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Colour Image Quality Assessment Using Structural Similarity Index and Singular Value Decomposition

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Computer Vision and Graphics (ICCVG 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5337))

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Abstract

In the paper the analysis of the influence of the colour space on the results obtained during image quality assessment using the Structural Similarity index and the Singular Value Decomposition approach has been investigated. Obtained results have been compared to the ones achieved by widely used Normalised Colour Difference (NCD) metric. All the calculations have been performed using the LIVE Image Quality Assessment Database in order to compare the correlation of achieved results with the Differential Mean Opinion Score (DMOS) values obtained from the LIVE database. As a good solution for the further research, also with the use of some other image quality metrics, the application of the HSV colour space is proposed instead of commonly used YUV/YIQ luminance channel or the average of the RGB channels.

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Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering Chair of Signal Processing and Multimedia Engineering, Szczecin University of Technology, 26. Kwietnia 10, 71-126, Szczecin, Poland

    Krzysztof Okarma

Authors
  1. Krzysztof Okarma
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Editor information

Editors and Affiliations

  1. Polish-Japanese Institute of Information Technology, 86 Koszykowa St, 02-008, Warsaw, Poland

    Leonard Bolc

  2. Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Księcia Trojdena 4, 02-109, Warsaw, Poland

    Juliusz L. Kulikowski

  3. Polish-Japanese Institute of Information Technology, The Silesian University of Technology, Institute of Computer Science, 86 Koszykowa St, 02-008, Warsaw, Poland

    Konrad Wojciechowski

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Okarma, K. (2009). Colour Image Quality Assessment Using Structural Similarity Index and Singular Value Decomposition. In: Bolc, L., Kulikowski, J.L., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2008. Lecture Notes in Computer Science, vol 5337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02345-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-02345-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02344-6

  • Online ISBN: 978-3-642-02345-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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