Review: A Survey on Objective Evaluation of Image Sharpness

被引：30
作者：
Zhu, Mengqiu [1 ]
Yu, Lingjie [1 ]
Wang, Zongbiao [2 ]
Ke, Zhenxia [1 ]
Zhi, Chao [1 ,3 ]
机构：
[1] Xian Polytech Univ, Sch Text Sci & Engn, Xian 710048, Peoples R China
[2] Univ Sydney, Fac Engn, Sydney, NSW 2006, Australia
[3] Xian Polytech Univ, Key Lab Funct Text Mat & Prod, Minist Educ, Xian 710048, Peoples R China
来源：
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 04期
基金：
中国国家自然科学基金;
关键词：
evaluation metric; image sharpness; no-reference; image quality; evaluation algorithm; QUALITY ASSESSMENT; STRUCTURAL INFORMATION; BLUR ASSESSMENT; GRADIENT; MAP;
D O I：
10.3390/app13042652
中图分类号：
O6 [化学];
学科分类号：
0703 ;
摘要：
Establishing an accurate objective evaluation metric of image sharpness is crucial for image analysis, recognition and quality measurement. In this review, we highlight recent advances in no-reference image quality assessment research, divide the reported algorithms into four groups (spatial domain-based methods, spectral domain-based methods, learning-based methods and combination methods) and outline the advantages and disadvantages of each method group. Furthermore, we conduct a brief bibliometric study with which to provide an overview of the current trends from 2013 to 2021 and compare the performance of representative algorithms on public datasets. Finally, we describe the shortcomings and future challenges in the current studies.
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页数：20
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[41]   Which Has Better Visual Quality: The Clear Blue Sky or a Blurry Animal? [J].
Li, Dingquan ;
Jiang, Tingting ;
Lin, Weisi ;
Jiang, Ming .
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 21 (05) :1221-1234
[42]   Exploiting High-Level Semantics for No-Reference Image Quality Assessment of Realistic Blur Images [J].
Li, Dingquan ;
Jiang, Tingting ;
Jiang, Ming .
PROCEEDINGS OF THE 2017 ACM MULTIMEDIA CONFERENCE (MM'17), 2017, :378-386
[43]   No-Reference Image Blur Assessment Based on Discrete Orthogonal Moments [J].
Li, Leida ;
Lin, Weisi ;
Wang, Xuesong ;
Yang, Gaobo ;
Bahrami, Khosro ;
Kot, Alex C. .
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (01) :39-50
[44]   No-Reference and Robust Image Sharpness Evaluation Based on Multiscale Spatial and Spectral Features [J].
Li, Leida ;
Xia, Wenhan ;
Lin, Weisi ;
Fang, Yuming ;
Wang, Shiqi .
IEEE TRANSACTIONS ON MULTIMEDIA, 2017, 19 (05) :1030-1040
[45]   Image Sharpness Assessment by Sparse Representation [J].
Li, Leida ;
Wu, Dong ;
Wu, Jinjian ;
Li, Haoliang ;
Lin, Weisi ;
Kot, Alex C. .
IEEE TRANSACTIONS ON MULTIMEDIA, 2016, 18 (06) :1085-1097
[46]   No-Reference Quality Assessment for Multiply-Distorted Images in Gradient Domain [J].
Li, Qiaohong ;
Lin, Weisi ;
Fang, Yuming .
IEEE SIGNAL PROCESSING LETTERS, 2016, 23 (04) :541-545
[47]   Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study [J].
Li, Yali ;
Jiang, Yaojun ;
Yu, Xi ;
Ren, Binbin ;
Wang, Chunyu ;
Chen, Sihui ;
Ma, Duoshan ;
Su, Danyang ;
Liu, Huilong ;
Ren, Xiangyang ;
Yang, Xiaopeng ;
Gao, Jianbo ;
Wu, Yan .
FRONTIERS IN ENDOCRINOLOGY, 2022, 13
[48]   No-reference image quality assessment with shearlet transform and deep neural networks [J].
Li, Yuming ;
Po, Lai-Man ;
Xu, Xuyuan ;
Feng, Litong ;
Yuan, Fang ;
Cheung, Chun-Ho ;
Cheung, Kwok-Wai .
NEUROCOMPUTING, 2015, 154 :94-109
[49]   Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning [J].
Lin, Kwan-Yee ;
Wang, Guanxiang .
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, :732-741
[50]   A novel scheme for image sharpness using inflection points [J].
Lin, Li-Hui ;
Chen, Tzong-Jer .
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2020, 30 (03) :753-760
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