Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Non-Linear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks – Concepts and Review of Research

Daniel Smith
,
Shivasubramanian Gopinath
,
Francis Gracy Arockiaraj
,
Andra Naresh Kumar Reddy
ORCID logo ,
Vinoth Balasubramani
,
Ravi Kumar
ORCID logo ,
Nitin Dubey
,
Soon Hock Ng
ORCID logo ,
Tomas Katkus
,
Shakina Jothi Selva
,
Dhanalakshmi Renganathan
,
Beaula Ruby Kamalam Manueldoss
,
Aravind Simon John Francis Rajeswary
,
Srinivasan Navaneethakrishnan
,
Stephen Rajkumar Inbanathan
,
Sandhra-Mirella Valdma
,
Praveen Periyasamy Angamuthu
,
Amudhavel Jayavel
,
Manoj Kumar
ORCID logo ,
Rashid A Ganeev
,
Pierre J Magistretti
,
Christian Depeursinge
,
Saulius Juodkazis
,
Joseph Rosen
ORCID logo ,
Vijayakumar Anand
*
Version 1 : Received: 28 May 2022 / Approved: 30 May 2022 / Online: 30 May 2022 (11:37:04 CEST)

A peer-reviewed article of this Preprint also exists.

Smith, D.; Gopinath, S.; Arockiaraj, F.G.; Reddy, A.N.K.; Balasubramani, V.; Kumar, R.; Dubey, N.; Ng, S.H.; Katkus, T.; Selva, S.J.; Renganathan, D.; Kamalam, M.B.R.; John Francis Rajeswary, A.S.; Navaneethakrishnan, S.; Inbanathan, S.R.; Valdma, S.-M.; Praveen, P.A.; Amudhavel, J.; Kumar, M.; Ganeev, R.A.; Magistretti, P.J.; Depeursinge, C.; Juodkazis, S.; Rosen, J.; Anand, V. Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks—Concepts and Review of Research. J. Imaging 2022, 8, 174. Smith, D.; Gopinath, S.; Arockiaraj, F.G.; Reddy, A.N.K.; Balasubramani, V.; Kumar, R.; Dubey, N.; Ng, S.H.; Katkus, T.; Selva, S.J.; Renganathan, D.; Kamalam, M.B.R.; John Francis Rajeswary, A.S.; Navaneethakrishnan, S.; Inbanathan, S.R.; Valdma, S.-M.; Praveen, P.A.; Amudhavel, J.; Kumar, M.; Ganeev, R.A.; Magistretti, P.J.; Depeursinge, C.; Juodkazis, S.; Rosen, J.; Anand, V. Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks—Concepts and Review of Research. J. Imaging 2022, 8, 174.

Abstract

Indirect imaging methods involve at least two steps, namely optical recording, and computational reconstruction. The optical recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical modulation functions and reconstruction methods developed in the past years for different applications. In most cases, a compatible pair of optical modulation function and reconstruction method gives optimal performance. A new reconstruction method termed non-linear reconstruction (NLR) was developed in 2017 to reconstruct the object image in the case of optical scattering modulators. During the years, it was revealed that the NLR could reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR has been investigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Keywords

Holography; computational imaging; non-linear reconstruction; Fresnel incoherent correlation holography; coded aperture imaging; rotating point spread function; diffractive optics; scattering.

Subject

Physical Sciences, Optics and Photonics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.