Open AccessLearning-based imaging through scattering media
Author(s) -
Ryoichi Horisaki,
Ryosuke Takagi,
Jun Tanida
Publication year - 2016
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.24.013738
Subject(s) - scattering , optics , inverse scattering problem , speckle pattern , light scattering , computer science , phase retrieval , speckle noise , x ray scattering techniques , speckle imaging , inverse problem , artificial intelligence , physics , x ray raman scattering , mathematics , inelastic scattering , mathematical analysis , quantum mechanics , fourier transform
We present a machine-learning-based method for single-shot imaging through scattering media. The inverse scattering process was calculated based on a nonlinear regression algorithm by learning a number of training object-speckle pairs. In the experimental demonstration, multilayer phase objects between scattering plates were reconstructed from intensity measurements. Our approach enables model-free sensing, where it is not necessary to know the sensing processes/models.