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Color Image Compression by Riemannian B-Tree Triangular Coding

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Advances in Visual Computing (ISVC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8034))

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Abstract

We propose an enhancement of the B-Tree-Triangulation coding technique in a Riemannian framework . Our method focuses on the subdivision criteria in the triangulation process, and compares results obtained by means of two different metrics: the Euclidean and the Riemannian one. Comparison between input and compressed/decompressed images, in terms of a set of image quality measures, shows better performance of Riemannian triangulation in low intensity levels, while using Euclidean distance works better in high intensities. We therefore propose two combined decision cirtirea and compare image quality measures. Results show an enhancement of image quality at similar compression rates, and are promissing for further adjustments to specific applications.

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Author information

Authors and Affiliations

  1. GRIFT, ENSI, Manouba University, Tunisia

    Olfa Triki

  2. Ecole Supérieure Privée d’Ingénierie et de Technologies, Tunisia

    Olfa Triki & Mourad Zéraï

  3. LAMSIN-ENIT, Tunis Al Manar University, Tunisia

    Mourad Zéraï

Authors
  1. Olfa Triki
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  2. Mourad Zéraï
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Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Arizona State University, Tempe, AZ, USA

    Baoxin Li

  6. Mitsubishi Electric Research Laboratories, Cambridge, MA, USA

    Fatih Porikli

  7. University of California, Riverside, CA, USA

    Victor Zordan

  8. AT&T Research Labs, Florham Park, NJ, USA

    James Klosowski

  9. ZIRST, Saint-Ismier Cedex, France

    Sabine Coquillart

  10. Qualcomm Research, San Diego, CA, USA

    Xun Luo

  11. Oxford e-Research Centre, University of Oxford,, Oxford, UK

    Min Chen

  12. IBM, Hawthorne, NY, USA

    David Gotz

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© 2013 Springer-Verlag Berlin Heidelberg

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Triki, O., Zéraï, M. (2013). Color Image Compression by Riemannian B-Tree Triangular Coding. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2013. Lecture Notes in Computer Science, vol 8034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41939-3_56

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  • DOI: https://doi.org/10.1007/978-3-642-41939-3_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41938-6

  • Online ISBN: 978-3-642-41939-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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