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Applied Sciences
Special Issues
State-of-the-Art Technology and Application of Hyperspectral Imaging
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State-of-the-Art Technology and Application of Hyperspectral Imaging

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

Deadline for manuscript submissions: closed (17 December 2021) | Viewed by 6484

Special Issue Editor

Prof. Dr. Byoung-Kwan Cho

E-Mail Website
Guest Editor
Nondestructive Bio-Sensing Laboratory, Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea
Interests: hyperspectral imaging; spectral analysis; chemometrics; nondestructive sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advancements in spectroscopy technology have led to the development of hyperspectral imaging (HSI). The main advantage of HSI over traditional techniques is that it holds a vast amount of significant information on the spectral and spatial (pixel-based) characteristics of samples. Conventional spectroscopic analytical methods (Vis/NIR, MIR, fluorescence, Raman spectroscopies, etc.) are well-established, non-invasive analytical techniques for the analysis of materials. However, these techniques are point-based scanning techniques and only examine a relatively small area of a specimen; thus, these techniques are unable to provide spatial information that is important for many material inspection applications. Sample analysis is also more convenient and comparatively fast with the help of the hyperspectral imaging technique because a large number of samples are analyzed at the same time, unlike with the single sampling technique used by other spectroscopic methods. Furthermore, HSI has instrumental flexibility and can be used to collect hyperspectral data for specimens with different sizes and shapes. With these advantages and flexibility, hyperspectral imaging has been successfully adopted in a variety of research and industry environments.

This Special Issue focuses on state-of-the-art research of hyperspectral imaging in various industrial applications. Accordingly, papers that demonstrate novel hyperspectral imaging technology concepts dealing with theoretical analyses, laboratory, and field studies in various industries, such as agriculture, remote sensing, defense, security, pharmacy, and biotechnology, etc., are welcomed.

We would like to invite you to submit original research papers and reviews for the “State-of-the-Art Technology and Application of Hyperspectral Imaging” Special issue.

Prof. Dr. Byoung-Kwan Cho
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 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. Applied Sciences 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 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

  • hyperspectral imaging
  • multispectral imaging
  • chemical imaging
  • spectral imaging
  • artificial intelligence
  • chemometric analysis
  • nondestructive measurement
  • quality evaluation

Published Papers (3 papers)

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Research

11 pages, 1823 KiB  
Article
Hyperspectral Imaging for the Detection of Bitter Almonds in Sweet Almond Batches
by Irina Torres-Rodríguez, María-Teresa Sánchez, José-Antonio Entrenas, Miguel Vega-Castellote, Ana Garrido-Varo and Dolores Pérez-Marín
Appl. Sci. 2022, 12(10), 4842; https://doi.org/10.3390/app12104842 - 11 May 2022
Cited by 1 | Viewed by 1525
Abstract
A common fraud in the sweet almond industry is the presence of bitter almonds in commercial batches. The presence of bitter almonds not only causes unpleasant flavours but also problems in the commercialisation and toxicity for consumers. Hyperspectral Imaging (HSI) has been proved [...] Read more.
A common fraud in the sweet almond industry is the presence of bitter almonds in commercial batches. The presence of bitter almonds not only causes unpleasant flavours but also problems in the commercialisation and toxicity for consumers. Hyperspectral Imaging (HSI) has been proved to be suitable for the rapid and non-destructive quality evaluation in foods as it integrates the spectral and spatial dimensions. Thus, we aimed to study the feasibility of using an HSI system to identify single bitter almond kernels in commercial sweet almond batches. For this purpose, sweet and bitter almond batches, as well as different mixtures, were analysed in bulk using an HSI system which works in the spectral range 946.6–1648.0 nm. Qualitative models were developed using Partial Least Squares-Discriminant Analysis (PLS-DA) to differentiate between sweet and bitter almonds, obtaining a classification success of over the 99%. Furthermore, data reduction, as a function of the most relevant wavelengths (VIP scores), was applied to evaluate its performance. Then, the pixel-by-pixel validation of the mixtures was carried out, identifying correctly between 61–85% of the adulterations, depending on the group of mixtures and the cultivar analysed. The results confirm that HSI, without VIP scores data reduction, can be considered a promising approach for classifying the bitterness of almonds analysed in bulk, enabling identifying individual bitter almonds inside sweet almond batches. However, a more complex mathematical analysis is necessary before its implementation in the processing lines. Full article
(This article belongs to the Special Issue State-of-the-Art Technology and Application of Hyperspectral Imaging)
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15 pages, 982 KiB  
Communication
Dual-Gratings Imaging Spectrometer
by Rui Ouyang, Duo Wang, Longxu Jin and Xingxiang Zhang
Appl. Sci. 2021, 11(22), 11048; https://doi.org/10.3390/app112211048 - 22 Nov 2021
Cited by 2 | Viewed by 2031
Abstract
Common dispersive-type spectroscopic instruments include prism-type and grating-type, usually using a single dispersive element. The continuous imaging band is always limited by the dispersion angle. When it is necessary to image two wavebands with an ultra-spectral resolution that are far apart, the imaging [...] Read more.
Common dispersive-type spectroscopic instruments include prism-type and grating-type, usually using a single dispersive element. The continuous imaging band is always limited by the dispersion angle. When it is necessary to image two wavebands with an ultra-spectral resolution that are far apart, the imaging is difficult due to the large diffraction angle. To broaden the spectral coverage of the imaging spectrometer, in this paper, we propose a dual-gratings imaging spectrometer with two independently rotating gratings. In this proposed system, two very far apart wavelength bands can be imaged in the adjacent areas by adjusting the angle of the dual gratings. This greatly expands the spectral coverage of the imaging spectrometer. Currently, the only application area considered for this instrument is solar applications. In this article, we present the optical system of the dual-gratings imaging spectrometer, illustrate several advantages of the new structure, and discuss new problems caused by the dual-gratings, which are referred to as overlap between two spectra and double image offset. We deduced the calculation process of the dual grating rotation angle, the relationship between the final acquired image and the slit, the relationship between the angle change between the dual gratings and the double image offset, and the relationship between the MTF upper limit reduction and the spatial frequency. This article also summarizes the shortcomings of this structure and studies the applicable fields under these shortcomings. At last, we simulate a dual-gratings imaging spectrometer system, compare this scheme with two traditional schemes, and conclude that this instrument has certain practical significance. Full article
(This article belongs to the Special Issue State-of-the-Art Technology and Application of Hyperspectral Imaging)
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13 pages, 31037 KiB  
Article
Quantitative Evaluation of Food-Waste Components in Organic Fertilizer Using Visible–Near-Infrared Hyperspectral Imaging
by Geonwoo Kim, Hoonsoo Lee, Byoung-Kwan Cho, Insuck Baek and Moon S. Kim
Appl. Sci. 2021, 11(17), 8201; https://doi.org/10.3390/app11178201 - 03 Sep 2021
Cited by 3 | Viewed by 2233
Abstract
Excessive addition of food waste fertilizer to organic fertilizer (OF) is forbidden in the Republic of Korea because of high sodium chloride and capsaicin concentrations in Korean food. Thus, rapid and nondestructive evaluation techniques are required. The objective of this study is to [...] Read more.
Excessive addition of food waste fertilizer to organic fertilizer (OF) is forbidden in the Republic of Korea because of high sodium chloride and capsaicin concentrations in Korean food. Thus, rapid and nondestructive evaluation techniques are required. The objective of this study is to quantitatively evaluate food-waste components (FWCs) using hyperspectral imaging (HSI) in the visible–near-infrared (Vis/NIR) region. A HSI system for evaluating fertilizer components and prediction algorithms based on partial least squares (PLS) analysis and least squares support vector machines (LS-SVM) are developed. PLS and LS-SVM preprocessing methods are employed and compared to select the optimal of two chemometrics methods. Finally, distribution maps visualized using the LS-SVM model are created to interpret the dynamic changes in the OF FWCs with increasing FWC concentration. The developed model quantitively evaluates the OF FWCs with a coefficient of determination of 0.83 between the predicted and actual values. The developed Vis/NIR HIS system and optimized model exhibit high potential for OF FWC discrimination and quantitative evaluation. Full article
(This article belongs to the Special Issue State-of-the-Art Technology and Application of Hyperspectral Imaging)
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