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This paper focuses on the inuence of ambient light on the perceived quality of videos displayed on Liquid Crystal Display (LCD) with local backlight dimming. A subjective test assessing the quality of videos with two backlight dimming methods and three lighting conditions, i.e. no light, low light level (5 lux) and higher light level (60 lux) was organized to collect subjective data. Results show that participants prefer the method exploiting local dimming possibilities to the conventional full backlight but that this preference varies depending on the ambient light level. The clear preference for one method at the low light conditions decreases at the high ambient light, conrming that the ambient light signicantly attenuates the perception of the leakage defect (light leaking through dark pixels). Results are also highly dependent on the content of the sequence, which can modulate the eect of the ambient light from having an important inuence on the quality grades to no inuence at all.

Local backlight dimming is a technology aiming at both saving energy and improving visual quality on television sets. As the rendition of the image is specified locally, the numerical signal corresponding to the displayed image needs to be computed through a model of the display. This simulated signal can then be used as input to objective quality metrics. The focus of this paper is on determining which characteristics of locally backlit displays influence quality assessment. A subjective experiment assessing the quality of highly contrasted videos displayed with various local backlight-dimming algorithms is set up. Subjective results are then compared with both objective measures and objective quality metrics using different display models. The first analysis indicates that the most significant objective features are temporal variations, power consumption (probably representing leakage), and a contrast measure. The second analysis shows that modeling of leakage is necessary for objective quality assessment of sequences displayed with local backlight dimming.

This paper investigates the impact of ambient light and peak white (maximum brightness of a display) on the perceived quality of videos displayed using local backlight dimming. Two subjective tests providing quality evaluations are presented and analyzed. The analyses of variance show significant interactions of the factors peak white and ambient light with the perceived quality. Therefore, we proceed to predict the subjective quality grades with objective measures. The rendering of the frames on liquid crystal displays with light emitting diodes backlight at various ambient light and peak white levels is computed using a model of the display. Widely used objective quality metrics are applied based on the rendering models of the videos to predict the subjective evaluations. As these predictions are not satisfying, three machine learning methods are applied: partial least square regression, elastic net, and support vector regression. The elastic net method obtains the best prediction accuracy with a spearman rank order correlation coefficient of 0.71, and two features are identified as having a major influence on the visual quality.

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