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Statistical Analysis of Image Quality Metrics for Watermark Transparency Assessment

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6297))

Abstract

In this paper, we propose a new statistical approach to investigate the performance of some objective quality metrics used in the literature in order to determine the most suitable quality metric for watermark transparency evaluation. To this end, we have defined a new procedure based on the ANOVA (ANalysis Of VAriance) tests and the subjective performance evaluation. Firstly, a set of selected quality metrics is statistically analyzed by means of ANOVA technique to identify the specific metric that provides the best discrimination to watermarking artifacts. So, the obtained results will answer the question: “which metrics are sensitive to watermarking artifacts?” Secondly, subjective tests were performed and some correlation measures between MOS (Mean Opinion Score) and each quality metric are computed. It is clear that the best quality metric is the one that provides the best consistency with subjective experiments. Results from both objective and subjective investigations were discussed to give some concluding remarks. All conclusions drawn in the paper are supported by extensive experiments in terms of used quality metrics, watermarking algorithms and image database.

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Nguyen, P.B., Luong, M., Beghdadi, A. (2010). Statistical Analysis of Image Quality Metrics for Watermark Transparency Assessment. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_63

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  • DOI: https://doi.org/10.1007/978-3-642-15702-8_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15701-1

  • Online ISBN: 978-3-642-15702-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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