Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.5
1.9
Journals
Photonics
Special Issues
Advancements in Optics and Laser Measurement
share announcement

Advancements in Optics and Laser Measurement

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Lasers, Light Sources and Sensors".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 1251

Special Issue Editors

Dr. Hongru Li

E-Mail Website
Guest Editor
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China
Interests: fringe projection profilometry; laser interferometry measurement; computational imaging; optical metrology; machine vision
Dr. Shutong Wang

E-Mail Website
Guest Editor
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China
Interests: laser micro machining; machine vision; laser interferometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of optics and laser measurement has seen remarkable advancements in recent years, with new methodologies, innovative technologies, and applications emerging across various industries. This Special Issue aims to showcase the latest research developments in the area of optics and laser measurement techniques, particularly those that push the boundaries of precision, efficiency, and versatility.

We invite researchers and practitioners to submit high-quality papers that highlight recent works in optical sensing technologies, laser-based measurement systems, and their applications in fields such as manufacturing, metrology, biomedical imaging, environmental monitoring, and more. Topics of interest include, but are not limited to:

  • Novel laser measurement techniques and systems
  • Advances in optical interferometry and metrology
  • High-resolution 3D surface measurement and profiling
  • Laser-based imaging systems and optical sensing technologies
  • Non-contact measurement technologies in industrial and medical fields
  • Laser scanning and 3D reconstruction techniques
  • Development of compact and portable laser measurement devices
  • Integration of optics and laser systems with AI and machine learning
  • Advances in optical and laser systems for environmental monitoring
  • Calibration and standards for laser and optical measurement systems

We welcome original research articles and comprehensive review papers that provide insights into the latest advancements and future directions in the field.

Dr. Hongru Li
Dr. Shutong Wang
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.

Keywords

  • optical sensing technologies
  • optical interferometry
  • 3D surface profiling
  • laser imaging
  • laser scanning and reconstruction
  • non-contact measurement
  • high-precision metrology
  • machine learning in optical measurement

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

22 pages, 9617 KB  
Article
An Improved PCA and Jacobian-Enhanced Whale Optimization Collaborative Method for Point Cloud Registration
by Haiman Chu, Jingjing Fan, Zai Luo, Yinbao Cheng, Yingqi Tang and Yaru Li
Photonics 2025, 12(8), 823; https://doi.org/10.3390/photonics12080823 - 19 Aug 2025
Viewed by 382
Abstract
Scanned data often contain substantial outliers due to environmental interference, which drastically decreases the performance of traditional registration algorithms. To address this issue, this article proposes an improved principal component analysis (PCA) and Jacobian-enhanced whale optimization collaborative method for point cloud registration. First, [...] Read more.
Scanned data often contain substantial outliers due to environmental interference, which drastically decreases the performance of traditional registration algorithms. To address this issue, this article proposes an improved principal component analysis (PCA) and Jacobian-enhanced whale optimization collaborative method for point cloud registration. First, an improved PCA point cloud initial registration algorithm is proposed by introducing the normal vector local information to set the screening conditions. This algorithm can streamline the original set of 48 candidate rotation matrices down to 4, achieving rapid point cloud registration at the data level between the scanned and model point clouds. Second, a Jacobian whale optimization algorithm for fine registration (JWOA-FR) is proposed by incorporating local gradient information. The algorithm employs gradient descent on optimal whale individuals to dynamically guide global search updates, thereby enhancing both registration accuracy and efficiency. Finally, a threshold is set to remove the outliers contained in the workpieces based on the information of the matched point pairs. The iterative closest point (ICP) algorithm is further used to improve registration accuracy for data without outliers. The experimental results showed that registration errors of large workpieces 1, 2, and 3 were 2.0755 mm, 2.3955 mm, and 2.5823 mm, respectively, after outlier removal, which indicates that the proposed method is applicable to data with outliers, and the registration accuracy meets the requirements. Full article
(This article belongs to the Special Issue Advancements in Optics and Laser Measurement)
►▼ Show Figures

Figure 1

18 pages, 4411 KB  
Article
Research on Enhancing Target Recognition Rate Based on Orbital Angular Momentum Spectrum with Assistance of Neural Network
by Guanxu Chen, Hongyang Wang, Hao Yun, Zhanpeng Shi, Zijing Zhang, Chengshuai Cui, Di Wu, Xinran Lyu and Yuan Zhao
Photonics 2025, 12(8), 771; https://doi.org/10.3390/photonics12080771 - 30 Jul 2025
Viewed by 609
Abstract
In this paper, the single-mode vortex beam is used to illuminate targets of different shapes, and the targets are recognized using machine learning algorithms based on the orbital angular momentum (OAM) spectral information of the echo signal. We innovatively utilize three neural networks—multilayer [...] Read more.
In this paper, the single-mode vortex beam is used to illuminate targets of different shapes, and the targets are recognized using machine learning algorithms based on the orbital angular momentum (OAM) spectral information of the echo signal. We innovatively utilize three neural networks—multilayer perceptron (MLP), convolutional neural network (CNN) and residual neural network (ResNet)—to train extensive echo OAM spectrum data. The trained models can rapidly and accurately classify the OAM spectrum data of different targets’ echo signals. The results show that the residual network (ResNet) performs best under all turbulence intensities and can achieve a high recognition rate when Cn2=1×10−13 m−2/3. In addition, even when the target size is η=0.3, the recognition rate of ResNet can reach 97%, while the robustness of MLP and CNN to the target size is lower; the recognition rates are 91.75% and 91%, respectively. However, although the recognition performance of CNN and MLP is slightly lower than that of ResNet, their training time is much lower than that of ResNet, which can achieve a good balance between recognition performance and training time cost. This research has a promising future in the fields of target recognition and intelligent navigation based on multi-dimensional information. Full article
(This article belongs to the Special Issue Advancements in Optics and Laser Measurement)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop