denoising methods. Technical report, Technical Note, CMLA (Centre de Mathematiques et de Leurs Applications.
- Cristobal, G., Chagoyen, M., Escalante-Ramirez, B., and Lopez-Miranda, J. (1996). Wavelet-based denoising methods. a comparative study with applications in microscopy. In SPIE Proc. Wavelet Applications in Signal and Image Processing IV, volume 2825, pages 660-671.
- Daugman, J. G. (1985). Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters. J. Opt. Soc. Am. A, 2(7):1160.
- Daugman, J. G. (1988). Complete discrete 2-d gabor transforms by nearal networks for image analysis and compression. IEEE Trans. Acoustics, Speech and Signal Proc., 36(7):1169-1179.
- Gabor, D. (1946). Theory of communication. 93:429-457.
- Srinivasan, V., Bhatia, P., and Ong, S. H. (1993). A fast implementation of the discrete 2-d gabor transform. Signal Process., 31(2):229-233.
- Teuner, A. and Hosticka, B. J. (1993). Adaptive gabor transformation for image processing. IEEE Transactions on Image Processing, 2(1):112-117.
- Wang, Z., Qu, C., and Cui, L. (2006). Denoising images using wiener filter in directionalet domain. In CIMCA 7806: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce, page 228, Washington, DC, USA. IEEE Computer Society.
Paper Citation
in Harvard Style
Pourebrahimi B. and C. A. van der Lubbe J. (2009). A NOVEL APPROACH FOR NOISE REDUCTION IN THE GABOR TIME-FREQUENCY DOMAIN . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 22-27. DOI: 10.5220/0001768000220027
in Bibtex Style
@conference{visapp09,
author={Behnaz Pourebrahimi and Jan C. A. van der Lubbe},
title={A NOVEL APPROACH FOR NOISE REDUCTION IN THE GABOR TIME-FREQUENCY DOMAIN},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={22-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001768000220027},
isbn={978-989-8111-69-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - A NOVEL APPROACH FOR NOISE REDUCTION IN THE GABOR TIME-FREQUENCY DOMAIN
SN - 978-989-8111-69-2
AU - Pourebrahimi B.
AU - C. A. van der Lubbe J.
PY - 2009
SP - 22
EP - 27
DO - 10.5220/0001768000220027