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A Differential-Geometrical Framework for Color Image Quality Measures

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Advances in Visual Computing (ISVC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6455))

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Abstract

We propose a differential-geometrical framework for color Image Quality Measures (IQMs). Our approach is based on the definition of a relevant image distortion measure in a Riemannian way. To do this, we use the concept of geodesic distance and apply the theoretical setting to exhibit closed-forms for all the differential geometric attributes of two well-know color spaces: Helmholtz and Stiles manifolds. With these formulæ, we generalize some useful IQMs from the Euclidean framework to the Riemannian one. Finally, we present some experiments performed on real images, gradually distorted by different kinds of noise to conclude that the Riemannian IQMs are meaningful and relevant.

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Author information

Authors and Affiliations

  1. Ecole Supérieure Privée d’Ingénierie et de Technologies, LAMSIN-ENIT, Tunis Al Manar University, Tunisia

    Mourad Zéraï

  2. Ecole Supérieure Privée d’Ingénierie et de Technologies GRIFT, ENSI, Manouba University, Tunisia

    Olfa Triki

Authors
  1. Mourad Zéraï
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  2. Olfa Triki
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, 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. The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Ronald Chung

  6. Dyna Vox Systems, Pittsburgh, PA, USA

    Riad Hammound

  7. King Saud University, Riyadh, Saudi Arabia

    Muhammad Hussain

  8. Hewlett Packard Labs, Paolo Alto, CA, USA

    Tan Kar-Han

  9. The Ohio State University, Columbus, OH, USA

    Roger Crawfis

  10. Virtual Reality Lab, EPFL, Lausanne, Switzerland

    Daniel Thalmann

  11. NASA Ames Research Center, Clifton Park, NY, USA

    David Kao

  12. Kitware, Clifton Park, NY, USA

    Lisa Avila

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Zéraï, M., Triki, O. (2010). A Differential-Geometrical Framework for Color Image Quality Measures. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17277-9_56

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  • DOI: https://doi.org/10.1007/978-3-642-17277-9_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17276-2

  • Online ISBN: 978-3-642-17277-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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