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Imaging through a scattering medium via model-driven deep learning
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DOI：10.1364/OL.498796.png)
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摘要
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Imaging through a scattering medium is of great significance in many areas. Especially, speckle correlation imaging has been valued for its noninvasiveness. In this work, we report a deep learning solution that incorporates the physical model and an additional regularization for high-fidelity speckle correlation imaging. Without large-scale data to train, the physical model and regularization prior provide a correct direction for neural network to precisely reconstruct hidden objects from speckle under different scattering scenarios and noise levels. Experimental results demonstrate that the proposed method presents a significant advance in improving generalization and combating the invasion of noise. (c) 2023 Optica Publishing Group
Keyword:
TRANSMISSION MATRIX
SPECKLE CORRELATION
LAYERS
WAVES
期刊
IF:
3.3
论文数:
4.0W
被引数:
7.6W
机构
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