Abstract
An adaptive hybrid filter combining a group of sigma vector median filters with different thresholds with a filter based on neuro-fuzzy system is proposed for color image processing. The first subunit of the proposed filter is six sigma vector median filters, their outputs are used as optimum initial points to input the second subunit constituted by a simple Sugeno-type neuro-fuzzy system, and then the optimized result is obtained from the output of the second subunit. The parameters of the neuro-fuzzy model are automatically tuned and fixed by a learning method based on genetic algorithm. The results have indicated that the design of the proposed hybrid filter has met the requirement of removing impulse noise and preserving details. The proposed filter performs better than other filters.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Plataniotis, K.N., Venetsanopoulos, A.N.: Color Image Processing and Applications. Springer, Heidelberg (2000)
Lukac, R., Smolka, B., Martin, K., Plataniotis, K.N., Venetsanopoulos, A.N.: Vector Filtering for Color Imaging. IEEE Signal Process. Mag. Spec. Issue on Color Image Processing 22, 74–86 (2005)
Zheng, J., Valavanis, K.P., Gauch, J.M.: Noise removal from color images. J. Intelligent and Robotic Syst. 7, 257–285 (1993)
Astola, J., Haavisto, P., Neuvo, Y.: Vector Median Filters. Proceeding of the IEEE 78, 678–689 (1990)
Lukac, R., Smolka, B., Plataniotis, K.N., Venetsanopulos, A.N.: Selection Weighted Vector Directional Filters. Comput. Vision Image Understand. Special Issue on Color for Image Indexing and Retrieval 94, 140–167 (2004)
Lucat, L., Siohan, P., Barba, D.: Adaptive and Global Optimization Methods for Weighted Vector Median Filters. Signal Process.: Image Commum. 17, 509–524 (2002)
Viero, T., Oistamo, K., Neuvo, Y.: Three-dimensional Median Related Filters for Color Image Sequence filtering. IEEE Trans. Circuits Syst. Video Technol. 4, 129–142 (1994)
Lee, J.S.: Digital Image Smoothing and The Sigma Filter. Computer Vision Graph. Image Process 24, 255–269 (1983)
Eng, H.L., Ma, K.K.: Noise Adaptive Soft-switching median filters. IEEE Trans. Image Process. 10, 242–251 (2001)
Russo, F.: Hybrid Neuro-fuzzy Filter for Impulse Noise Removal. Pattern Recognition 32, 1843–1855 (1999)
Yuksel, M.E.: A Median/ANFIS Filter for Efficient Restoration of Digital Images Corrupted by Impulse Noise. Int. J. Electron. Commum. 60, 628–637 (2006)
Lukac, R., Smolka, B., Plataniotis, K.N., Venetsanopulos, A.N.: Vector Sigma Filters for Noise Detection and Removal in Color Images. J. Vis. Commum. Image R. 17, 1–26 (2006)
Trahanias, P.E., Venetsanopoulos, A.N.: Vector Directional Filters: A New Class of Multichannel Image Processing Filters. IEEE Trans. Image Process. 2, 524–528 (1993)
Karakos, D.G., Trahanias, P.E.: Combining Vector Median and Vector Directional Filters: The Directional Distance Filters. In: IEEE ICIP Conf., pp. 171–174. IEEE Press, New York (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Guo, X., Guo, B., Hu, T., Yang, O. (2009). An Adaptive Hybrid Filtering for Removing Impulse Noise in Color Images. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_54
Download citation
DOI: https://doi.org/10.1007/978-3-642-01513-7_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
eBook Packages: Computer ScienceComputer Science (R0)