Advanced Imaging, Volume. 1, Issue 2, 021003(2024)

Ultra-robust imaging restoration of intrinsic deterioration in graded-index imaging systems enabled by classified-cascaded convolutional neural networks

Zaipeng Duan1,2,3、†, Yang Yang1,2, Ruiqi Zhou1,2, Jie Ma3, Jiong Xiao1,2, Zihang Liu1,2, Feifei Hao1,2, Jinwei Zeng1,2、*, and Jian Wang1,2、*
Author Affiliations
  • 1Wuhan National Laboratory for Optoelectronics and School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
  • 2Optics Valley Laboratory, Wuhan, China
  • 3National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
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    Zaipeng Duan, Yang Yang, Ruiqi Zhou, Jie Ma, Jiong Xiao, Zihang Liu, Feifei Hao, Jinwei Zeng, Jian Wang, "Ultra-robust imaging restoration of intrinsic deterioration in graded-index imaging systems enabled by classified-cascaded convolutional neural networks," Adv. Imaging 1, 021003 (2024)

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    Paper Information

    Category: Research Article

    Received: Jun. 15, 2024

    Accepted: Aug. 19, 2024

    Published Online: Sep. 20, 2024

    The Author Email: Jinwei Zeng (zengjinwei@hust.edu.cn), Jian Wang (jwang@hust.edu.cn)

    DOI:10.3788/AI.2024.10009

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