Mitigating the ambiguity problem in the CNN-based wavefront correction

Chenda Lu; Qinghua Tian; Lei Zhu; Ran Gao; Haipeng Yao; Feng Tian; Qi Zhang; Xiangjun Xin

doi:10.1364/OL.459799

Mitigating the ambiguity problem in the CNN-based wavefront correction

Chenda Lu, Qinghua Tian^*, Lei Zhu, Ran Gao, Haipeng Yao, Feng Tian, Qi Zhang, Xiangjun Xin

^*Corresponding author for this work

School of Information and Electronics

Beijing University of Posts and Telecommunications

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

In this work, we propose an attention-based adaptive optics method that uses a non-local block to integrate phase diversity with a convolutional neural network (CNN). The simulation results showcase the effectiveness of the proposed method to mitigate the ambiguity problem of phase retrieval and better performance than traditional CNN-based wavefront correction.

Original language	English
Pages (from-to)	3251-3254
Number of pages	4
Journal	Optics Letters
Volume	47
Issue number	13
DOIs	https://doi.org/10.1364/OL.459799
Publication status	Published - 1 Jul 2022

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title = "Mitigating the ambiguity problem in the CNN-based wavefront correction",

abstract = "In this work, we propose an attention-based adaptive optics method that uses a non-local block to integrate phase diversity with a convolutional neural network (CNN). The simulation results showcase the effectiveness of the proposed method to mitigate the ambiguity problem of phase retrieval and better performance than traditional CNN-based wavefront correction.",

author = "Chenda Lu and Qinghua Tian and Lei Zhu and Ran Gao and Haipeng Yao and Feng Tian and Qi Zhang and Xiangjun Xin",

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T1 - Mitigating the ambiguity problem in the CNN-based wavefront correction

AU - Lu, Chenda

AU - Tian, Qinghua

AU - Zhu, Lei

AU - Gao, Ran

AU - Yao, Haipeng

AU - Tian, Feng

AU - Zhang, Qi

AU - Xin, Xiangjun

PY - 2022/7/1

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N2 - In this work, we propose an attention-based adaptive optics method that uses a non-local block to integrate phase diversity with a convolutional neural network (CNN). The simulation results showcase the effectiveness of the proposed method to mitigate the ambiguity problem of phase retrieval and better performance than traditional CNN-based wavefront correction.

AB - In this work, we propose an attention-based adaptive optics method that uses a non-local block to integrate phase diversity with a convolutional neural network (CNN). The simulation results showcase the effectiveness of the proposed method to mitigate the ambiguity problem of phase retrieval and better performance than traditional CNN-based wavefront correction.

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U2 - 10.1364/OL.459799

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VL - 47

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JO - Optics Letters

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IS - 13

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Mitigating the ambiguity problem in the CNN-based wavefront correction

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