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Phase unwrapping method based on improved U-net network
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Title: Phase unwrapping method based on improved U-net network

Creator:

Li, Jiansu ; Chen, Haowen ; Yang, Zhao ; Zhao, Junsheng ; Dang, Changying ; Zhang, Jingjing

Contributor:

Urbańczyk, Wacław. Redakcja

Description:

Optica Applicata, Vol. 54, 2024, nr 4, s. 532-539 ; Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory ; click here to follow the link

Abstrakt:

In order to solve the problem of unwrapping the phase in digital holographic reconstruction, a new convolutional architecture is proposed. The proposed method takes the U-net network as a framework, and incorporates the lightweight deep learning network of Mobilenetv1 in the encoding part to reduce the model complexity, the number of parameters, and the cost of computation; and proposes a complex dual-channel convolutional block in the decoding part instead of the 3 × 3 convolution in the original U-net network, which fully incorporates the features in the decoding process. (abbreviated as DC-UMnet network) Meanwhile, the loss value is calculated using the SmoothL1Loss function, and the activation function uses ReLU6. Finally, the simulated dataset containing noise is used for training; and the experimentally obtained wrapped phase maps is used for verifying. The simulation results show that under different degrees of noise conditions, compared with the DCT method and the deep learning phase unwrapping network, the structural similarity index values of the DC-UMnet network are improved by 0.416 and 0.064; and the normalized root-mean-square errors are reduced respectively by 13.2% and 5.8%. Through the actual measurement data, the proposed network model of the feasibility and good noise reduction ability are verified, which can realize digital holographic phase unwrapping in a simple, fast and efficient way.

Publisher:

Oficyna Wydawnicza Politechniki Wrocławskiej

Place of publication:

Wrocław

Date:

2024

Resource Type:

artykuł

Resource Identifier:

doi:10.37190/oa/195576 ; oai:dbc.wroc.pl:137462

Source:

<sygn. PWr A3481II> ; click here to follow the link ; click here to follow the link

Language:

eng

Relation:

Optica Applicata ; Optica Applicata, Vol. 54, 2024 ; Optica Applicata, Vol. 54, 2024, nr 4 ; Politechnika Wrocławska. Wydział Podstawowych Problemów Techniki

Rights:

Wszystkie prawa zastrzeżone (Copyright)

Access Rights:

Dla wszystkich w zakresie dozwolonego użytku

Location:

Politechnika Wrocławska

Group publication title:

Optica Applicata

Subject and keywords:

optyka phase unwrapping DC-UMnet network deep learning digital holography

Object collections:

Last modified:

Jun 30, 2025

In our library since:

Jun 30, 2025

Number of object content hits:

2

All available object's versions:

https://dbc.wroc.pl/publication/176123

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Edition name Date
Phase unwrapping method based on improved U-net network Jun 30, 2025

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