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Original scientific paper

Selecting Low-level Features for Image Quality Assessment by Statistical Methods

Atidel Lahouhou ; University Paris 13
Emmanuel Viennet
Azeddine Beghdadi ; University Paris 13

Full text: english pdf 476 Kb


page 183-189

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Image quality assessment is an
important component in every image processing
system where the last link of the chain is the
human observer. This domain is of increasing
interest, in particular in the context of image
compression where coding scheme optimization
is based on the distortion measure. Many
objective image quality measures have been
proposed in the literature and validated by
comparing them to the Mean Opinion Score
(MOS). We propose in this paper an empirical
study of several indicators and show how one
can improve the performances by combining
them. We learn a regularized regression model
and apply variable selection techniques to
automatically find the most relevant indicators.
Our technique enhances the state of the art
results on two publicly available databases.


Image quality assessment; perceptual

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