Advanced Spectral Imaging Technology

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 1180

Special Issue Editor

Key Laboratory of Precision Opto-Mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China
Interests: hyperspectral imaging; light field imaging; remote sensing image processing

Special Issue Information

Dear Colleagues,

The spectral imaging technology acquires 2D spatial and 1D spectral information of interested scenes. The enormous spatial and spectral features abstracted from a spectral datacube can be applied for target detection, resources remote sensing, medical diagnosis, and military reconnaissance. Various spectral imaging systems have been proposed along with detail-correlated component design, calibration, and data-processing methods.

Benefiting from the development and advancement of high-precision fabrication techniques, computational techniques, and other technologies, a variety of spectral imaging systems have emerged. Each of these systems has its unique design and data-mapping techniques, but they all have the same goal, which is to obtain a 3D spatial–spectral datacube. Furthermore, the key components, data reconstruction, and applications have also evolved with techniques.

This Special Issue aims to gather the latest research related to advances in spectral imaging technology. Both original research articles with innovative ideas and review articles discussing the state of the art are welcomed. Specific topics of interest include, but are not limited to, the following:

  • Novel spectral imaging principle;
  • Design and development of key components;
  • System calibration methods;
  • Data-processing methods;
  • Application of spectral imaging systems.

Dr. Lijuan Su
Guest Editor

Manuscript Submission Information

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Keywords

  • system design
  • key component
  • calibration
  • data processing
  • application

Published Papers (1 paper)

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Research

18 pages, 6398 KiB  
Article
Reconstruction Algorithm Optimization Based on Multi-Iteration Adaptive Regularity for Laser Absorption Spectroscopy Tomography
by Rong Zhao, Cheng Du, Jianyong Zhang, Ruixue Cheng, Zhongqiang Yu and Bin Zhou
Appl. Sci. 2023, 13(21), 12083; https://doi.org/10.3390/app132112083 - 06 Nov 2023
Viewed by 855
Abstract
Laser absorption spectroscopy tomography is an effective combustion diagnostic method for obtaining simultaneous two-dimensional distribution measurements of temperature and gas molar concentrations. For the reconstruction process of complex combustion flames, a new algorithm named ‘multi-iterative adaptive optimization regularization’ (MIARO) is proposed. This algorithm [...] Read more.
Laser absorption spectroscopy tomography is an effective combustion diagnostic method for obtaining simultaneous two-dimensional distribution measurements of temperature and gas molar concentrations. For the reconstruction process of complex combustion flames, a new algorithm named ‘multi-iterative adaptive optimization regularization’ (MIARO) is proposed. This algorithm is a further development of another algorithm known as the ‘modified adaptive algebraic reconstruction technique’ (MAART) with the improvement of the initial value and adaptive regularization parameter selections. In MIARO, the problem of the MAART’s initial value sensitivity is compensated for, and in addition, reconstruction parameters are also introduced into the regularization so that both the quality of reconstruction and the convergence of regularization are guaranteed. In butane burner experiments, an average relative error of 1.82% was achieved with MIARO, compared to 2.44% with MAART, which is a significant reduction of 25.1%. The simulation and experimental results clearly demonstrate that the MIARO algorithm can be used to reconstruct dynamic combustion fields and eliminate boundary artifacts with improved measurement accuracy and robustness. Full article
(This article belongs to the Special Issue Advanced Spectral Imaging Technology)
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