Advanced Optical Metrology Technology

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

Deadline for manuscript submissions: 30 September 2026 | Viewed by 827

Special Issue Editors


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Guest Editor
Alcon Research Laboratories, Fort Worth, TX, USA
Interests: optical metrology; structured light; computer vision; deep learning; photo mechanics
Special Issues, Collections and Topics in MDPI journals
School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, Athens, GA, USA
Interests: 3D imaging; in situ inspection; 3D optical metrology; fringe analysis
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Engineering and Engineering Technology, University of Wisconsin–Oshkosh, Oshkosh, WI, USA
Interests: high-dimensional optical metrology; deep learning; high-speed optical metrology

Special Issue Information

Dear Colleagues,

Optical Metrology is a rapidly evolving research domain. Recent advancements have enabled nano measurements using optical methods. With the growth of artificial intelligence, the computational load of these methods has significantly decreased, leading them to be used in many in situ, real-time applications. The objective of this Special Issue of Photonics is to include the State-of-the-Art research advancements in optical methods and their applications in various domains. We cordially invite researchers to contribute their original and unique articles, as well as review articles. Topics include but are not limited to the following areas:

  1. Structured light systems;
  2. Interferometry;
  3. Phase shifting-based methods;
  4. Optical coherence tomography;
  5. Laser-based methods;
  6. Computational imaging;
  7. Microscope methods.

Dr. Vignesh Suresh
Dr. Beiwen Li
Dr. Jiaqiong Li
Guest Editors

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Keywords

  • optical metrology
  • laser scanner
  • structured light
  • computer vision
  • interferometry

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Published Papers (1 paper)

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Research

20 pages, 3318 KB  
Article
Fast Decomposition of Single Excitation–Emission Matrix Fluorescence Spectrum via Encoder–Decoder Model
by Zhenjie Zhou, Qingtao Wu and Xiaoping Wang
Photonics 2026, 13(5), 405; https://doi.org/10.3390/photonics13050405 - 22 Apr 2026
Viewed by 397
Abstract
Three–dimensional excitation–emission matrix (3D–EEM) fluorescence spectroscopy is widely applied for the rapid characterization of dissolved organic matter (DOM) in aquatic environments. However, conventional decomposition based on parallel factor analysis (PARAFAC) requires multiple spectra and manual intervention, limiting its applicability for rapid analysis and [...] Read more.
Three–dimensional excitation–emission matrix (3D–EEM) fluorescence spectroscopy is widely applied for the rapid characterization of dissolved organic matter (DOM) in aquatic environments. However, conventional decomposition based on parallel factor analysis (PARAFAC) requires multiple spectra and manual intervention, limiting its applicability for rapid analysis and future online implementation. The purpose of this study is to develop an efficient data–driven method capable of decomposing fluorescence components from a single 3D–EEM spectrum. We propose a conditional single–spectrum decomposition network (CSSD–Net) based on the encoder–decoder model. The encoder extracts fluorescence features from the input spectrum, while the decoder combines these features with conditional information on component count to generate up to five component maps. The component count can be automatically predicted by CSSD–Net or manually specified to support flexible application scenarios. CSSD–Net was trained using publicly available component spectra from the OpenFluor database without PARAFAC preprocessing. Validation on natural water samples demonstrates that the results obtained from CSSD–Net using a single sample are highly consistent with those from PARAFAC using multiple parallel samples, with a mean Tucker’s congruence coefficient (TCC) of 0.9615. These results show that CSSD–Net provides a fast and practical solution for decomposing single 3D–EEM spectra under constrained aquatic scenarios, and it has potential for future near–real–time and in situ applications. Full article
(This article belongs to the Special Issue Advanced Optical Metrology Technology)
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