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Photonics
Special Issues
Innovations and Challenges in Polarization Imaging Detection Technology
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Innovations and Challenges in Polarization Imaging Detection Technology

A special issue of Photonics (ISSN 2304-6732).

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1264

Special Issue Editors

Prof. Dr. Qiang Fu

E-Mail Website
Guest Editor
Changchun University of Science and Technology, College of Opto-Electronic Engineering, No. 7186, Weixing Road, Chaoyang District, Changchun 130000, China
Interests: optical transmission characteristics testing; multi-dimensional optical imaging; multi-point and multi-functional space laser communication research; target polarization characteristics testing; space target polarization detection; multi-angle, multi-functional and multi-dimensional polarization imaging detection technology
Dr. Su Zhang

E-Mail Website
Guest Editor
Changchun University of Science and Technology, College of Opto-Electronic Engineering, No. 7186, Weixing Road, Chaoyang District, Changchun 130000, China
Interests: polarization detection; polarization transmission characteristics; optical information processing; polarized optical model; applied optics
Dr. Haodong Shi

E-Mail Website
Guest Editor
Changchun University of Science and Technology, College of Opto-Electronic Engineering, No. 7186, Weixing Road, Chaoyang District, Changchun 130000, China
Interests: optical system design; polarization spectrum detection; free-form imaging technology; infrared imaging technology; optical inspection technology

Special Issue Information

Dear Colleagues,

Polarization detection technology is an emerging cutting-edge technology that adds polarization information to traditional intensity imaging. It can provide two-dimensional light intensity distribution and obtain the target’s polarization information. It is important in the fields of target identification, optical remote sensing, military reconnaissance, and address exploration. Today, with the development of the polarization field, polarized three-dimensional imaging, the development and application of ultra-surface polarization devices and other technologies tend to mature, and gradually replace some of the old technology.

In order to promote this rapidly developing and important technology field, the aim of this Special Issue is to solicit manuscripts that provide effective solutions to future challenges in the field of polarized optics. Topics of interest for this Special Issue include, but are not limited, to the following:

  • Optical transmission characteristics testing;
  • Multi-dimensional optical imaging;
  • Space laser communication research;
  • Target polarization characteristics testing;
  • Space target polarization detection;
  • Analysis of target surface polarization characteristics;
  • Polarization imaging detection technology;
  • Establishment of target surface polarization characteristics models.

Prof. Dr. Qiang Fu
Dr. Su Zhang
Dr. Haodong Shi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (1 paper)

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Research

15 pages, 3310 KiB  
Article
Training a Dataset Simulated Using RGB Images for an End-to-End Event-Based DoLP Recovery Network
by Changda Yan, Xia Wang, Xin Zhang, Conghe Wang, Qiyang Sun and Yifan Zuo
Photonics 2024, 11(5), 481; https://doi.org/10.3390/photonics11050481 - 20 May 2024
Viewed by 964
Abstract
Event cameras are bio-inspired neuromorphic sensors that have emerged in recent years, with advantages such as high temporal resolutions, high dynamic ranges, low latency, and low power consumption. Event cameras can be used to build event-based imaging polarimeters, overcoming the limited frame rates [...] Read more.
Event cameras are bio-inspired neuromorphic sensors that have emerged in recent years, with advantages such as high temporal resolutions, high dynamic ranges, low latency, and low power consumption. Event cameras can be used to build event-based imaging polarimeters, overcoming the limited frame rates and low dynamic ranges of existing systems. Since events cannot provide absolute brightness intensity in different angles of polarization (AoPs), degree of linear polarization (DoLP) recovery in non-division-of-time (non-DoT) event-based imaging polarimeters is an ill-posed problem. Thus, we need a data-driven deep learning approach. Deep learning requires large amounts of data for training, and constructing a dataset for event-based non-DoT imaging polarimeters requires significant resources, scenarios, and time. We propose a method for generating datasets using simulated polarization distributions from existing red–green–blue images. Combined with event simulator V2E, the proposed method can easily construct large datasets for network training. We also propose an end-to-end event-based DoLP recovery network to solve the problem of DoLP recovery using event-based non-DoT imaging polarimeters. Finally, we construct a division-of-time event-based imaging polarimeter simulating an event-based four-channel non-DoT imaging polarimeter. Using real-world polarization events and DoLP ground truths, we demonstrate the effectiveness of the proposed simulation method and network. Full article
(This article belongs to the Special Issue Innovations and Challenges in Polarization Imaging Detection Technology)
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