Infrared and Laser Engineering, Volume. 53, Issue 2, 20230564(2024)

Research on phase unwrapping technology based on improved U-Net network

Ruishu Xu1,2,3, Xiaonan Luo3, Yaoqiong Shen1,2, Chuangwei Guo1,2, Wentao Zhang3, Yuqing Guan1,2, Yunxia Fu1,2, and Lihua Lei1,2、*
Author Affiliations
  • 1Shanghai Institute of Measurement and Testing Technology, Shanghai 201203, China
  • 2Shanghai Key Laboratory of Online Testing and Control Technology, Shanghai 201203, China
  • 3School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin 541004, China
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    [9] Holden Daniel, J Saito, T Komura. A deep learning framework for character motion synthesis and editing. ACM Journals, 35, 1-11(2016).

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    [14] [14] Zhou L. PUGAN: A onestep 2D InSAR phase unwrapping based on conditional generative adversarial wk [C]IEEE Trans Geosci Remote Sens, 2022, 60: 110.

    [16] Z Li, F Liu, W Yang, et al. A survey of convolutional neural networks: analysis, applications, and prospects. IEEE Transactions on Neural Networks and Learning Systems, 33, 6999-7019(2021).

    [18] [18] Ryu K, Gho S M, Nam Y, et al. Development of a deep learning method f phase unwrap MR images [C]Proc Int Soc Magn Reson Med, 2019, 27: 4707.

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    CLP Journals

    [1] Jingjing ZHANG, Jiansu LI, Changying DANG, Haowen CHEN, Zhao YANG. DC-UMnet network method for unwrapping the phase of holographic undersampling[J]. Infrared and Laser Engineering, 2024, 53(10): 20240219

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    Ruishu Xu, Xiaonan Luo, Yaoqiong Shen, Chuangwei Guo, Wentao Zhang, Yuqing Guan, Yunxia Fu, Lihua Lei. Research on phase unwrapping technology based on improved U-Net network[J]. Infrared and Laser Engineering, 2024, 53(2): 20230564

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    Paper Information

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    Received: Oct. 9, 2023

    Accepted: --

    Published Online: Mar. 27, 2024

    The Author Email:

    DOI:10.3788/IRLA20230564

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