单月,刘段,万晓霞.无参考图像质量评价研究现状与前景分析[J].包装工程,2022,43(13):296-304.
SHAN Yue,LIU Duan,WAN Xiao-xia.Current Research Status and Prospect of No-reference Image Quality Assessment[J].Packaging Engineering,2022,43(13):296-304.
无参考图像质量评价研究现状与前景分析
Current Research Status and Prospect of No-reference Image Quality Assessment
  
DOI:10.19554/j.cnki.1001-3563.2022.13.037
中文关键词:  图像质量评价  无参考图像质量评价  CiteSpace  特征提取  自然场景统计  文献计量分析
英文关键词:image quality assessment  no-reference image quality assessment  CiteSpace  feature extraction  natural scene statistics  bibliometric analysis
基金项目:
作者单位
单月 武汉大学 图像传播与印刷包装研究中心,武汉 430072 
刘段 武汉大学 图像传播与印刷包装研究中心,武汉 430072 
万晓霞 武汉大学 图像传播与印刷包装研究中心,武汉 430072 
AuthorInstitution
SHAN Yue Research Center of Image Communication and Printing and Packaging, Wuhan University, Wuhan 430072, China 
LIU Duan Research Center of Image Communication and Printing and Packaging, Wuhan University, Wuhan 430072, China 
WAN Xiao-xia Research Center of Image Communication and Printing and Packaging, Wuhan University, Wuhan 430072, China 
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中文摘要:
      目的 为了进一步掌握无参考图像质量评价的发展过程与研究热点,为后续的相关研究提供参考。方法 使用citespace文献可视化软件对2000—2021年在Web of Science检索到的1 712条文献数据进行基本分析、共被引分析和
英文摘要:
      The work aims to further understand the development process and research hotspots of no-reference image quality assessment and provide reference for subsequent related research. CiteSpace literature visualization software was used to conduct basic analysis, co-citation analysis and Keywordanalysis on 1 712 items of literature retrieved from Web of Science from 2000 to 2021. The development characteristics of no-reference image quality assessment were obtained by analyzing the visualization atlas. The analysis results showed that no-reference image quality assessment was currently in a stage of rapid development, and countries all over the world had made achievements in this field. At present, there were more mature no-reference image assessment algorithms, but there was still a gap in accuracy compared with subjective assessment. In the future, researchers should combine today's artificial intelligence technology to promote the transition from high-speed development to high-quality development of no-reference image quality assessment.
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