Abstract
The removal of periodic noise is an important problem in image processing. To avoid using the time-consuming methods that require Fourier transform, a simple and efficient spatial filter based on soft mathematical morphology (MM) is proposed in this paper. The soft morphological filter (Soft MF) is optimized by an improved particle swarm optimizer with passive congregation (PSOPC) subject to the least mean square error criterion. The performance of this new filter and its comparison with other commonly used filters are also analyzed, which shows that it is more effective in reducing both periodic and non-periodic noise meanwhile preserving the details of the original image.
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References
Quintana, M.I., Poli, R., Claridge, E.: Morphological algorithm design for binary images using genetic programming. Genetic Programming and Evolvable Machines 7(1), 81–102 (2006)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, vol. IV, pp. 1942–1948. IEEE Press, Piscataway, NJ (1995)
He, S., Wu, Q.H., Wen, J.Y., Saunders, J.R., Paton, R.C.: A particle swarm optimizer with passive congregation. Biosystems 78, 135–147 (2004)
Gasteratos, A., Andreadis, I., Tsalides, P.: Fuzzy soft mathematical morphology. Vision, Image Signal Processing, IEE Proceedings 145(1), 41–49 (1988)
Hamid, M., Harvey, N., Marshall, S.: Genetic algorithm optimisation of multidimensional grey-scale soft morphological filters with applications in archive film restoration. Circuits and Systems for Video Technology, IEEE Transactions 13(5), 406–416 (2003)
Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39–43. Kluwer Academic Publishers, Nagoya, Japan (1995)
Clerc, M., Kennedy, J.: The particle swarm - explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation 6(1), 58–73 (2002)
Parrish, J.K., Hamner, W.M.: Animal groups in three dimensions. Cambridge University Press, Cambridge, UK (1997)
Aizenberg, I., Butakoff, C.: Frequency domain median-like filter fo periodic and quasi-periodic noise removal. In: SPIE Proceedings of Image Processing: Algorithms and Systems, pp. 181–191 (2002)
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Ji, T.Y., Lu, Z., Wu, Q.H. (2007). A Particle Swarm Optimizer Applied to Soft Morphological Filters for Periodic Noise Reduction. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_40
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DOI: https://doi.org/10.1007/978-3-540-71805-5_40
Publisher Name: Springer, Berlin, Heidelberg
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