论文标题
全向图像的感知质量评估
Perceptual Quality Assessment of Omnidirectional Images
论文作者
论文摘要
全向图像和视频可以在虚拟现实(VR)环境中提供现实世界中的沉浸式体验。我们在本文中提出了一项感知的全向图像质量评估(IQA)研究,因为在VR环境下提供良好的经验非常重要。我们首先建立一个全向IQA(OIQA)数据库,其中包括16个源图像和320个失真的图像,这些图像被4种常见的失真类型降解,即JPEG压缩,JPEG2000压缩,高斯的模糊和高斯噪声。然后,在VR环境中的OIQA数据库上进行了主观质量评估研究。考虑到人类只能在VR环境中的一个运动中看到场景的一部分,因此视觉关注变得极为重要。因此,我们还在质量评级实验期间跟踪头部和眼动数据。原始和扭曲的全向图像,主观质量评级以及头部和眼动数据构成了OIQA数据库。在OIQA数据库上测试了最先进的全参考(FR)IQA措施,并进行了一些与传统IQA不同的新观察结果。
Omnidirectional images and videos can provide immersive experience of real-world scenes in Virtual Reality (VR) environment. We present a perceptual omnidirectional image quality assessment (IQA) study in this paper since it is extremely important to provide a good quality of experience under the VR environment. We first establish an omnidirectional IQA (OIQA) database, which includes 16 source images and 320 distorted images degraded by 4 commonly encountered distortion types, namely JPEG compression, JPEG2000 compression, Gaussian blur and Gaussian noise. Then a subjective quality evaluation study is conducted on the OIQA database in the VR environment. Considering that humans can only see a part of the scene at one movement in the VR environment, visual attention becomes extremely important. Thus we also track head and eye movement data during the quality rating experiments. The original and distorted omnidirectional images, subjective quality ratings, and the head and eye movement data together constitute the OIQA database. State-of-the-art full-reference (FR) IQA measures are tested on the OIQA database, and some new observations different from traditional IQA are made.