Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric

Benjamin Bringier 1 Ludovic Quintard 1 Mohamed-Chaker Larabi 1
1 SIC
XLIM - XLIM, Université de Poitiers
Abstract : This paper deals with image quality assessment that is capturing the focus of several research teams from academic and industrial parts. This field has an important role in various applications related to image from acquisition to projection. Numbers of objective image quality metrics have been developed during the last decade. These metrics are more or less correlated to end-user feedback and can be separated in three categories: 1) Full Reference (FR) trying to evaluate the impairment in comparison to the reference image, 2) Reduced Reference (RR) using some features extracted from an image to represent it and compare it with the distorted one and 3) No Reference (NR) measures known distortions such as blockiness, blurriness,\ldots without the use of a reference. Unfortunately, the quality assessment community have not achieved to a universal image quality model and only empirical models established on psychophysical experimentation are generally used. In this paper, we focus only on the third category to evaluate the quality of CRT (Cathode Ray Tube) and LCD (Liquid Crystal Display) color reproduction where a blind metric, based on modeling a part of the human visual system behavior. The objective results are validated by single-media and cross-media subjective tests. This allows to study the ability of simulating displays on a reference one.
Type de document :
Article dans une revue
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Computer Vision Center Press, 2008, 7 (3), pp.23-35
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https://hal.archives-ouvertes.fr/hal-00476580
Contributeur : Benjamin Bringier <>
Soumis le : lundi 26 avril 2010 - 17:34:43
Dernière modification le : lundi 13 octobre 2014 - 15:43:25

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  • HAL Id : hal-00476580, version 1

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Benjamin Bringier, Ludovic Quintard, Mohamed-Chaker Larabi. Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric. ELCVIA Electronic Letters on Computer Vision and Image Analysis, Computer Vision Center Press, 2008, 7 (3), pp.23-35. 〈hal-00476580〉

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