Acta Optica Sinica, Volume. 42, Issue 4, 0436001(2022)
Expansion of Depth-of-Field of Scattering Imaging Based on DenseNet
Scattering is a fundamental phenomenon in nature. The imaging with large depth-of-field through a scattering medium is significant and valuable. In recent years, with the wide application of deep learning in computational imaging, it is urgent to study and further extend the depth-of-field in a scattering imaging system. In the paper, based on DenseNet and combined with the UNet architecture, a deep convolutional neural network model, namely DUNet, with good mobility and depth-of-field expansion ability is proposed. Moreover, the network is trained with speckle images passing through frosted glasses of different mesh, and the depth-of-field can be generalized to 50 mm away from the focal plane. The preliminary results on a rat brain slice demonstrate that the DUNet can be further implemented in the tomographic scanning of deep tissues.
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Zhaosu Lin, Yangyundou Wang, Hao Wang, Chuanfei Hu, Min Gu, Hui Yang. Expansion of Depth-of-Field of Scattering Imaging Based on DenseNet[J]. Acta Optica Sinica, 2022, 42(4): 0436001
Category: Letters
Received: Nov. 12, 2021
Accepted: Dec. 23, 2021
Published Online: Jan. 29, 2022
The Author Email: Wang Yangyundou (ywang0606@usst.edu.cn), Yang Hui (yanghui313@126.com)