Hyperspectral Imaging (HSI) Sensor

A device that uses optical absorption and emission lines to identify substances invisible to the naked eye. Applications range from surveillance to chemical analysis in laboratories, as well as soil conservation, food composition, water quality, and skin health maintenance.
Technology Readiness Level (TRL)

Technology Readiness Level (TRL)

Ready for Implementation

Technology is developed and qualified. It is readily available for implementation but the market is not entirely familiar with the technology.

Hyperspectral Imaging (HSI) Sensor

Non-invasive sensors that allow the visualization of the molecular composition of certain materials. When connected to a smartphone, it can identify variations on the surface of the matter caused by contamination or differentiation on the substance level that's invisible to the naked eye. Hyperspectral Imaging (HSI) sensors collect and process information from across the electromagnetic spectrum, obtaining the range for each pixel in the image of a scene, finding objects, identifying materials and chemical composition, identifying alterations on the surface, such as the skin, or detecting processes. It can be paired with computer vision and machine learning to produce a comprehensive analysis of the stored data.

In controlled environments, this technology provides flexible and high-performance acquisition of spectral information, producing a highly detailed overview for the customer about the targeted area. These sensors can be embedded in mobile devices and used for checking the ripeness of fruit, identifying allergen compounds in food, measuring differences or alterations on various surfaces such as the skin, or measuring the concentration and composition of surface pollutants, among others.

Currently, HSI sensors are used in various industries to record digital images remotely or locally. There is an extensive range of industrial applications, including medical diagnosis, crops mapping, the early detection of pests, forensic document examination, cultural heritage, artwork authentication, border control, and personal care. For water resource and flood management, it helps the early detection of the results of floods as well as the biochemical, hydro-physical, and biological attributes of water bodies.

Future Perspectives

At the end-consumer level, we might see the miniaturization of this technology at a lower cost, making it accessible to individuals besides national agencies or companies. In the future, after the standardization of the technology, it could be incorporated into industries requiring the processing of a large range of visual motion, including autonomous vehicles and IoT-based home systems.

With the improvement of the accuracy and resolution of the imaging sensor as well as the algorithm used for processing the images, the handheld sensor could be used for complex identifications, such as scanning and mapping the current level of the healthiness of the human skin as well as micro-changes due to the alteration of microbiome status and composition of the skin.

Image generated by Envisioning using Midjourney

Reflection spectroscopy is known as a non‐invasive technology for the evaluation of healthy and diseased human skin. Recently, for both applications, the combination of spectroscopy and imaging within one device was introduced as hyperspectral imaging. The goal of spectral imaging (SI) is to obtain the spectrum for each coordinate in the image of a scene by a single shot. Several acquisition techniques and applications of hyperspectral imaging were described.
Techniques and Applications of Hyperspectral Image Analysis gives an introduction to the field of image analysis using hyperspectral techniques, and includes definitions and instrument descriptions. Other imaging topics that are covered are segmentation, regression and classification. The book discusses how high quality images of large data files can be structured and archived. Imaging techniques also demand accurate calibration, and are covered in sections about multivariate calibration techniques. The book explains the most important instruments for hyperspectral imaging in more technical detail. A number of applications from medical and chemical imaging are presented and there is an emphasis on data analysis including modeling, data visualization, model testing and statistical interpretation.
Imec has developed its first first shortwave infrared (SWIR) range hyperspectral imaging camera.
In an attempt to extract information relevant for agriculture in remotely sensed wheat crops, MIVIS hyperspectral images are analyzed in the visible and near-infrared domains. Through the selection, by means of a principal component analysis (PCA), of two endmembers of wheat, related respectively to well-developed and stressed plants, a water deficiency is detected among the spectral population of wheat. The image is then modeled by a spectral mixture analysis (unmixing) of these two wheat endmembers, soil, and shade. Resulting fraction images are interpreted in terms of crop vitality (level of green biomass) in relation to stress presence and compared to field knowledge. In addition, these images allow mapping the leaf area index (LAI) over the whole scene, with an empirical relationship based on 12 ground measurements of this variable. This work shows the interest of the approach combining PCA and unmixing for stress detection and mapping of agronomic variables, with a good accuracy compared to spectral ratio analysis. It provides relevant support for crop monitoring and precision agriculture, by means of numerical cartographic products obtained by hyper- (super-) spectral remote sensing. It demonstrates the need for improved methodologies derived from hyperspectral data analysis, and reveals that, through such methods, one can, however, retrieve a significant amount of information with limited number of spectral channels (10–20), highlighting the potential of superspectral observations.
We propose a novel method and system that utilizes a popular smartphone to realize hyperspectral imaging for analyzing skin morphological features and monitoring hemodynamics. The imaging system works based on a built-in RGB camera and flashlight on the smartphone. We apply Wiener estimation to transform the acquired RGB-mode images into “pseudo”-hyperspectral images with 16 wavebands, covering a visible range from 470nm to 620nm. The processing method uses weighted subtractions between wavebands to extract absorption information caused by specific chromophores within skin tissue, mainly including hemoglobin and melanin. Based on the extracted absorption information of hemoglobin, we conduct real-time monitoring experiments in the skin to measure heart rate and to observe skin activities during a vascular occlusion event. Compared with expensive hyperspectral imaging systems, the smartphone-based system delivers similar results but with very-high imaging resolution. Besides, it is easy to operate, very cost-effective and has a wider customer base. The use of an unmodified smartphone to realize hyperspectral imaging promises a possibility to bring a hyperspectral analysis of skin out from laboratory and clinical wards to daily life, which may also impact on healthcare in low resource settings and rural areas.
The online version of Mass Spectrometry for Biotechnology by Gary Siuzdak on ScienceDirect.com, the world's leading platform for high quality peer-reviewed full-text books.
HC-Vision's early prototype rig, a precursor of its single-sensor hyperspectral imaging camera
 In recent years, the amount of commercial and industrial applications of hyperspectral imaging has continued to increase. So, what are the main current and potential industrial and commercial applications? What are the key benefits and challenges of using the technology? And what innovations and trends can we expect over the next few years?
Eshet Eilon’s new fruit sorters use ‘X-ray powers’ to analyze the inside of produce
Imagine you needed to map the spread of an invasive plant species in a tropical forest. Hyperspectral imaging and LiDAR are great at identifying vegetation, but have their limitations and tend to be costly.
In spinal surgery, surgical navigation is an essential tool for safe intervention, including the placement of pedicle screws without injury to nerves and blood vessels. Commercially available systems typically rely on the tracking of a dynamic reference frame attached to the spine of the patient. However, the reference frame can be dislodged or obscured during the surgical procedure, resulting in loss of navigation. Hyperspectral imaging (HSI) captures a large number of spectral information bands across the electromagnetic spectrum, providing image information unseen by the human eye. We aim to exploit HSI to detect skin features in a novel methodology to track patient position in navigated spinal surgery. In our approach, we adopt two local feature detection methods, namely a conventional handcrafted local feature and a deep learning-based feature detection method, which are compared to estimate the feature displacement between different frames due to motion. To demonstrate the ability of the system in tracking skin features, we acquire hyperspectral images of the skin of 17 healthy volunteers. Deep-learned skin features are detected and localized with an average error of only 0.25 mm, outperforming the handcrafted local features with respect to the ground truth based on the use of optical markers.
Tellspec is delivering food safety tools across the complete food supply chain by offering cloud-based spectroscopy solutions
Inspired by the eyes of mantis shrimp, researchers have developed a new kind of optical sensor that is small enough to fit on a smartphone but is capable of hyperspectral and polarimetric imaging.
HySpecIQ’s contract follows three commercial imagery study awards announced by the NRO in June to BlackSky Global, Maxar Technologies and Planet.
Using multispectral data has arrived in the agricultural commodity chain. Compared to multispectral data, spectrally continuous narrow-band sampling, often referred to as hyperspectral sensing, can potentially provide additional information and/or increased sampling accuracy. However, due to the lack of hyperspectral satellite systems with high spatial resolution, these advantages mostly are not yet used in practical farming. This paper summarizes where hyperspectral data provide additional value and information in an agricultural context. It lists the variables of interest and highlights the contribution of hyperspectral sensing for information-driven agriculture, preparing the application of future operational spaceborne hyperspectral missions.
Imec, the world-leading research and innovation hub in nanoelectronics and digital technologies, today announced that it will demonstrate at this week’s SPIE Photonics West in San Francisco its second generation high-speed SNAPSCAN hyperspectral imaging camera.
In this paper, we briefly review the basic concepts of soil spectroscopy with a special attention to the effects of soil roughness on reflectance and then provide a review of state of the art, achievements and perspectives in soil mapping and monitoring based on imaging spectroscopy from air- and spaceborne sensors. Selected application cases are presented for the modelling of soil organic carbon, mineralogical composition, topsoil water content and characterization of soil crust, soil erosion and soil degradation stages based on airborne and simulated spaceborne imaging spectroscopy data.
Sustainable agriculture is a simple and pragmatic idea that there does not have to be a trade-off between agricultural productivity and environmental protection. The conventional approach, however, has been to view agricultural yields and environmental protection as some sort of a zero-sum game in which the latter was constantly out-prioritised by the former. As a result, we have only managed to exacerbate the already adverse environmental impact of agriculture in terms of groundwater depletion, water pollution from fertilizer runoffs, biodiversity loss, soil erosion, and high rates of greenhouse gas emissions.
A multitude of disciplines within the biomedical, chemical, and pharmaceutical fields often rely on mass spectrometry (MS) as a means for identifying compound structure, quantifying metabolites, and measuring molecules in mixtures of varying complexities. This highly sensitive approach for the study of biological systems is also used in drug discovery and is crucial in the development of potentially life-saving therapeutics. Large system size is perhaps the most common limiting factor that may be preventing widespread application of MS in the clinical environment. Additionally, complicated analytical methods can make the system impractical for some healthcare practitioners and nonmedical professionals. Miniature MS has recently been introduced to help overcome size and weight limitations inherent in conventional MS tools. Benchtop MS instruments have become condensed and modified for portability and accessibility, and some miniature MS systems have been adapted for handheld use. Being able to use miniature MS for in situ analysis, for example, has been one significant reason for developing miniature systems. Also, having a MS system that is approachable and easy-to-use by nonmedical professionals, like firefighters and inspectors of food safety, is also a driving force behind the expansion of miniature MS. This technology will be highlighted in numerous talks at Pittcon in Chicago, IL, March 5-9, 2017. Sessions will be led by leading researchers in the field of MS and miniature MS, including R. Graham Cooks of Purdue University and Daniel Austin of Brigham Young University. Talks will be given on the subjects of ion traps and the miniaturization of MS, and numerous companies will be in attendance to demonstrate their mass spectrometer products and how they can be used in a variety of scientific applications.
SCiO is the world's first NIR Spectrometer that fits in the palm of your hand; a tiny molecular sensor that enables you to discover the world around you.
We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art micro-optic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.
Mass spectrometry (MS) is known for highly specific and sensitive analysis. The general applicability of this technique makes it a good candidate for biological applications over a much broader range than is now the case. The limiting factors preventing MS from being applied at the biologist's bench or in a physician's office are identified as the large size of the systems, as well as the complicated analytical procedures required. An approach for developing miniature MS analysis systems with simplified operational procedures is described and the associated technical developments are discussed.
A miniature, low cost mass spectrometer has been developed that is capable of unit resolution over a mass range of 10 to 50 AMU. The design of the mass spectrometer incorporates several new features that enhance the performance of the design over comparable instruments. An efficient ion source allows a relatively low power consumption without sacrificing resolution. Variable geometry mechanical filters allow for variable resolution. An onboard ion pump removes the need for an external pumping source. An onboard digital controller allows a large degree of flexibility over the operation of the mass spectrometer while eliminating the need for high voltage electrical feedthroughs. The miniature mass spectrometer is sensitive to fractions of a percentage of inlet gas, and formatted mass spectra are returned digitally to a laptop.
Getting clearer, healthier skin could soon be as easy as taking a selfie. At CES 2018 in Las Vegas on Tuesday, Lulu Lab — a member of the Samsung-C accele...
HELICoiD project applies the technique to human brain cancer, with clinical studies intended to follow.
Clin Podiatr Med Surg. 2018 Jul;35(3):343-355. doi: 10.1016/j.cpm.2018.02.005. Epub 2018 May 3. Review
The first device to assess Parkinson’s is made by an Israeli firm; the World Economic Forum takes note

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