Polarimetric hyperspectral imaging with acousto-optic tunable filter in the visible to shortwave infrared range

2018 ◽  
Author(s):  
Emir Y. Haskovic ◽  
Sudhir Trivedi ◽  
Jolanta Soos ◽  
Narasimha S. Prasad ◽  
Susan Kutcher ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Tunable Filter ◽  
Infrared Range ◽  
Shortwave Infrared

scholarly journals Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 407
Author(s):  
Thomas De Kerf ◽  
Georgios Pipintakos ◽  
Zohreh Zahiri ◽  
Steve Vanlanduit ◽  
Paul Scheunders
Keyword(s):  
Hyperspectral Imaging ◽  
Cross Correlation ◽  
Salt Spray ◽  
Ground Truth ◽  
Infrared Range ◽  
Neutral Salt ◽  
Correlation Algorithm ◽  
Infrared Spectrometer ◽  
Shortwave Infrared ◽  
Hyperspectral Camera

In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900–1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time.

scholarly journals Identification of peat type and humification by laboratory VNIR/SWIR hyperspectral imaging of peat profiles with focus on fen-bog transition in aapa mires

2020 ◽  
Author(s):  
L. Granlund ◽  
M. Keinänen ◽  
T. Tahvanainen
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Support Vector ◽  
High Resolution Imaging ◽  
Factors Affecting ◽  
Vector Machines ◽  
Resolution Imaging ◽  
Shortwave Infrared ◽  
Type Classification ◽  
Wide Potential

Abstract Aims Hyperspectral imaging (HSI) has high potential for analysing peat cores, but methodologies are deficient. We aimed for robust peat type classification and humification estimation. We also explored other factors affecting peat spectral properties. Methods We used two laboratory setups: VNIR (visible to near-infrared) and SWIR (shortwave infrared) for high resolution imaging of intact peat profiles with fen-bog transitions. Peat types were classified with support vector machines, indices were developed for von Post estimation, and K-means clustering was used to analyse stratigraphic patterns in peat quality. With separate experiments, we studied spectral effects of drying and oxidation. Results Despite major effects, oxidation and water content did not impede robust HSI classification. The accuracy between Carex peat and Sphagnum peat in validation was 80% with VNIR and 81% with SWIR data. The spectral humification indices had accuracies of 82% with VNIR and 56%. Stratigraphic HSI patterns revealed that 36% of peat layer shifts were inclined by over 20 degrees. Spectral indices were used to extrapolate visualisations of element concentrations. Conclusions HSI provided reliable information of basic peat quality and was useful in visual mapping, that can guide sampling for other analyses. HSI can manage large amounts of samples to widen the scope of detailed analysis beyond single profiles and it has wide potential in peat research beyond the exploratory scope of this paper. We were able to confirm the capacity of HSI to reveal shifts of peat quality, connected to ecosystem-scale change.

3D Plant Modelling Using Spectral Data from Visible to Near Infrared Range

2015 ◽  
pp. 273-294
Author(s):  
Ali Zia ◽  
Jie Liang
Keyword(s):  
Hyperspectral Imaging ◽  
Material Properties ◽  
Near Infrared ◽  
Infrared Range ◽  
Plant Surface ◽  
Imaging Device ◽  
Plant Phenomics ◽  
Physical Traits ◽  
Plant Modelling ◽  
Near Infrared Range

Plant phenomics research requires different types of sensors employed to measure the physical traits of plant surface and to estimate the biomass. Of particular interests is the hyperspectral imaging device which captures wavelength indexed band images that characterize material properties of objects under study. This chapter introduces a proof of concept research that builds 3D plant model directly from hyperspectral images captured in a controlled lab environment. The method presented in this chapter allows fine structural-spectral information of an object be captured and integrated into the 3D model, which can be used to support further research and applications. The hyperspectral imaging has shown clear advantages in segmenting plant from its background and is very promising in generating comprehensive 3D plant models.

Determination of the viability of retinispora (Hinoki cypress) seeds using shortwave infrared hyperspectral imaging spectroscopy

2020 ◽  
Vol 28 (2) ◽  
pp. 70-80 ◽  
Author(s):  
Perez Mukasa ◽  
Collins Wakholi ◽  
Akbar Faqeerzada Mohammad ◽  
Eunsoo Park ◽  
Jayoung Lee ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Hyperspectral Imaging ◽  
Imaging Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Successive Projections Algorithm ◽  
Hinoki Cypress ◽  
Sorting System ◽  
Shortwave Infrared ◽  
Successive Projections

The combination of hyperspectral imaging with multivariate data analysis methods has recently been applied to develop a nondestructive technique, required to determine the seed viability of artificially aged vegetable and cereal seeds. In this study, the potential of shortwave infrared hyperspectral imaging to determine the viability of naturally aged seeds was investigated and thereafter a model for online seed sorting system was developed. The hyperspectral images of 400 Hinoki cypress tree seeds were acquired, and germination tests were conducted for viability confirmation, which indicated 31.5% of the viable seeds. Partial least square discriminant analysis models with 179 variables in the wavelength region of 1000–1800 nm were developed with a maximum model accuracy of 98.4% and 93.8% in both the calibration and validation sets, respectively. The partial least square discriminant analysis beta coefficient revealed the key wavelengths to differentiate viable from nonviable seeds, determined based on the differences in the chemical compositions of the seeds, including their lipid and fatty acid contents, which may control the germination ability of the seeds. The most effective wavelengths were selected using two model-based variable selection methods (i.e., the variable importance of projection (15 variables) and the successive projections algorithm (8 variables)) to develop the model. The successive projections algorithm wavelength selection method was considered to develop a viability model, and its application to the raw data resulted in a prediction accuracy of 94.7% in the calibration set and 92.2% in the validation set. These results demonstrate the potential of shortwave infrared hyperspectral imaging spectroscopy as a powerful nondestructive method to determine the viability of Hinoki cypress seeds. This method could be applied to develop an online seed sorting system for seed companies and nurseries.

scholarly journals Ancient Greek text concealed on the back of unrolled papyrus revealed through shortwave-infrared hyperspectral imaging

2019 ◽  
Vol 5 (10) ◽  
pp. eaav8936 ◽  
Author(s):  
A. Tournié ◽  
K. Fleischer ◽  
I. Bukreeva ◽  
F. Palermo ◽  
M. Perino ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Multispectral Imaging ◽  
18Th Century ◽  
Primary Source ◽  
Greek Text ◽  
Ancient Greek ◽  
Substantial Impact ◽  
Text Reconstruction ◽  
Shortwave Infrared ◽  
The Way

Only a few Herculaneum rolls exhibit writing on their reverse side. Since unrolled papyri are permanently glued to paperboard, so far, this fact was known to us only from 18th-century drawings. The application of shortwave-infrared (SWIR; 1000-2500 nm) hyperspectral imaging (HSI) to one of them (PHerc. 1691/1021) has revealed portions of Greek text hidden on the back more than 220 years after their first discovery, making it possible to recover this primary source for the ongoing new edition of this precious book. SWIR HSI has produced better contrast and legibility even on the extensive text preserved on the front compared to former imaging of Herculaneum papyri at 950 nm (improperly called multispectral imaging), with a substantial impact on the text reconstruction. These promising results confirm the importance of advanced techniques applied to ancient carbonized papyri and open the way to a better investigation of hundreds of other such papyri.

scholarly journals Hyperspectral Imaging and Hierarchical PLS-DA Applied to Asbestos Recognition in Construction and Demolition Waste

2019 ◽  
Vol 9 (21) ◽  
pp. 4587 ◽  
Author(s):  
Giuseppe Bonifazi ◽  
Giuseppe Capobianco ◽  
Silvia Serranti
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Response ◽  
Principal Component ◽  
Short Wave ◽  
Partial Least Square ◽  
Least Square ◽  
Construction And Demolition Waste ◽  
Infrared Range ◽  
Demolition Waste ◽  
Control Approach

Asbestos-Containing Materials (ACMs) are hazardous and prohibited to be sold or used as recycled materials. In the past, asbestos was widely used, together with cement, to produce “asbestos cement-based” products. During the recycling process of Construction and Demolition waste (C&DW), ACM must be collected and deposited separately from other wastes. One of the main aims of the recycling strategies applied to C&DW was thus to identify and separate ACM from C&DW (e.g., concrete and brick). However, to obtain a correct recovery of C&DW materials, control methodologies are necessary to evaluate the quality and the presence of harmful materials, such as ACM. HyperSpectral Imaging (HSI)-based sensing devices allow performing the full detection of materials constituting demolition waste. ACMs are, in fact, characterized by a spectral response that nakes them is different from the “simple” matrix of the material/s not embedding asbestos. The described HSI quality control approach is based on the utilization of a platform working in the short-wave infrared range (1000–2500 nm). The acquired hyperspectral images were analyzed by applying different chemometric methods: Principal Component Analysis for data exploration and hierarchical Partial Least-Square-Discriminant Analysis (PLS-DA) to build classification models. Following this approach, it was possible to set up a repeatable, reliable and efficient technique able to detect ACM presence inside a C&DW flow stream. Results showed that it is possible to discriminate and identify ACM inside C&DW. The recognition is potentially automatic, non-destructive and does not need any contact with the investigated products.

scholarly journals Polarizer-Free AOTF-Based SWIR Hyperspectral Imaging for Biomedical Applications

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4439
Author(s):  
Vladislav Batshev ◽  
Alexander Machikhin ◽  
Grigoriy Martynov ◽  
Vitold Pozhar ◽  
Sergey Boritko ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Biomedical Applications ◽  
Cost Effective ◽  
Short Wave ◽  
Tunable Filter ◽  
Quality Analysis ◽  
Imaging Data ◽  
Image Quality Analysis ◽  
Data Volume ◽  
Integrate Design

Optical biomedical imaging in short wave infrared (SWIR) range within 0.9–1.7 μm is a rapidly developing technique. For this reason, there is an increasing interest in cost-effective and robust hardware for hyperspectral imaging data acquisition in this range. Tunable-filter-based solutions are of particular interest as they provide image processing flexibility and effectiveness in terms of collected data volume. Acousto-optical tunable filters (AOTFs) provide a unique set of features necessary for high-quality SWIR hyperspectral imaging. In this paper, we discuss a polarizer-free configuration of an imaging AOTF that provides a compact and easy-to-integrate design of the whole imager. We have carried out image quality analysis of this system, assembled it and validated its efficiency through multiple experiments. The developed system can be helpful in many hyperspectral applications including biomedical analyses.

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