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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...
This paper investigates what composes the quality of videos displayed on LCD with local backlight dimming. In a subjective experiment, participants assessed the level of nine attributes defined using the Qualitative Descriptive Analysis method. Results show that three attributes (Contrast, Change over time and Grain) vary significantly depending on the backlight dimming algorithm. Predicting global...
Objective image and video quality metrics focus mostly on the digital representation of the signal. However, the display characteristics are also essential for the overall Quality of Experience (QoE). In this paper, we use a model of a backlight dimming system for Liquid Crystal Display (LCD) and show how the modeled image can be used as an input to quality assessment algorithms. For quality assessment,...
This paper presents a subjective experiment collecting quality assessment of images displayed on a LCD with local backlight dimming using two methodologies: absolute category ratings and paired-comparison. Some well-known objective quality metrics are then applied to the stimuli and their respective performance are analyzed. The HDR-VDP metric seems to achieve good performance on every source image.
Local backlight dimming is one of the most promising techniques for reducing power consumption and improving contrast characteristics of liquid crystal displays (LCD). In practice, due to light diffusion and a smaller number of backlight sources than pixels, local backlight dimming must often trade-off between leakage of light in dark pixels and clipping of luminance in bright pixels. Only few studies...
In this work, we consider and propose two extensions to an optimization-based image dependent backlight dimming algorithm. The first extension introduces error weighting based on human perception of luminance, aiming to improve the perceived image quality; the second extension adds an adjustable term for power consumption to the cost function, allowing flexible power management. Experimental results...
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