2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges

Abstract

Image quality is important not only for the viewing experience, but also for the performance of image processing algorithms. Image quality assessment (IQA) has been a topic of intense research in the fields of image processing and computer vision. In this paper, we first analyze the factors that affect two-dimensional (2D) and three-dimensional (3D) image quality, and then provide an up-to-date overview on IQA for each main factor. The main factors that affect 2D image quality are fidelity and aesthetics. Another main factor that affects stereoscopic 3D image quality is visual comfort. We also describe the IQA databases and give the experimental results on representative IQA metrics. Finally, we discuss the challenges for IQA, including the influence of different factors on each other, the performance of IQA metrics in real applications, and the combination of quality assessment, restoration, and enhancement.