A Particle Swarm Optimizer Applied to Soft Morphological Filters for Periodic Noise Reduction

Authors:
T. Y. Ji;Z. Lu;Q. H. Wu
Affiliations:
Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, U.K.;Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, U.K.;Department of Electrical Engineering and Electronics, The University of Liverpool, Liverpool, L69 3GJ, U.K.
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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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.