A U-Net Based Method for Radio Astronomical Image Deconvolution

Xinghui Zhou

doi:10.1088/1674-4527/adf710

2025-10-01

PRE

DOI：10.1088/1674-4527/adf710

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摘要

En 中文

射电干涉测量中的反卷积因空间频率域中可见度的采样不完整（由有限的基线数量引起）而面临挑战，导致产生病态逆问题。将污点图像重建为清晰图像对于后续科学分析至关重要。为解决这些挑战，我们提出了一种基于U-Net的方法，该方法从污点图像中提取高层信息，并通过有效减少伪影和旁瓣来重建清晰图像。U-Net架构由编码器-解码器结构和跳跃连接组成，促进了信息流动并保留了空间细节。我们使用射电星系的模拟数据训练模型，并在测试集上评估其性能。与CLEAN方法和基于可见度与图像条件去噪扩散概率模型相比，我们提出的模型能够有效重建扩展源和微弱点源，并在结构相似性指数和峰值信噪比上获得更高值。此外，我们研究了噪声对模型性能的影响，证明了其在不同噪声水平下的鲁棒性。

Keyword:

techniques: image processing

techniques: interferometric

radio continuum: galaxies

methods: data analysis

期刊

Research in Astronomy and Astrophysics

IF:

论文数:

被引数:

机构

Guangzhou University

学者数:

1.8W

论文数: 1.3W

被引数: 1.8W

Shanghai Jiao Tong University

学者数:

7.8K

论文数: 2.4K

被引数: 14.8W

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