Fiber Optic Speckle Recovery Based on Lightweight Adversarial Network

Yanzhu Zhang, Haishuai Zhang, Xiaomeng Zhang, J. Pu, Xiaoyan Wang
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Abstract

When light with object information passes through a multi-core fiber, the speckle pattern is obtained. The reconstruction of the original image from the speckle pattern is crucial. In this paper, we propose a lightweight adversarial network for reconstruct image from the speckle pattern. Combining the characteristics of U-Net network and Mobile-Net, a lightweight Mobile-U-Net network is formed to reduce the number of network parameters by using deep separable convolution to realize fast reconstructing image. The adversarial network is also introduced to restrain the quality of the restored image and solve the quality problem of the restored image further. Thus, a high-quality reconstructing image can be achieved.
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基于轻量级对抗网络的光纤散斑恢复
当带有物体信息的光通过多芯光纤时,得到散斑图。从散斑图中重建原始图像是至关重要的。在本文中,我们提出了一种轻量级的对抗网络,用于从散斑模式中重建图像。结合U-Net网络和Mobile-Net网络的特点,采用深度可分离卷积技术减少网络参数数量,实现图像的快速重构,形成了一种轻量级的Mobile-U-Net网络。引入对抗网络对恢复图像的质量进行约束,进一步解决恢复图像的质量问题。因此,可以获得高质量的重建图像。
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