Hyperspectral and multispectral imaging: setting the scene

Amigo, José Manuel

doi:10.1016/b978-0-444-63977-6.00001-8

Cited by 50 publications

(34 citation statements)

References 28 publications

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“…All the above-mentioned techniques can be coupled with imaging or microscopic devices in order to provide hyperspectral images [66]. The use of hyperspectral imaging, i.e., the possibility of recording images in which a whole spectrum is acquired for each pixel, allows obtaining at the same time the spatial and spectral characterization of the samples under investigation.…”

Section: Short Description Of Spectroscopic Techniquesmentioning

confidence: 99%

Application of Novel Techniques for Monitoring Quality Changes in Meat and Fish Products during Traditional Processing Processes: Reconciling Novelty and Tradition

et al. 2020

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In this review, we summarize the most recent advances in monitoring changes induced in fish and other seafood, and meat and meat products, following the application of traditional processing processes by means of conventional and emerging advanced techniques. Selected examples from the literature covering relevant applications of spectroscopic methods (i.e., visible and near infrared (VIS/NIR), mid-infrared (MIR), Raman, nuclear magnetic resonance (NMR), and fluorescence) will be used to illustrate the topics covered in this review. Although a general reluctance toward using and adopting new technologies in traditional production sectors causes a relatively low interest in spectroscopic techniques, the recently published studies have pointed out that these techniques could be a powerful tool for the non-destructive monitoring and process optimization during the production of muscle food products.

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Section: Short Description Of Spectroscopic Techniquesmentioning

confidence: 99%

Application of Novel Techniques for Monitoring Quality Changes in Meat and Fish Products during Traditional Processing Processes: Reconciling Novelty and Tradition

et al. 2020

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“…Hyperspectral imaging instruments can measure signals from the various regions of the electromagnetic spectrum including but not limited to the visible (VIS), near infrared (NIR), and mid infrared (MIR). Some other hyperspectral imaging instrumentations of increasing attention are the confocal laser microscopy scanners, Raman spectroscopy, Terahertz spectroscopy, X-ray spectroscopy, magnetic resonance imaging, and 3D ultrasound imaging [ 56 ]. Generally, a hyperspectral system comprises of a light source, a wavelength dispersion device, and an area detector.…”

Section: Hyperspectral Imaging Technology and Instrumentationmentioning

confidence: 99%

“…A hyperspectral image is usually displayed as a hypercube in three dimensions including two spatial (X, Y) and one spectral (λ) dimension. This hypercube structure contains chemical information related to the target of interest [ 56 , 73 ].…”

Section: Hyperspectral Imaging Technology and Instrumentationmentioning

confidence: 99%

Non-Destructive Assessment of Chicken Egg Fertility

Adegbenjo

Liu

Ngadi

2020

Sensors

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Total hatching egg set (for both egg production chicks and broilers) in the Agriculture and Agri-Food Canada report 2017 was over 1.0 billion. With the fertility rate for this year observed to be around 82%, there were about 180 million unhatched eggs (worth over 300 million Canadian dollars) incubated in Canada for the year 2017 alone. These non-hatching (non-fertile) eggs can find useful applications as commercial table eggs or low-grade food stock if they can be detected early and isolated accordingly preferably prior to incubation. The conventional method of chicken egg fertility assessment termed candling, is subjective, cumbersome, slow, and eventually inefficient, leading to huge economic losses. Hence, there is a need for a non-destructive, fast and online prediction technology to assist with early chicken egg fertility identification problem. This paper reviewed existing non-destructive approaches including ultrasound and dielectric measurements, thermal imaging, machine vision, spectroscopy, and hyperspectral imaging. Hyperspectral imaging was extensively discussed, being an emerging new technology with great potential. Suggestions were finally proffered towards building futuristic robust model(s) for early detection of chicken egg fertility.

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“…In this way, spatial and chemical information about the samples is provided and limitations linked to traditional single point spectroscopic techniques, such as the lack of spatial information, are clearly overcome. Nowadays, imaging platforms offer a wealth of spatial resolution scales and are adapted to the specificities of many spectroscopic (and spectrometric) modalities 1,2 . Despite the clear value of the complementary information provided by the currently available imaging platforms, image fusion is still a challenge that does not have a generalized solution 3 .…”

Section: Introductionmentioning

confidence: 99%

Fusion of Hyperspectral Images. Looking at the structure of vegetal tissues: a case study.

Gómez-Sánchez¹,

Marro²,

Marsal³

et al. 2021

Preprint

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Hyperspectral imaging (HSI) is a useful non-invasive technique that offers spatial and chemical information of samples. Often, different HSI techniques are used to obtain complementary information from the sample by combining different image modalities (Image Fusion). However, issues related to the different spatial resolution, sample orientation or area scanned among platforms need to be properly addressed. Unmixing methods are helpful to analyze and interpret the information of HSI related to each of the components contributing to the signal. Among those, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) offers very suitable features for image fusion, since it can easily cope with multiset structures formed by blocks of images coming from different samples and platforms and allows the use of optional and diverse constraints to adapt to the specific features of each HSI employed. In this work, a case study based on the investigation of cross-sections from rice leaves by Raman, synchrotron infrared and fluorescence imaging techniques is presented. HSI of these three different techniques are fused for the first time in a single data structure and analyzed by MCR-ALS. This example is challenging in nature and allows describing clearly the necessary steps required to perform unmixing in an image fusion context.

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Hyperspectral and multispectral imaging: setting the scene

Cited by 50 publications

References 28 publications

Application of Novel Techniques for Monitoring Quality Changes in Meat and Fish Products during Traditional Processing Processes: Reconciling Novelty and Tradition

Application of Novel Techniques for Monitoring Quality Changes in Meat and Fish Products during Traditional Processing Processes: Reconciling Novelty and Tradition

Non-Destructive Assessment of Chicken Egg Fertility

Fusion of Hyperspectral Images. Looking at the structure of vegetal tissues: a case study.

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