Breaking Boundaries: A Universal Wavefront Reconstruction Approach for High-resolution Solar Imaging

This Letter proposes a universal wavefront reconstruction approach based on a coupled data set and neural network, aiming to overcome the limitations of current algorithms in terms of universality and wavefront sensing accuracy for variable imaging objects. First, a novel data set, Multi-Object Wave...

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Bibliographic Details
Published in:Astrophysical journal. Letters 2024-07, Vol.970 (1), p.L1
Main Authors: Ge, Xinlan, Zhu, Licheng, Gao, Zeyu, Ma, Shiqing, Li, Ao, Wang, Shuai, Yang, Ping
Format: Article
Language:English
Subjects:
Algorithms
Astronomical models
Celestial bodies
Datasets
Decoupling
Energy utilization
High resolution
Image reconstruction
Image resolution
Image restoration
Neural networks
Solar activity
Solar imagery
Wave front reconstruction
Wave front sensors
Wave fronts
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Summary:This Letter proposes a universal wavefront reconstruction approach based on a coupled data set and neural network, aiming to overcome the limitations of current algorithms in terms of universality and wavefront sensing accuracy for variable imaging objects. First, a novel data set, Multi-Object Wavefront Coupling Dataset (MOCD-Dataset), is developed to provide diverse data and enable the network to learn universal wavefront features. Next, a new universal wavefront reconstruction network called Object-Independent Wavefront Decoupling Network (OIWD-Net) is introduced, aiming to separate imaging object information from multiple variable images. Our algorithm eliminates the need for specialized wavefront sensors, has a simple system, high light energy utilization, and does not require customized models for each different type of imaging objects, making it highly practical. By combining the MOCD-Dataset and the OIWD-Net, excellent accuracy in wavefront reconstruction of different imaging objects has been achieved. This research provides a new solution for high-resolution image restoration in fields such as solar structure observation and astronomical high-resolution imaging.
ISSN:2041-8205
2041-8213
DOI:10.3847/2041-8213/ad5b53