A comprehensive research on light field imaging: Theory and application

Abstract Computational photography is a combination of novel optical designs and processing methods to capture high‐dimensional visual information. As an emerged promising technique, light field (LF) imaging measures the lighting, reflectance, focus, geometry and viewpoint in the free space, which h...

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Main Authors: Fei Liu, Yunlong Wang, Qing Yang, Shubo Zhou, Kunbo Zhang
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Computer Vision
Subjects:
Online Access:https://doi.org/10.1049/cvi2.12321
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author Fei Liu
Yunlong Wang
Qing Yang
Shubo Zhou
Kunbo Zhang
author_facet Fei Liu
Yunlong Wang
Qing Yang
Shubo Zhou
Kunbo Zhang
author_sort Fei Liu
collection DOAJ
description Abstract Computational photography is a combination of novel optical designs and processing methods to capture high‐dimensional visual information. As an emerged promising technique, light field (LF) imaging measures the lighting, reflectance, focus, geometry and viewpoint in the free space, which has been widely explored for depth estimation, view synthesis, refocus, rendering, 3D displays, microscopy and other applications in computer vision in the past decades. In this paper, the authors present a comprehensive research survey on the LF imaging theory, technology and application. Firstly, the LF imaging process based on a MicroLens Array structure is derived, that is MLA‐LF. Subsequently, the innovations of LF imaging technology are presented in terms of the imaging prototype, consumer LF camera and LF displays in Virtual Reality (VR) and Augmented Reality (AR). Finally the applications and challenges of LF imaging integrating with deep learning models are analysed, which consist of depth estimation, saliency detection, semantic segmentation, de‐occlusion and defocus deblurring in recent years. It is believed that this paper will be a good reference for the future research on LF imaging technology in Artificial Intelligence era.
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institution Kabale University
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language English
publishDate 2024-12-01
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series IET Computer Vision
spelling doaj-art-cdbf22afee7541f8ab6b84603f8904d52024-12-28T11:01:57ZengWileyIET Computer Vision1751-96321751-96402024-12-011881269128410.1049/cvi2.12321A comprehensive research on light field imaging: Theory and applicationFei Liu0Yunlong Wang1Qing Yang2Shubo Zhou3Kunbo Zhang4School of Management and Engineering Capital University of Economics and Business Beijing ChinaNew Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences Beijing ChinaSchool of Management and Engineering Capital University of Economics and Business Beijing ChinaCollege of Information Science and Technology Donghua University Shanghai ChinaNew Laboratory of Pattern Recognition (NLPR), State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS) Institute of Automation Chinese Academy of Sciences Beijing ChinaAbstract Computational photography is a combination of novel optical designs and processing methods to capture high‐dimensional visual information. As an emerged promising technique, light field (LF) imaging measures the lighting, reflectance, focus, geometry and viewpoint in the free space, which has been widely explored for depth estimation, view synthesis, refocus, rendering, 3D displays, microscopy and other applications in computer vision in the past decades. In this paper, the authors present a comprehensive research survey on the LF imaging theory, technology and application. Firstly, the LF imaging process based on a MicroLens Array structure is derived, that is MLA‐LF. Subsequently, the innovations of LF imaging technology are presented in terms of the imaging prototype, consumer LF camera and LF displays in Virtual Reality (VR) and Augmented Reality (AR). Finally the applications and challenges of LF imaging integrating with deep learning models are analysed, which consist of depth estimation, saliency detection, semantic segmentation, de‐occlusion and defocus deblurring in recent years. It is believed that this paper will be a good reference for the future research on LF imaging technology in Artificial Intelligence era.https://doi.org/10.1049/cvi2.12321camerasimage captureimage processingimage sampling
spellingShingle Fei Liu
Yunlong Wang
Qing Yang
Shubo Zhou
Kunbo Zhang
A comprehensive research on light field imaging: Theory and application
IET Computer Vision
cameras
image capture
image processing
image sampling
title A comprehensive research on light field imaging: Theory and application
title_full A comprehensive research on light field imaging: Theory and application
title_fullStr A comprehensive research on light field imaging: Theory and application
title_full_unstemmed A comprehensive research on light field imaging: Theory and application
title_short A comprehensive research on light field imaging: Theory and application
title_sort comprehensive research on light field imaging theory and application
topic cameras
image capture
image processing
image sampling
url https://doi.org/10.1049/cvi2.12321
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