Open AccessSingle-shot multi-view imaging enabled by scattering lens
Author(s) -
Xiaogang Zhu,
Sujit Kumar Sahoo,
Dong Wang,
Huy Quoc Lam,
Phil Surman,
Dayan Li,
Cuong Dang
Publication year - 2019
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.27.037164
Subject(s) - optics , computer vision , computer science , artificial intelligence , speckle pattern , point spread function , deconvolution , ghost imaging , integral imaging , imaging science , iterative reconstruction , scattering , projection (relational algebra) , physics , image (mathematics) , algorithm
Imaging three-dimensional (3D) objects has been realized by methods such as binocular stereo vision and multi-view imaging. These methods, however, needs multiple cameras or multiple shots to get elemental images. In this paper, we develop a single-shot multi-view imaging technique by utilizing the natural randomness of scattering media. By exploiting the memory effect and uncorrelated point spread functions (PSF) among scattering media, we demonstrate that both stereo imaging with large disparity and up to seven-view imaging of a 3D object can be reconstructed from only one speckle pattern by deconvolution. The elemental images are consistent with 3D object projection and images taken by multi-shot imaging. Our technique provides a feasible method to capture multi-view imaging with short acquisition time and easy calibration.