Review: A Survey on Objective Evaluation of Image Sharpness

被引:22
|
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.
引用
收藏
页数:20
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