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Multi-directional sub-aperture wrapped phase aberration compensation for synthetic aperture digital holographic microscopy using deep learning
10.1016/j.optlastec.2025.113595
2025-07-21
0
PRE
AI
Abstract
En 中文
• Proposes sub-aperture aberration compensation enabling 1.87 × resolution enhancement. • Integrates Moga Blocks into ConvNeXt for better feature balance and robustness. • Creates a hybrid simulation dataset with diverse samples to enhance generalization. • Achieves baseline unification via averaging sub-aperture unwrapped phase maps. • High-fidelity synthetic aperture imaging without residual aberration correction.
Keywords:
sub-aperture aberration compensation
ConvNeXt with Moga Blocks
hybrid simulation dataset
baseline unification
synthetic aperture imaging
Journal
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IF:
5
Papers: 1.4K
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Citations: 3.5W
Researchers
L
Liu Huang
H-index:
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Papers: 1
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Citations: 0
Z
Zhiwei Wang
H-index:
0
Papers: 1
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Citations: 0
B
Benyong Chen
H-index:
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Papers: 1
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Citations: 0
X
Xiaping Fu
H-index:
0
Papers: 1
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Citations: 0
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