Laser & Optoelectronics Progress, Volume. 61, Issue 16, 1611015(2024)

Deep Learning-Based Light-Field Image Restoration and Enhancement: A Survey (Invited)

Zeyu Xiao1, Zhiwei Xiong1、*, Lizhi Wang2, and Hua Huang3
Author Affiliations
  • 1Key Laboratory of Ministry of Education for Brain inspired Intelligent Perception and Cognition, School of Information Science and Technology, University of Science and Technology of China, Hefei 230027, Anhui, China
  • 2School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
  • 3School of Artificial Intelligence, Beijing Normal University, Beijing 100875, China
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    [18] Engl H W, Groetsch C W[M]. Inverse and ill-posed problems(2014).

    [25] Farrugia R A, Guillemot C. Light field super-resolution using a low-rank prior and deep convolutional neural networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 1162-1175(2020).

    [63] Wu G C, Liu Y B, Fang L et al. Revisiting light field rendering with deep anti-aliasing neural network[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 5430-5444(2022).

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    Zeyu Xiao, Zhiwei Xiong, Lizhi Wang, Hua Huang. Deep Learning-Based Light-Field Image Restoration and Enhancement: A Survey (Invited)[J]. Laser & Optoelectronics Progress, 2024, 61(16): 1611015

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    Paper Information

    Category: Imaging Systems

    Received: Jun. 3, 2024

    Accepted: Jul. 11, 2024

    Published Online: Aug. 12, 2024

    The Author Email: Zhiwei Xiong (zwxiong@ustc.edu.cn)

    DOI:10.3788/LOP241404

    CSTR:32186.14.LOP241404

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