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
Tianshu Li, Shigang Wang
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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.
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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
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