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Advanced Optical Imaging and Interference Detection Techniques
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Advanced Optical Imaging and Interference Detection Techniques

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: closed (31 March 2026) | Viewed by 924

Editor

Dr. Lisong Yan

E-Mail Website
Guest Editor
School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
Interests: adaptive optics; advanced optical detection; lithography defect inspection; optical interferometry; AR/VR optics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The flexibility and freedom offered by complex curved optical components have enabled significant advancements in optical system performance and packaging. Significant progress has been made in optical design, optical testing, and optical alignment. This Special Issue explores cutting-edge developments in high-resolution optical measurement techniques, novel interference-based sensing systems, and their applications across scientific and industrial domains. We invite contributions addressing both fundamental innovations and practical implementations that push the boundaries of precision, speed, and functionality in optical technology.

We welcome contributions addressing key challenges and innovations in the following fields:

  • Computational imaging (e.g., Fourier ptychography and phase retrieval).
  • Ultrafast laser interferometry for nanoscale defect detection.
  • Adaptive optics in dynamic environments (e.g., vehicle-mounted laser radar and lithography inspection).
  • AI-driven optical system optimization and defect classification.
  • Structured light and vortex beams for 3D sensing.
  • Interferometric testing of high-order aspheric surfaces.
  • Real-time imaging with deep learning reconstruction.
  • Precise measurement in super-resolution microscopy and its unprocessed applications.

We look forward to receiving your contributions.

Dr. Lisong Yan
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly 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 2600 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 design
  • optical testing
  • interferometry
  • adaptive optics
  • laser metrology
  • phase retrieval
  • real-time measurement

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Published Papers (2 papers)

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Research

12 pages, 18917 KB  
Article
High-Speed, UV-NIR Dual-Band Photodetection via a 2H-MoSe2/Si/1T-WS2 Bipolar Heterojunction
by Zihao Wang, Meiping Tan, Lan Wang, Yan Xu and Yongqiang Yu
Sensors 2026, 26(15), 4949; https://doi.org/10.3390/s26154949 - 5 Aug 2026
Viewed by 250
Abstract
Ultraviolet (UV) and near-infrared (NIR) dual-band photodetection is critical for applications ranging from secure optical communication and environmental monitoring to biomedical imaging. However, existing dual-band systems typically rely on discrete single-band detectors combined with optical filters, leading to complex alignment and high cost. [...] Read more.
Ultraviolet (UV) and near-infrared (NIR) dual-band photodetection is critical for applications ranging from secure optical communication and environmental monitoring to biomedical imaging. However, existing dual-band systems typically rely on discrete single-band detectors combined with optical filters, leading to complex alignment and high cost. Herein, we demonstrate a bipolar heterojunction (BHJ) based on a 2H-MoSe2/Si/1T-WS2 structure for filter-free, high-speed UV-NIR dual-band photodetection. The optimized device achieves high responsivities of 0.7 A/W@365 nm and 0.8 A/W@1064 nm at bias voltage of −2 V, along with a fast response time of 1.28 μs and a −3 dB bandwidth of 70 kHz. Furthermore, in comparative evaluations with broadband Si photodiodes, the BHJ successfully enabled high-quality NIR single-pixel imaging, reconstructing high-resolution images with 128 × 128 pixels under ambient lighting conditions. This work validates the potential of such transition metal dichalcogenides-Si heterojunctions for next-generation multispectral sensing and imaging systems. Full article
(This article belongs to the Special Issue Advanced Optical Imaging and Interference Detection Techniques)
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22 pages, 39776 KB  
Article
High-Precision Depth Image Estimation for Array Gm-APD LiDAR Based on Dual-Parameter Model Feature in Dynamic Atmospheric Obscurant Environments
by Yinbo Zhang, Qingyu Hou, Haoyan Wang, Boteng Zhang, Jialong Zhou and Jianfeng Sun
Sensors 2026, 26(14), 4641; https://doi.org/10.3390/s26144641 - 22 Jul 2026
Viewed by 289
Abstract
The nonstationary distribution of dynamic atmospheric obscurants and intense backscattering interference jointly create a severely photon-starved regime, substantially degrading the depth imaging performance of array Gm-APD LiDAR in highly scattering environments. Here, we present a depth imaging estimation algorithm through dynamic atmospheric obscurants, [...] Read more.
The nonstationary distribution of dynamic atmospheric obscurants and intense backscattering interference jointly create a severely photon-starved regime, substantially degrading the depth imaging performance of array Gm-APD LiDAR in highly scattering environments. Here, we present a depth imaging estimation algorithm through dynamic atmospheric obscurants, which enables the discrimination of atmospheric obscurant interference and significantly improves depth imaging accuracy. The proposed method employs a three-step strategy comprising data preprocessing, adaptive identification of interference-source regions, and continuous multi-frame depth image fusion based on temporal correlation, thereby enabling efficient suppression of dynamic noise and improved target integrity. The proposed method is successfully demonstrated under different attenuation lengths and dynamic atmospheric obscurant conditions. Across all tested conditions, the proposed method achieves a target recovery rate (TR) ranging from 0.71 to 0.89, a root mean square error (RMSE) ranging from 35.62 to 49.20 time bins (equivalent to 5.34–7.38 m), and a structural similarity (SSIM) ranging from 0.89 to 0.94. Compared with traditional methods, the proposed method improves TR by at least 0.41 (116.2%) and SSIM by at least 0.06 (6.8%), while reducing RMSE by at least 11.03 time bins (23.6%). In particular, under the most challenging condition, with an average attenuation length of 2.43 and an occlusion ratio of 48%, the proposed algorithm achieves a TR of 0.89, an RMSE of 49.20 time bins (equivalent to 7.38 m), and an SSIM of 0.89. These results demonstrate the considerable potential of the proposed method for depth imaging in extremely strong scattering environments. Full article
(This article belongs to the Special Issue Advanced Optical Imaging and Interference Detection Techniques)
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