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Discrete Tomography Reconstruction Based on the Multi-well Potential

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Combinatorial Image Analysis (IWCIA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6636))

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Abstract

In this paper we present a new discrete tomography reconstruction algorithm developed for reconstruction of images that consist of a small number of gray levels. The proposed algorithm, called DTMWP is based on the minimization of the objective function which combines the regularized squared projection error with the multi-well potential function. The minimization is done by a gradient based method. We present experimental results obtained by application of the proposed algorithm for reconstruction of images that consist from three gray levels using small number of projections.

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Author information

Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Serbia

    Tibor Lukić

Authors
  1. Tibor Lukić
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Texas, 1 University Station C0803, 78712-0240, Austin, TX, USA

    Jake K. Aggarwal

  2. Department of Computer and Information Science, State University of New York at Fredonia, 280 Central Ave., 14063, Fredonia, NY, USA

    Reneta P. Barneva

  3. Mathematics Department, SUNY Buffalo State College, 1300 Elmwood Ave., 14222, Buffalo, NY, USA

    Valentin E. Brimkov

  4. Esuela Politécnica Superior, Departamento de Ingenería Informática, Universidad Autónoma de Madrid, c/Tomas y Valiente, 11, 28049, Cantoblanco, Madrid, Spain

    Kostadin N. Koroutchev

  5. Departamento de Física Fundamental, Universidad Nacional de Educación a Distancia, c/ Senda del Rey 9, 28080, Madrid, Spain

    Elka R. Korutcheva

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© 2011 Springer-Verlag Berlin Heidelberg

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Lukić, T. (2011). Discrete Tomography Reconstruction Based on the Multi-well Potential. In: Aggarwal, J.K., Barneva, R.P., Brimkov, V.E., Koroutchev, K.N., Korutcheva, E.R. (eds) Combinatorial Image Analysis. IWCIA 2011. Lecture Notes in Computer Science, vol 6636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21073-0_30

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  • DOI: https://doi.org/10.1007/978-3-642-21073-0_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21072-3

  • Online ISBN: 978-3-642-21073-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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