对背光调光液晶显示器上的彩色图像和视频质量进行建模

J. Korhonen, Claire Mantel, Nino Burini, Søren Forchhammer
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引用次数: 6

摘要

客观图像和视频质量指标主要关注信号的数字表示。然而,显示特性对于整体体验质量(QoE)也是必不可少的。在本文中,我们使用了液晶显示器(LCD)的背光调光系统模型,并展示了如何将建模图像用作质量评估算法的输入。对于质量评估,我们提出了一种基于CIE L*a*b*色彩空间中峰值信噪比(PSNR)计算的图像质量度量。该度量考虑了产生的图像中的亮度降低、颜色失真和均匀性损失。对使用不同背光调光算法和裁剪策略生成的图像的主观评价表明,所提出的度量比传统的PSNR更准确地估计感知图像质量。
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Modeling the color image and video quality on liquid crystal displays with backlight dimming
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, we propose an image quality metric, based on Peak Signal-to-Noise Ratio (PSNR) computation in the CIE L*a*b* color space. The metric takes luminance reduction, color distortion and loss of uniformity in the resulting image in consideration. Subjective evaluations of images generated using different backlight dimming algorithms and clipping strategies show that the proposed metric estimates the perceived image quality more accurately than conventional PSNR.
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