Abstract
A fuzzy logic filter to remove mixed Gaussian and impulsive noise from CT medical images is presented. The method performs a weighted average operation where a fuzzy rule-based model is defined to compute the coefficients. In addition, a parallel filter based on this method is presented. Implementation of the parallel algorithm on multi-core platform using OpenMP is presented. Efficiency is measured in terms of execution time and in terms of PSNR over medical CT images. Experimental results show that mixed Gaussian-impulsive noise is reduced efficiently and image details are preserved. The multi-core implementation allows reducing mixed Gaussian-impulse noise in real-time.
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Acknowledgment
This research was supported by the Spanish Ministry of Science, Innovation and Universities (Grant RTI2018-098156-B-C54) co-financed by FEDER funds.
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Arnal, J., Pérez, J.B., Vidal, V. (2020). A Parallel Fuzzy Method to Reduce Mixed Gaussian-Impulsive Noise in CT Medical Images. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1074. Springer, Cham. https://doi.org/10.1007/978-3-030-32456-8_104
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DOI: https://doi.org/10.1007/978-3-030-32456-8_104
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