Regularized Total Variation Image Enhancement Using E.Coli Bacteria Foraging Algorithm: Application to Neutron Radiography Projections

نویسندگان

  • Slami SAADI
  • Abderrezak GUESSOUM
  • Maamar BETTAYEB
چکیده

This paper proposes a novel approach based on swarm intelligence and foraging behavior of Escherichia coli Bacteria in the human intestine for enhancing neutron radiography projections blurred during acquisition by the high neutron flux and noise contaminated due to Gamma radiations. This approach uses the total variation (TV) optimization to solve an ill-posed problem. We consider a regularization operator for smoothing task. In comparison with other efficient methods, the proposed Algorithm can be suitable for image enhancement and noise removal. Streszczenie. W artykule zaproponowano wykorzystaniu algorytmu rojowego bazującego na zachowaniu bakterii E.coli do poprawy jakości projekcji radiograficznej. W porównaniu z innymi algorytmami ta metoda charakteryzuje się dobrą możliwością poprawy jakości obrazu i usuwania szumu. (Poprawa jakości obrazu radiograficznego przy wykorzystaniu algorytmu bazującego na bakterii E.coli)

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تاریخ انتشار 2012