With the development of multimedia technology, Augmented Reality (AR) has become a promising next-generation mobile platform. The primary value of AR is to promote the fusion of digital contents and real-world environments, however, studies on how this fusion will influence the Quality of Experience (QoE) of these two components are lacking. To achieve better QoE of AR, whose two layers are influenced by each other, it is important to evaluate its perceptual quality first. In this paper, we consider AR technology as the superimposition of virtual scenes and real scenes, and introduce visual confusion as its basic theory. A more general problem is first proposed, which is evaluating the perceptual quality of superimposed images, i.e., confusing image quality assessment. A ConFusing Image Quality Assessment (CFIQA) database is established, which includes 600 reference images and 300 distorted images generated by mixing reference images in pairs. Then a subjective quality perception study and an objective model evaluation experiment are conducted towards attaining a better understanding of how humans perceive the confusing images. An objective metric termed CFIQA is also proposed to better evaluate the confusing image quality. Moreover, an extended ARIQA study is further conducted based on the CFIQA study. We establish an ARIQA database to better simulate the real AR application scenarios, which contains 20 AR reference images, 20 background (BG) reference images, and 560 distorted images generated from AR and BG references, as well as the correspondingly collected subjective quality ratings. We also design three types of full-reference (FR) IQA metrics to study whether we should consider the visual confusion when designing corresponding IQA algorithms. An ARIQA metric is finally proposed for better evaluating the perceptual quality of AR images.
翻译:随着多媒体技术的发展, " 增强现实 " (AR)已经成为一个令人振奋的下一代移动平台。AR的主要价值是促进数字内容和真实世界环境的融合,然而,缺乏关于这种融合将如何影响这两个组成部分的经验质量的研究。为了实现更好的AR QoE(其两层相互影响),必须首先评价其感知质量。在本文件中,我们认为AR技术是虚拟场景和真实场景的叠加,并引入视觉混淆作为其基本理论。首先提出一个更普遍的问题,即评价超传图像的感知质量,即令人困惑的图像质量评估。建立了一个图像质量评估数据库,其中包括600个参考图像和300个通过将参考图像混合成对立而生成的扭曲图像。随后,我们进行了主观质量对应研究和客观评估实验,以更好地了解人类对混乱图像的感知度。一个称为 CFIQA 的客观背景参考,也是用来评估超传图像质量的更好评估,我们为AR AL AL Q (我们为AR IMA 进行真实的AR Q ),我们为AR 做了一个更精确的图像质量研究。