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Modeling the color image and video quality on liquid crystal displays with backlight dimming

机译:利用背光调光对液晶显示器上的彩色图像和视频质量进行建模

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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.
机译:客观的图像和视频质量指标主要集中在信号的数字表示上。但是,显示特性对于整体体验质量(QoE)也至关重要。在本文中,我们使用液晶显示器(LCD)的背光调光系统模型,并展示如何将建模的图像用作质量评估算法的输入。为了进行质量评估,我们基于CIE L * a * b *颜色空间中的峰值信噪比(PSNR)计算,提出了一种图像质量度量。该度量考虑了在所得图像中的亮度降低,颜色失真和均匀性损失。使用不同的背光调光算法和裁剪策略生成的图像的主观评估表明,与传统的PSNR相比,所提出的指标可更准确地估算感知的图像质量。

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