Image reconstruction from optical speckle pattern based on deep learning

Lihua Shen; Bote Qi; Rui-Pin Chen

doi:10.1117/12.2602488

9 October 2021 Image reconstruction from optical speckle pattern based on deep learning

Lihua Shen, Bote Qi, Rui-Pin Chen

Proceedings Volume 11897, Optoelectronic Imaging and Multimedia Technology VIII; 118970F (2021) https://doi.org/10.1117/12.2602488
Event: SPIE/COS Photonics Asia, 2021, Nantong, JS, China

Abstract

The image reconstruction of an object passed through a scattering media has attracted a lot of interest due to its potential application in corresponding fields. Recently, the deep learning techniques have been introduced into the computational imaging through scattering media and obtained good results. In this work, a modified U-Net model with dense blocks is designed under the framework of PyTorch, MobileNet is used as the backbone model. The network is trained by using mean square error (MSE) loss function. The features of image can be extracted and the information of every pixel of the speckle field can be classified and restored in this model through depth separable convolution. Thus, the speckle field can be reconstructed. The experimental results show that this network has good generalization ability for image reconstruction and improves the ability of information acquisition.

Conference Presentation

Citation Download Citation

Lihua Shen, Bote Qi, and Rui-Pin Chen "Image reconstruction from optical speckle pattern based on deep learning", Proc. SPIE 11897, Optoelectronic Imaging and Multimedia Technology VIII, 118970F (9 October 2021); https://doi.org/10.1117/12.2602488

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