2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges
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 aff...
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doaj-055b626190b34be397c32a4ce8eddacc2021-03-29T22:06:16ZengIEEEIEEE Access2169-35362019-01-01778280110.1109/ACCESS.2018.288581885731202D and 3D Image Quality Assessment: A Survey of Metrics and ChallengesYuzhen Niu0https://orcid.org/0000-0002-9874-9719Yini Zhong1Wenzhong Guo2Yiqing Shi3Peikun Chen4College of Mathematics and Computer Science, Fuzhou University, Fujian, ChinaCollege of Mathematics and Computer Science, Fuzhou University, Fujian, ChinaCollege of Mathematics and Computer Science, Fuzhou University, Fujian, ChinaCollege of Mathematics and Computer Science, Fuzhou University, Fujian, ChinaCollege of Mathematics and Computer Science, Fuzhou University, Fujian, ChinaImage 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.https://ieeexplore.ieee.org/document/8573120/Image quality assessmentimage aesthetics assessmentvisual comfortimage quality enhancement |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuzhen Niu Yini Zhong Wenzhong Guo Yiqing Shi Peikun Chen |
spellingShingle |
Yuzhen Niu Yini Zhong Wenzhong Guo Yiqing Shi Peikun Chen 2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges IEEE Access Image quality assessment image aesthetics assessment visual comfort image quality enhancement |
author_facet |
Yuzhen Niu Yini Zhong Wenzhong Guo Yiqing Shi Peikun Chen |
author_sort |
Yuzhen Niu |
title |
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges |
title_short |
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges |
title_full |
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges |
title_fullStr |
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges |
title_full_unstemmed |
2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges |
title_sort |
2d and 3d image quality assessment: a survey of metrics and challenges |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
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. |
topic |
Image quality assessment image aesthetics assessment visual comfort image quality enhancement |
url |
https://ieeexplore.ieee.org/document/8573120/ |
work_keys_str_mv |
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