Abstract
We propose a hybrid deep framework that combines trained as well as untrained deep models for phase recovery in inline holography. We adopted distributed optimization which efficiently combines learned priors in loss function for high-fidelity reconstruction.
© 2023 The Author(s)
PDF Article | Presentation VideoMore Like This
Mingjun Xiang, Lingxiao Wang, Yu Sha, Hui Yuan, Kai Zhou, and Hartmut G. Roskos
Tu4A.4 Digital Holography and Three-Dimensional Imaging (DH) 2022
Tomoyoshi Shimobaba, Vipin Tiwari, Anuj Gupta, Fan Wang, Harutaka Shiomi, Chau-Jern Cheng, and Tomoyoshi Ito
JW4A.6 Frontiers in Optics (FiO) 2023
Silvio Montresor, Ketao Yan, Marie Tahon, Kemao Qian, Yingjie Yu, and Pascal Picart
HW3C.4 Digital Holography and Three-Dimensional Imaging (DH) 2023