HDR-VDP-2 a calibrated visual metric for visibility and quality predictions in all luminance conditions
HDR-VDP-2 a calibrated visual metric for visibility and quality predictions in all luminance conditions
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HDR-VDP-2 一种经过校准的视觉指标，用于在所有亮度条件下进行可见性和质量预测
DOI：
10.1145/2010324.1964935
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发表时间：
2011
影响因子：
6.2
通讯作者：
Mantiuk R
中科院分区：
文献类型：
--
作者：
Mantiuk R
视觉指标可以在评估新的照明，渲染和成像算法中发挥重要作用。不幸的是，目前的度量仅适用于窄的强度范围，并且与这些范围之外的实验数据不相关。为了解决这些问题，我们提出了一个视觉指标预测可见性（歧视）和质量（平均意见分数）。该指标是基于一个新的视觉模型的所有亮度条件下，这已经从新的对比敏感度测量。该模型的校准和验证几个对比度判别数据集，和图像质量数据库（LIVE和TID 2008）。与原始HDR-VDP和VDP度量相比，可见性度量被示出为提供大大改进的预测，特别是对于低亮度条件。图像质量预测与MS-SSIM相当或更好，MS-SSIM被认为是最成功的质量指标之一。建议的度量标准的代码可在线获得。
Visual metrics can play an important role in the evaluation of novel lighting, rendering, and imaging algorithms. Unfortunately, current metrics only work well for narrow intensity ranges, and do not correlate well with experimental data outside these ranges. To address these issues, we propose a visual metric for predicting visibility (discrimination) and quality (mean-opinion-score). The metric is based on a new visual model for all luminance conditions, which has been derived from new contrast sensitivity measurements. The model is calibrated and validated against several contrast discrimination data sets, and image quality databases (LIVE and TID2008). The visibility metric is shown to provide much improved predictions as compared to the original HDR-VDP and VDP metrics, especially for low luminance conditions. The image quality predictions are comparable to or better than for the MS-SSIM, which is considered one of the most successful quality metrics. The code of the proposed metric is available on-line.