基于深度学习的全景图像质量评价研究现状及展望
Research Status and Prospects of Omnidirectional Image Quality Assessment Based on Deep Learning
摘要
Abstract
In recent years,with the rapid development of virtual reality technology,omnidirectional images have gradually gained widespread attention due to their significant role in providing immersive experiences.Existing objective image quality assessment methods have not effectively evaluated the quality of omnidirectional images,making it particularly necessary to design specialized objective quality assessment methods for omnidirectional images.This paper provides a comprehensive summary of the research progress in deep learning-based objective quality assessment methods for omni-directional images.The characteristics of omnidirectional images are analyzed.Based on the input image type of the assess-ment methods,objective quality assessment methods for omnidirectional images are divided into four categories:equirectangular projection format quality assessment methods,segmented spherical projection format quality assessment methods,cubic projection format quality assessment methods,and viewport image quality assessment methods.The prin-ciples,characteristics,and performance of these methods are compared.The datasets and evaluation metrics used in ob-jective omnidirectional image quality assessment are summarized.The future development directions of objective omnidirec-tional image quality assessment are discussed,and practical research ideas for subsequent studies are provided.关键词
全景图像/深度学习/图像质量评价/虚拟现实/客观评价Key words
omnidirectional image/deep learning/image quality assessment/virtual reality/objective assessment分类
信息技术与安全科学引用本文复制引用
田颖哲,董武,陆利坤,马倩,周子镱,张二青..基于深度学习的全景图像质量评价研究现状及展望[J].计算机科学与探索,2026,20(3):650-670,21.基金项目
北京印刷学院校级科研项目(E6202405) （E6202405）
北京印刷学院学科建设和研究生教育专项(21090525014,21090325003) （21090525014,21090325003）
北京印刷学院信息与通信工程一级学科博士点培育项目(21090525004) （21090525004）
北京印刷学院出版学新兴交叉学科平台建设项目(04190123001/003) （04190123001/003）
北京印刷学院科研平台建设项目(KYCPT202509).This work was supported by the University-Level Scientific Research Project of Beijing Institute of Graphic Communication(E6202405),the Discipline Construction and Postgraduate Education Special Project of Beijing Institute of Graphic Communication(21090525014,21090325003),the First-Level Discipline Doctoral Program Cultivation Project in Information and Communica-tion Engineering of Beijing Institute of Graphic Communication(21090525004),the Emerging Interdisciplinary Platform Construction Project for Publishing Science of Beijing Institute of Graphic Communication(04190123001/003),and the Scientific Research Platform Construction Project of Beijing Institute of Graphic Communication(KYCPT202509). （KYCPT202509）
