Open AccessMask-modulated lensless imaging via translated structured illumination
Author(s) -
LU Chang-chun,
You Zhou,
Yanxun Guo,
Shaowei Jiang,
Zibang Zhang,
Guoan Zheng,
Jingang Zhong
Publication year - 2021
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.421228
Subject(s) - phase retrieval , computer science , optics , computer vision , iterative reconstruction , artificial intelligence , image quality , image sensor , image resolution , image formation , physics , image (mathematics) , fourier transform , quantum mechanics
Lensless microscopy technique enables high-resolution image recovery over a large field of view. By integrating the concept of phase retrieval, it can also retrieve the lost phase information from intensity-only measurements. Here we report a mask-modulated lensless imaging platform based on translated structured illumination. In the reported platform, we sandwich the object in-between a coded mask and a naked image sensor for lensless data acquisition. An LED array is used to provide angle-varied illumination for projecting a translated structured pattern without involving mechanical scanning. For different LED elements, we acquire the lensless intensity data for recovering the complex-valued object. In the reconstruction process, we employ the regularized ptychographic iterative engine and implement an up-sampling process in the reciprocal space. As demonstrated by experimental results, the reported platform is able to recover complex-valued object images with higher resolution and better quality than previous implementations. Our approach may provide a cost-effective solution for high-resolution and wide field-of-view ptychographic imaging without involving mechanical scanning.