缩小差距:考虑观看条件的视觉质量评估

Yucheng Zhu, Guangtao Zhai, Ke Gu, Zhaohui Che
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引用次数: 3

摘要

大多数现有的视觉质量评估算法都是在标准数据库上进行测试的,这些数据库是在受控的观看条件下创建的(例如显示设备、观看距离和照明)。这意味着所有重新编码的主观分数只对数据库中使用的特定设置有效。然而,随着移动设备的普及,实际的观看环境可能会随时发生显著变化。我们的日常经验是,在不同的设备上,在不同的观看距离和/或照明条件下,相同的图像看起来会有很大的不同。换句话说,在目前的质量评估研究中,眼睛和屏幕后面的视觉内容之间存在着差距。因此,在这项工作中,我们在不同的实际观看条件下进行主观质量评估。为了使研究具有可重复性,我们建立了一个原型系统来记录眼睛从屏幕上真正看到的东西,并构建了观看环境变化的图像数据库。该数据库将向公众开放。同时设计了一种专用的有效的环境评价算法。我们相信这项工作将有利于视觉质量评估的研究走向更多的实际应用。
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Closing the gap: Visual quality assessment considering viewing conditions
Most of existing visual quality assessment algorithms are tested on standard databases that are created in controlled viewing conditions (e.g. display device, viewing distance and lighting). This implies that all the recoded subjective scores are only valid for the specific settings used in the database. However, with the prevalence of mobile devices, the practical viewing environments can significantly vary from moment to moment. It is our daily experience that the same image can look drastically different on dissimilar devices under changed viewing distance and/or lighting conditions. In other words, a gap exists between the eyes and the visual contents behind the screen in current research of quality assessment. Therefore, in this work, we perform subjective quality evaluation with varied actual viewing conditions. To make the research reproducible, we build a prototype system to record what the eyes really see from the screen and construct the viewing environment-changed image database. The database will be made available to the public. Meanwhile we design a dedicated effective environment-assessing algorithm. We believe that this work will benefit the research of visual quality assessment towards more practical applications.
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