Mr. Zhaoyang Tang Profile

Zhaoyang Tang

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Proceedings Article | 31 August 2021 Paper

High fidelity image reconstruction of light passing through scattering medium based on convolutional neural network

Zhaoyang Tang, Chengchao Xiang, Qixin Liu, Yue Dai, Jiaqi He, Yingchun Ding

Proceedings Volume 11907, 119072J (2021) https://doi.org/10.1117/12.2603144

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Optical imaging through scattering media such as ground glass, fog, biological tissues, etc. has always been a widely used and challenging task in the optical field. Compared with traditional imaging methods such as transmission matrix and optical phase conjugation, deep learning has shown great potential in this field because of its simple device and fast reconstruction speed. In this article, we developed an algorithm based on convolutional neural network to realize imaging through scattering media and applied this algorithm to recover complex images. The speckle images of the original images are obtained through a speckle generation program, and then the speckle images and the original images are input into the neural network in pairs for training. Finally, the reconstructed speckle images can be obtained by using the trained neural network. In the numerical simulation, we proposed two indicators, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), to evaluate the quality of reconstructed images. The results show that our method can restore highfidelity images. This new image reconstruction method provides new ideas for research in the fields of astronomy and biomedicine.

Proceedings Article | 31 August 2021 Paper

Research on multi-point light focusing based on complex neural network

Chengchao Xiang, Zhaoyang Ttang, Yuanshen Xiao, Yingchun Ding, Jiaqi He

Proceedings Volume 11907, 119072H (2021) https://doi.org/10.1117/12.2603136

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The research of light focusing and imaging through scattering media is currently a popular topic. Many focusing technologies have been developed, such as transmission matrix method, phase conjugation method, iterative optimization method, etc. However, these methods have some limitations. At present, deep learning methods have been widely used in the field of image restoration, and have strong inverse restoration capabilities. Yet, the application of this method in the field of optical focusing is still relatively limited, and the performance is not ideal. In this letter, a method based on complex neural network is proposed, and the multi-point focusing of light passing through the scattering medium is numerically simulated. Since the complex information of the network is not reduced, compared with the real number neural network method, this method more accurately simulates the recovery process of light scattering, and can obtain multiple light focal points with high enhancement at the same time.

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