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

Zaipeng Duan; Yang Yang; Ruiqi Zhou; Jie Ma; Jiong Xiao; Zihang Liu; Feifei Hao; Jinwei Zeng; Jian Wang

doi:10.3788/AI.2024.10009

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 Duan^1,2,3、†, Yang Yang^1,2, Ruiqi Zhou^1,2, Jie Ma³, Jiong Xiao^1,2, Zihang Liu^1,2, Feifei Hao^1,2, Jinwei Zeng^1,2、*, and Jian Wang^1,2、*

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

show less

Supplementary Materials

AI_1_2_021003_ds001.pdf

Download

Tools

Get Citation

Copy Citation Text

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)

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

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

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology