Affiliation:
1. School of Textile Science and Engineering, Xi’an Polytechnic University, Xi’an 710048, China
2. Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia
3. Key Laboratory of Functional Textile Material and Product, Xi’an Polytechnic University, Ministry of Education, Xi’an 710048, China
Abstract
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.
Funder
National Natural Science Foundation of China
Key Research and Development Program of Shaanxi
Natural Science Basic Research Program of Shaanxi
Innovation Capability Support Program of Shaanxi
Outstanding Young Talents Support Plan of Shaanxi Universities (2020), Scientific Research Program Funded by Shaanxi Provincial Education Department
Science and Technology Guiding Project of China National Textile and Apparel Council
Innovation Capacity Support Plan of Shaanxi, China
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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