Mr. Shuo Zhu Profile

Shuo Zhu

at Nanjing Univ of Science and Technology

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Proceedings Article | 12 March 2021 Paper

Research on optimal skip connection scale in learning-based scattering imaging

Yingjie Shi, Enlai Guo, Shuo Zhu, Jie Gu, Lianfa Bai, Jing Han

Proceedings Volume 11763, 117630Y (2021) https://doi.org/10.1117/12.2586177

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Strong scattering media bring difficulties to imaging in many fields such as medicine and astronomy. The deep learning method has a powerful fitting ability, which can be better applied in reconstructing the target behind the scattering medium. But the detail of the reconstructed target is often inaccurate. In this paper, the skip connection is added in the neural network to improve the accuracy of the reconstructed detail. This network can combine pixel-level information with high-level semantic information, and the information missed during the encoding process can be more involved in the final reconstruction process. 1100 handwritten characters are used as the targets hidden behind the ground glass. It is found that the quality of the reconstructed target is different when the skip connection is added to the network at different scales. The feature map visualization method is used to help us analyze the role of the skip connection. Meanwhile, PSNR (Peak Signal to Noise Ratio) is also used as an objective evaluation standard to evaluate the quality of reconstructed targets. According to subjective and objective evaluation criteria, conclusions can be drawn that the detail of targets can be better retained when the skip connection is added between the convolutional layer corresponding to the feature map of the size 64*64, and the average PSNR can be enhanced 1 dB compared with the network without skip connections. This work provides a reference for the fusion methods of different scale features in the computational optical imaging.

Proceedings Article | 15 January 2021 Paper

High sensitive locating through scattering medium with phase-space-prior

Shuo Zhu, Enlai Guo, Qianying Cui, Dongliang Zheng, Lianfa Bai, Jing Han

Proceedings Volume 11761, 117611W (2021) https://doi.org/10.1117/12.2586521

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The light scattering brings serious degradation for the object information. The conventional optical techniques cannot extract the relevant message on the object location in the scattering. In this paper, in the phase-space, the speckle characteristic with different depths has been analyzed and discussed. We utilize the phase-space-prior to locate the objects through a strong scattering medium with a learning method. Comparing with the single data-driven method, our scheme can help the deep neural network (DNN) to extract the depth information efficiently. The experimental results proved that our method is novel and technically correct with high locating accuracy. Our technique paves the way to a physical-informed DNN in locating and ranging objects through complex scattering media.

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