Joint Generating Terminal Correction Imaging method for modular LED integral imaging systems

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Computer Vision and Image Understanding Pub Date : 2025-02-01 DOI:10.1016/j.cviu.2025.104279
Tianshu Li, Shigang Wang
{"title":"Joint Generating Terminal Correction Imaging method for modular LED integral imaging systems","authors":"Tianshu Li,&nbsp;Shigang Wang","doi":"10.1016/j.cviu.2025.104279","DOIUrl":null,"url":null,"abstract":"<div><div>Integral imaging has garnered significant attention in 3D display technology due to its potential for high-quality visualization. However, elemental images in integral imaging systems usually suffer from misalignment due to the mechanical or human-induced assembly within the lens arrays, leading to undesirable display quality. This paper introduces a novel Joint-Generating Terminal Correction Imaging (JGTCI) approach tailored for large-scale, modular LED integral imaging systems to address the misalignment between the optical centers of physical lens arrays and the camera in generated elemental image arrays. Specifically, we propose: (1) a high-sensitivity calibration marker to enhance alignment precision by accurately matching lens centers to the central points of elemental images; (2) a partitioned calibration strategy that supports independent calibration of display sections, enabling seamless system expansion without recalibrating previously adjusted regions; and (3) a calibration setup where markers are strategically placed near the lens focal length, ensuring optimal pixel coverage in the camera frame for improved accuracy. Extensive experimental results demonstrate that our JGTCI approach significantly enhances 3D display accuracy, extends the viewing angle, and improves the scalability and practicality of modular integral imaging systems, outperforming recent state-of-the-art methods.</div></div>","PeriodicalId":50633,"journal":{"name":"Computer Vision and Image Understanding","volume":"252 ","pages":"Article 104279"},"PeriodicalIF":4.3000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Vision and Image Understanding","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077314225000025","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Integral imaging has garnered significant attention in 3D display technology due to its potential for high-quality visualization. However, elemental images in integral imaging systems usually suffer from misalignment due to the mechanical or human-induced assembly within the lens arrays, leading to undesirable display quality. This paper introduces a novel Joint-Generating Terminal Correction Imaging (JGTCI) approach tailored for large-scale, modular LED integral imaging systems to address the misalignment between the optical centers of physical lens arrays and the camera in generated elemental image arrays. Specifically, we propose: (1) a high-sensitivity calibration marker to enhance alignment precision by accurately matching lens centers to the central points of elemental images; (2) a partitioned calibration strategy that supports independent calibration of display sections, enabling seamless system expansion without recalibrating previously adjusted regions; and (3) a calibration setup where markers are strategically placed near the lens focal length, ensuring optimal pixel coverage in the camera frame for improved accuracy. Extensive experimental results demonstrate that our JGTCI approach significantly enhances 3D display accuracy, extends the viewing angle, and improves the scalability and practicality of modular integral imaging systems, outperforming recent state-of-the-art methods.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
Computer Vision and Image Understanding
Computer Vision and Image Understanding 工程技术-工程:电子与电气
CiteScore
7.80
自引率
4.40%
发文量
112
审稿时长
79 days
期刊介绍: The central focus of this journal is the computer analysis of pictorial information. Computer Vision and Image Understanding publishes papers covering all aspects of image analysis from the low-level, iconic processes of early vision to the high-level, symbolic processes of recognition and interpretation. A wide range of topics in the image understanding area is covered, including papers offering insights that differ from predominant views. Research Areas Include: • Theory • Early vision • Data structures and representations • Shape • Range • Motion • Matching and recognition • Architecture and languages • Vision systems
期刊最新文献
Monocular per-object distance estimation with Masked Object Modeling Editorial Board Corrigendum to “LightSOD: Towards lightweight and efficient network for salient object detection” [J. Comput. Vis. Imag. Underst. 249 (2024) 104148] Guided image filtering-conventional to deep models: A review and evaluation study Learning to mask and permute visual tokens for Vision Transformer pre-training
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1