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5 November 2020 Learning-based short-coherence digital holographic imaging through scattering media
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Abstract
Conventional digital holography (DH) technique largely limited by the effect of random scattering media in the imaging path, which causes great challenges for its applications in vivo imaging. As an improvement, short-coherence digital holography (SCDH) uses a low-coherence light source (near-infrared (NIR) region), where the absorption of light is at a minimum, to enhance its ability to resist scattering. However, SCDH also fails under strong scattering conditions. Here we propose to use deep learning (DL) for SCDH, and the results show that an image of a target behind a 2.30 mm chicken breast tissue can be reconstructed successfully. We experimentally demonstrate that DL-based SCDH can be used to reconstruct the object from a single measurement under some hard conditions, for example, when there is strong static or dynamic scattering media in the imaging path.
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Shi Dong, Fei Wang, Hao Wang, Wanqin Yang, Haichao Wang, Xin Fan, and Guohai Situ "Learning-based short-coherence digital holographic imaging through scattering media", Proc. SPIE 11565, AOPC 2020: Display Technology; Photonic MEMS, THz MEMS, and Metamaterials; and AI in Optics and Photonics, 1156510 (5 November 2020); https://doi.org/10.1117/12.2580150
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