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An Analytical Approach to the Image Reconstruction Problem Using EM Algorithm

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Artificial Intelligence and Soft Computing (ICAISC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7267))

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Abstract

In this paper an analytical iterative approach to the problem of image reconstruction from parallel projections is presented. The reconstruction process is performed using Expectation Minimization algorithm. Experimental results show that the appropriately designed reconstruction procedure is able to reconstruct an image with better quality than obtained using the traditional convolution/ back-projection algorithm.

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Author information

Authors and Affiliations

  1. Departament of Computer Engineering, Technical University of Czestochowa, Armii Krajowej 36, 42-200, Czestochowa, Poland

    Piotr Dobosz

Authors
  1. Piotr Dobosz
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Computer Science Division, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2012 Springer-Verlag Berlin Heidelberg

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Dobosz, P. (2012). An Analytical Approach to the Image Reconstruction Problem Using EM Algorithm. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_57

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  • DOI: https://doi.org/10.1007/978-3-642-29347-4_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29346-7

  • Online ISBN: 978-3-642-29347-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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