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

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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Evaluating the Persistence of Post-Wildfire Ash: A Multi-Platform Spatiotemporal Analysis

Fire ◽

10.3390/fire4040068 ◽

2021 ◽

Vol 4 (4) ◽

pp. 68

Author(s):

Sarah A. Lewis ◽

Peter R. Robichaud ◽

Andrew T. Hudak ◽

Eva K. Strand ◽

Jan U. H. Eitel ◽

...

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Field Measurements ◽

Cost Effective ◽

Spatiotemporal Analysis ◽

Short Wave ◽

Hydrologic Model ◽

Landsat 8 ◽

Data Volume ◽

Sentinel 2

As wildland fires amplify in size in many regions in the western USA, land and water managers are increasingly concerned about the deleterious effects on drinking water supplies. Consequences of severe wildfires include disturbed soils and areas of thick ash cover, which raises the concern of the risk of water contamination via ash. The persistence of ash cover and depth were monitored for up to 90 days post-fire at nearly 100 plots distributed between two wildfires in Idaho and Washington, USA. Our goal was to determine the most ‘cost’ effective, operational method of mapping post-wildfire ash cover in terms of financial, data volume, time, and processing costs. Field measurements were coupled with multi-platform satellite and aerial imagery collected during the same time span. The image types spanned the spatial resolution of 30 m to sub-meter (Landsat-8, Sentinel-2, WorldView-2, and a drone), while the spectral resolution spanned visible through SWIR (short-wave infrared) bands, and they were all collected at various time scales. We that found several common vegetation and post-fire spectral indices were correlated with ash cover (r = 0.6–0.85); however, the blue normalized difference vegetation index (BNDVI) with monthly Sentinel-2 imagery was especially well-suited for monitoring the change in ash cover during its ephemeral period. A map of the ash cover can be used to estimate the ash load, which can then be used as an input into a hydrologic model predicting ash transport and fate, helping to ultimately improve our ability to predict impacts on downstream water resources.

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Development of a hyperspectral imaging technique with internal scene scan for analysing the chemistry of food degradation

Journal of Spectral Imaging ◽

10.1255/jsi.2018.a12 ◽

2018 ◽

Author(s):

Guo Chen ◽

Jung Huang

Keyword(s):

Hyperspectral Imaging ◽

Food Quality ◽

Biomedical Applications ◽

Imaging Technique ◽

Cost Effective ◽

Field Of View ◽

Oxidation Processes ◽

Food Quality Control ◽

Light Region ◽

Food Quality And Safety

Hyperspectral imaging (HSI) can provide valuable information about the spatial distribution of ingredients in an object, therefore the technique has been widely adopted in numerous applications, ranging from remote sensing and land planning, food quality control, to biomedical applications. However, HSI instruments are expensive, which has limited the technique to some high-end applications. In this study, we developed a cost-effective HSI technique with an internal scene-scan mechanism, which enables rapid acquisitions of a scene without moving the instrument or the tested object. The apparatus was characterised, revealing an imaging resolution of 0.4 mm in a field of view (FoV) of 10 cm and a spectral resolution of 1.3 nm in the 40–800 nm visible light region. We succeeded in applying our apparatus to analyse the oxidation processes of apple and meat, which demonstrated our design and relevant data analysis to be of high value to visualise chemistry related to food quality and safety.

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Standardization of Image Quality Analysis – ISO 19264

Archiving Conference ◽

10.2352/issn.2168-3204.2016.1.0.111 ◽

2016 ◽

Vol 2016 (1) ◽

pp. 111-116 ◽

Cited By ~ 2

Author(s):

Dietmar Wueller ◽

Ulla Bøgvad Kejser

Keyword(s):

Image Quality ◽

Quality Analysis ◽

Image Quality Analysis

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Image Quality Analysis of X-ray Grating Interferometer Using Integrating-bucket Method

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2020.64.2.020503 ◽

2020 ◽

Vol 64 (2) ◽

pp. 20503-1-20503-5

Author(s):

Faiz Wali ◽

Shenghao Wang ◽

Ji Li ◽

Jianheng Huang ◽

Yaohu Lei ◽

...

Keyword(s):

Image Quality ◽

Phase Contrast ◽

Quality Analysis ◽

Phase Contrast Imaging ◽

Phase Image ◽

Contrast Imaging ◽

High Quality ◽

Image Quality Analysis ◽

X Ray ◽

Grating Interferometer

Abstract Grating-based x-ray phase-contrast imaging has the potential to enhance image quality and provide inner structure details non-destructively. In this work, using grating-based x-ray phase-contrast imaging system and employing integrating-bucket method, the quantitative expressions of signal-to-noise ratios due to photon statistics and mechanical error are analyzed in detail. Photon statistical noise and mechanical error are the main sources affecting the image noise in x-ray grating interferometry. Integrating-bucket method is a new phase extraction method translated to x-ray grating interferometry; hence, its image quality analysis would be of great importance to get high-quality phase image. The authors’ conclusions provide an alternate method to get high-quality refraction signal using grating interferometer, and hence increases applicability of grating interferometry in preclinical and clinical usage.

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Review on Methodologies Used in the Synthesis of Metal Nanoparticles: Significance of Phytosynthesis Using Plant Extract as an Emerging Tool

Current Pharmaceutical Design ◽

10.2174/1381612826666200531150218 ◽

2020 ◽

Vol 26 (40) ◽

pp. 5188-5204

Author(s):

Uzair Nagra ◽

Maryam Shabbir ◽

Muhammad Zaman ◽

Asif Mahmood ◽

Kashif Barkat

Keyword(s):

Green Synthesis ◽

Metal Nanoparticles ◽

Plant Extracts ◽

Biomedical Applications ◽

Noble Metals ◽

Cost Effective ◽

Green Technology ◽

Critical Parameters ◽

Nanosized Particles ◽

Preparation Methods

Nanosized particles, with a size of less than 100 nm, have a wide variety of applications in various fields of nanotechnology and biotechnology, especially in the pharmaceutical industry. Metal nanoparticles [MNPs] have been synthesized by different chemical and physical procedures. Still, the biological approach or green synthesis [phytosynthesis] is considered as a preferred method due to eco-friendliness, nontoxicity, and cost-effective production. Various plants and plant extracts have been used for the green synthesis of MNPs, including biofabrication of noble metals, metal oxides, and bimetallic combinations. Biomolecules and metabolites present in plant extracts cause the reduction of metal ions into nanosized particles by one-step preparation methods. MNPs have remarkable attractiveness in biomedical applications for their use as potential antioxidant, anticancer and antibacterial agents. The present review offers a comprehensive aspect of MNPs production via top-to-bottom and bottom-to-top approach with considerable emphasis on green technology and their possible biomedical applications. The critical parameters governing the MNPs formation by plant-based synthesis are also highlighted in this review.

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ASSESSING POTENTIAL ENVIRONMENTAL HAZARDS ASSOCIATED WITH MINERALIZED AREAS IN WESTERN INDIA USING AVIRIS-NG HYPERSPECTRAL IMAGING DATA

10.1130/abs/2019am-339640 ◽

2019 ◽

Author(s):

William H. Farrand ◽

Keyword(s):

Hyperspectral Imaging ◽

Environmental Hazards ◽

Western India ◽

Imaging Data

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The image quality analysis of neutron digital radiography through the variation of multiple image capturing

10.1063/1.5054544 ◽

2018 ◽

Author(s):

Ayu Fitri Amalia ◽

Widodo Budhi ◽

Urip Nurwijayanto Prabowo ◽

Gede Bayu Suparta

Keyword(s):

Image Quality ◽

Digital Radiography ◽

Quality Analysis ◽

Image Quality Analysis ◽

Multiple Image ◽

Image Capturing

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A cost-effective algae-based biosensor for water quality analysis: Development and testing in collaboration with peasant communities

Environmental Technology & Innovation ◽

10.1016/j.eti.2021.101479 ◽

2021 ◽

pp. 101479

Author(s):

Cecilia Prudkin-Silva ◽

Esteban Lanzarotti ◽

Lucía Álvarez ◽

María Belén Vallerga ◽

Matías Factorovich ◽

...

Keyword(s):

Water Quality ◽

Cost Effective ◽

Quality Analysis ◽

Water Quality Analysis ◽

Peasant Communities

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Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

Remote Sensing ◽

10.3390/rs13081562 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1562

Author(s):

Xiangyu Ge ◽

Jianli Ding ◽

Xiuliang Jin ◽

Jingzhe Wang ◽

Xiangyue Chen ◽

...

Keyword(s):

Data Mining ◽

Soil Moisture ◽

Moisture Content ◽

Hyperspectral Imaging ◽

Fractional Order ◽

Arid Regions ◽

Soil Moisture Content ◽

Order Derivative ◽

Imaging Data ◽

Strategy I

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.

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