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International Conference Image Analysis and Recognition

ICIAR 2014: Image Analysis and Recognition pp 55–64Cite as

Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions \(S_k(\mathbf{x} ,\mathbf{y})\)

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8814))

Abstract

We examine the use of individual components of the Structural Similarity image quality measure as criteria for best approximation in terms of orthogonal expansions. We also introduce a family of higher order SSIM-like rational functions.

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References

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, Faculty of Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada

    Paul Bendevis & Edward R. Vrscay

Authors
  1. Paul Bendevis
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  2. Edward R. Vrscay
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Corresponding author

Correspondence to Edward R. Vrscay .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    Aurélio Campilho

  2. Dept. of Electrical and Computer Eng., University of Waterloo, Waterloo, Ontario, Canada

    Mohamed Kamel

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© 2014 Springer International Publishing Switzerland

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Bendevis, P., Vrscay, E.R. (2014). Structural Similarity-Based Approximation over Orthogonal Bases: Investigating the Use of Individual Component Functions \(S_k(\mathbf{x} ,\mathbf{y})\) . In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8814. Springer, Cham. https://doi.org/10.1007/978-3-319-11758-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-11758-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11757-7

  • Online ISBN: 978-3-319-11758-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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