Ghost imaging based on Y-net: a dynamic coding and decoding approach

Optics Express
Ruiguo ZhuJian Wang

Abstract

Ghost imaging incorporating deep learning technology has recently attracted much attention in the optical imaging field. However, deterministic illumination and multiple exposure are still essential in most scenarios. Here we propose a ghost imaging scheme based on a novel dynamic decoding deep learning framework (Y-net), which works well under both deterministic and indeterministic illumination. Benefited from the end-to-end characteristic of our network, the image of a sample can be achieved directly from the data collected by the detector. The sample is illuminated only once in the experiment, and the spatial distribution of the speckle encoding the sample in the experiment can be completely different from that of the simulation speckle in training, as long as the statistical characteristics of the speckle remain unchanged. This approach is particularly important to high-resolution x-ray ghost imaging applications due to its potential for improving image quality and reducing radiation damage.

References

Nov 14, 1988·Physical Review Letters·I FreundS Feng
Apr 20, 2004·Physical Review Letters·Jing Cheng, Shensheng Han
Sep 21, 2004·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhou WangEero P Simoncelli
Apr 12, 2006·Physical Review Letters·Giuliano ScarcelliYanhua Shih
Aug 1, 1982·Applied Optics·J R Fienup
May 9, 2012·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Baris I Erkmen
Dec 4, 2012·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Vladimir Katkovnik, Jaakko Astola
Mar 12, 2013·Physical Review Letters·M BinaF Ferri
May 21, 2013·Science·B SunM J Padgett
Jun 16, 2015·Optics Express·Hong YuShensheng Han
May 18, 2016·Scientific Reports·Zhentao LiuShensheng Han
Jul 15, 2016·Optics Express·Ryoichi HorisakiJun Tanida
Sep 24, 2016·Physical Review Letters·Hong YuDaming Zhu
Sep 24, 2016·Physical Review Letters·Daniele PellicciaDavid M Paganin
Dec 3, 2016·Nature·R I KhakimovA G Truscott
Jun 28, 2017·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Miles J Padgett, Robert W Boyd
Dec 21, 2017·Scientific Reports·Meng LyuGuohai Situ
Mar 24, 2018·Scientific Reports·Xialin LiuGuihua Zeng
Jun 6, 2018·IEEE Transactions on Medical Imaging·Tran Minh QuanWon-Ki Jeong
Jun 8, 2018·Optics Express·Yu SunUlugbek S Kamilov
Sep 29, 2018·Physical Review Letters·S LiD Ratner
Nov 25, 2018·Optics Express·Thanh NguyenGeorge Nehmetallah
Jan 5, 2019·Physical Review Letters·Alexandre GoyGeorge Barbastathis
Mar 7, 2019·Light, Science & Applications·Yair RivensonAydogan Ozcan
Nov 7, 2019·Optics Express·Chenyu HuShensheng Han
Dec 28, 2019·Optics Express·Lei SunGuihua Zeng

❮ Previous
Next ❯

Citations


❮ Previous
Next ❯

Related Concepts

Related Feeds

Cell Imaging in CNS

Here is the latest research on cell imaging and imaging modalities, including light-sheet microscopy, in the central nervous system.

Related Papers

Optics Express
Xiao ZhangPing Xue
Bulletin of the New York Academy of Medicine
M K Holmes
© 2021 Meta ULC. All rights reserved