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Image File Compression Using Region Growing and Interpolation

  • Conference paper
Neural Nets (WIRN 2005, NAIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3931))

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Abstract

We propose an image file compression method using Region Growing and Interpolation. Firstly, using the techniques of Region Growing, we divide the image in blocks. The compression-decompression method is based on bivariate interpolation. Error estimates in terms of the modulus of continuity of the original image are obtained. Experimental results illustrate the performances of the proposed method.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Salerno, Italy

    Antonio Di Nola & Nicla Paladino

  2. Department of Mechanical and System Engineering, Budapest Tech, Népszinház u. 8, H-1081, Budapest, Hungary

    Barnabás Bede

Authors
  1. Antonio Di Nola
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  2. Nicla Paladino
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  3. Barnabás Bede
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Editor information

Editors and Affiliations

  1. Dipartimentimento di Scienze dell’Informazione, via Comelico 39/41, 20135, Milano, Italy

    Bruno Apolloni

  2. Dipartimento di Fisica “E.R. Caianiello”, Università degli Studi di Salerno, Via S. Allende, 84081, Baronissi (SA), Italy

    Maria Marinaro

  3. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Giuseppe Nicosia

  4. Department of Mathematics and Informatics, University of Salerno, Via Ponte Don Melillo, 84084, Fisciano (SA), Italy

    Roberto Tagliaferri

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© 2006 Springer-Verlag Berlin Heidelberg

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Di Nola, A., Paladino, N., Bede, B. (2006). Image File Compression Using Region Growing and Interpolation. In: Apolloni, B., Marinaro, M., Nicosia, G., Tagliaferri, R. (eds) Neural Nets. WIRN NAIS 2005 2005. Lecture Notes in Computer Science, vol 3931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731177_27

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  • DOI: https://doi.org/10.1007/11731177_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33183-4

  • Online ISBN: 978-3-540-33184-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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