Abstract

Fourier ptychographic microscopy (FPM) is a recently proposed computational imaging method that achieves both high resolution (HR) and wide field of view. In the conventional FPM model, the sample is assumed to be a 2D thin layer, and a series of low-resolution images at different illumination angles is used for HR image reconstruction. However, in practice, the sample complex amplitude distribution is usually mixed with some unknown background interferences. These background interferences may result from inhomogeneous media distribution or other defocusing layers, etc. The background interference will significantly degrade FPM reconstruction results, but so far it is not considered in the conventional FPM algorithm. Here, we propose a method that adaptively separates background interferences for each illumination angle. Experimental results show that the proposed method has a faster convergence speed and better reconstruction accuracy than the conventional FPM model.

© 2018 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Self-learning based Fourier ptychographic microscopy

Yongbing Zhang, Weixin Jiang, Lei Tian, Laura Waller, and Qionghai Dai
Opt. Express 23(14) 18471-18486 (2015)

Nonlinear optimization approach for Fourier ptychographic microscopy

Yongbing Zhang, Weixin Jiang, and Qionghai Dai
Opt. Express 23(26) 33822-33835 (2015)

Sampling criteria for Fourier ptychographic microscopy in object space and frequency space

Jiasong Sun, Qian Chen, Yuzhen Zhang, and Chao Zuo
Opt. Express 24(14) 15765-15781 (2016)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (6)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (1)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (12)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription