A next generation VNIR-SWIR hyperspectral camera system: HySpex ODIN-1024

2014 ◽  
Author(s):  
Søren Blaaberg ◽  
Trond Løke ◽  
Ivar Baarstad ◽  
Andrei Fridman ◽  
Pesal Koirala
Keyword(s):  
Next Generation ◽  
Camera System ◽  
Hyperspectral Camera

First results of a new hyperspectral camera system for chemical based wound analysis

2015 ◽  
Vol 10-11 ◽  
pp. 17-22 ◽  
Author(s):  
Jörg Marotz ◽  
Apostolos Siafliakis ◽  
Amadeus Holmer ◽  
Axel Kulcke ◽  
Frank Siemers
Keyword(s):  
Camera System ◽  
First Results ◽  
Hyperspectral Camera

scholarly journals The National Geographic Society Deep-Sea Camera System: A Low-Cost Remote Video Survey Instrument to Advance Biodiversity Observation in the Deep Ocean

2021 ◽  
Vol 7 ◽  
Author(s):  
Jonatha Giddens ◽  
Alan Turchik ◽  
Whitney Goodell ◽  
Michelle Rodriguez ◽  
Denley Delaney
Keyword(s):  
Deep Sea ◽  
Survey Methods ◽  
Deep Ocean ◽  
Cost Effective ◽  
Marine Biodiversity ◽  
Next Generation ◽  
National Geographic Society ◽  
Camera System ◽  
National Geographic ◽  
New Instrument

There is a growing need for marine biodiversity baseline and monitoring data to assess ocean ecosystem health, especially in the deep sea, where data are notoriously sparse. Baited cameras are a biological observing method especially useful in the deep ocean to estimate relative abundances of scavenging fishes and invertebrates. The National Geographic Society Exploration Technology Lab developed an autonomous benthic lander platform with a baited camera system to conduct stationary video surveys of deep-sea megafauna. The first-generation landers were capable of sampling to full ocean depth, however, the form factor, power requirements, and cost of the system limited deployment opportunities. Therefore, a miniaturized version (76 cm × 76 cm × 36 cm, 18 kg in air) was developed to provide a cost-effective method to observe ocean life to 6000 m depth. Here, we detail this next-generation deep-sea camera system, including the structural design, scientific payload, and the procedures for deployment. We provide an overview of NGS deep-sea camera system deployments over the past decade with a focus on the performance improvements of the next-generation system, which began field operations in 2017 and have performed 264 deployments. We present example imagery and discuss the strengths and limitations of the instrument in the context of existing complementary survey methods, and for use in down-stream data products. The key operational advantages of this new instrument are spatial flexibility and cost-efficiency. The instrument can be hand-deployed by a single operator from a small craft concurrent with other shipboard operations. The main limitation of the system is battery power, which allows for 6 h of continuous recording, and takes up to 8 h to recharge between deployments. Like many baited-camera methods, this instrument is specialized to measure the relative abundance of mobile megafauna that are attracted to bait, which results in a stochastic snapshot of the species at the deployment location and time. The small size and ease of deployment of this next-generation camera system allows for increased sample replication on expeditions, and presents a path forward to advance cost-effective biological observing and sustained monitoring in the deep ocean.

scholarly journals Hyperspectral camera system: acquisition and analysis

1995 ◽  
Author(s):  
Gavin J. Brelstaff ◽  
Alejandro Parraga ◽  
Tomasz Troscianko ◽  
Derek Carr
Keyword(s):  
Camera System ◽  
System Acquisition ◽  
Hyperspectral Camera

Experimental Research on Construction-Waste-Classification Algorithms for a Hyperspectral-Camera System

2020 ◽  
Vol 46 (1) ◽  
pp. 5-14
Author(s):  
Yuedong Ku ◽  
Jianhong Yang ◽  
Huaiying Fang ◽  
Jiangteng Zhuang ◽  
Wen Xiao
Keyword(s):  
Adaptive Learning ◽  
Near Infrared ◽  
Comprehensive Evaluation ◽  
Spectral Characteristics ◽  
Recognition Rate ◽  
Classification Model ◽  
Camera System ◽  
Construction Waste ◽  
Learning Machine ◽  
Hyperspectral Camera

A large proportion of construction waste has a high recovery value, and some of the existing recycling-classification methods rely mainly on physical properties for vibration screening. In order to effectively recover construction waste, an industrial near-infrared hyperspectral camera is proposed in this paper to distinguish the spectral characteristics of the objects. The testing results were verified using an extreme learning machine, an adaptive-learning multilayer perceptron, and a one-dimensional convolutional neural network classification model. By establishing several different models to classify and identify the same kinds of experimental materials, the experimental results not only output the correct recognition rate, but also use the recognition efficiency and stability as indices for comprehensive evaluation. The results show that different classification models have different efficiencies and levels of correctness. Under different analytical conditions, such as when using data from different bands, it is very important to select the appropriate classification model to classify construction waste.

Development of an Optical Multispectral Remote Sensing System for Measuring Volcanic Surface Phenomena – Promotion Project for Next Generation Volcano Research B2 (Subtopic 2-2)

2019 ◽  
Vol 14 (5) ◽  
pp. 728-743
Author(s):  
Tetsuya Jitsufuchi ◽  
Keyword(s):  
Remote Sensing ◽  
Volcanic Eruption ◽  
High Accuracy ◽  
Observation System ◽  
Next Generation ◽  
Surface Phenomena ◽  
Camera System ◽  
Sensing System ◽  
Multispectral Remote Sensing ◽  
Remote Sensing Techniques

In 2016, we launched the “Promotion Project for Next Generation Volcano Research B2 (Theme B: Development of Cutting-edge Volcano Observation Technology, subtheme 2: Development of Remote Sensing Techniques for Volcano Observation), subtopic 2-2 (Development of Remote Sensing Techniques for Surface Phenomena of Volcano)” under the “Integrated Program for Next Generation Volcano Research and Human Resources Development” [1], aiming at the development of an optical multispectral remote sensing system for measuring volcanic surface phenomena. With subtopic 2-2, we are planning to develop a new observation device called a surface phenomena imaging camera (SPIC), which is technically superior to current remote sensing techniques, i.e., optical remote observation techniques used to observe volcanic surface phenomena from aircrafts or ground. We are also aiming at applying the developed observation system to quantify volcanic activities and determine volcanic eruption potentials (degrees of urgency) or branching of event trees for volcanic crises with high accuracy, contributing to better predictions of volcanic eruption transitions. To achieve the above-mentioned aims, we started the development of the SPIC by equipping it with camera-type sensors, based on preliminary analyses of the experimental observations made with the airborne spectral imaging system ARTS-SE, which consists of a pushbroom scanner and a camera system, developed by the National Research Institute for Earth Science and Disaster Resilience in FY 2015. We have already developed its components, such as the prototype filter-type multiband cameras SPIC-UC, a prototype uncooled infrared camera, SPIC-C, a cooled camera, and SPIC-SS, a visible-light camera. The SPIC-UC is a two-band camera with the function of visualizing temperature and SO2 gas concentration distributions. The SPIC-C has the function of measuring temperatures between 2 and 1075◦C with high accuracy (noise equivalent temperature difference, NETD: 16 mK); it is equipped with a sensor and a filter wheel that work in the middle wave infrared region (MWIR). The SPIC-SS is a six-lens multiband camera system that estimates the measured images from multiband spectra (6 bands) to hyper spectra (300 bands). Further, we studied a method to estimate digital surface model with a ∼30-m error. As our plan has progressed as scheduled, we intend to complete the prototype SPIC by 2020.

Oxygenation and perfusion monitoring with a hyperspectral camera system for chemical based tissue analysis of skin and organs

2016 ◽  
Vol 37 (11) ◽  
pp. 2064-2078 ◽  
Author(s):  
Amadeus Holmer ◽  
Florian Tetschke ◽  
Jörg Marotz ◽  
Hagen Malberg ◽  
Wenke Markgraf ◽  
...  
Keyword(s):  
Tissue Analysis ◽  
Camera System ◽  
Hyperspectral Camera

Precise on-line Measurement of Lattice Vectors

1990 ◽  
Vol 48 (1) ◽  
pp. 530-531
Author(s):  
W.J. de Ruijter ◽  
Sharma Renu
Keyword(s):  
Electron Microscope ◽  
Measurement Errors ◽  
Dynamic Range ◽  
Structural Information ◽  
Statistical Parameter ◽  
Systematic Errors ◽  
Geometric Distortion ◽  
Crystal Silicon ◽  
Camera System ◽  
On Line

Established methods for measurement of lattice spacings and angles of crystalline materials include x-ray diffraction, microdiffraction and HREM imaging. Structural information from HREM images is normally obtained off-line with the traveling table microscope or by the optical diffractogram technique. We present a new method for precise measurement of lattice vectors from HREM images using an on-line computer connected to the electron microscope. It has already been established that an image of crystalline material can be represented by a finite number of sinusoids. The amplitude and the phase of these sinusoids are affected by the microscope transfer characteristics, which are strongly influenced by the settings of defocus, astigmatism and beam alignment. However, the frequency of each sinusoid is solely a function of overall magnification and periodicities present in the specimen. After proper calibration of the overall magnification, lattice vectors can be measured unambiguously from HREM images.Measurement of lattice vectors is a statistical parameter estimation problem which is similar to amplitude, phase and frequency estimation of sinusoids in 1-dimensional signals as encountered, for example, in radar, sonar and telecommunications. It is important to properly model the observations, the systematic errors and the non-systematic errors. The observations are modelled as a sum of (2-dimensional) sinusoids. In the present study the components of the frequency vector of the sinusoids are the only parameters of interest. Non-systematic errors in recorded electron images are described as white Gaussian noise. The most important systematic error is geometric distortion. Lattice vectors are measured using a two step procedure. First a coarse search is obtained using a Fast Fourier Transform on an image section of interest. Prior to Fourier transformation the image section is multiplied with a window, which gradually falls off to zero at the edges. The user indicates interactively the periodicities of interest by selecting spots in the digital diffractogram. A fine search for each selected frequency is implemented using a bilinear interpolation, which is dependent on the window function. It is possible to refine the estimation even further using a non-linear least squares estimation. The first two steps provide the proper starting values for the numerical minimization (e.g. Gauss-Newton). This third step increases the precision with 30% to the highest theoretically attainable (Cramer and Rao Lower Bound). In the present studies we use a Gatan 622 TV camera attached to the JEM 4000EX electron microscope. Image analysis is implemented on a Micro VAX II computer equipped with a powerful array processor and real time image processing hardware. The typical precision, as defined by the standard deviation of the distribution of measurement errors, is found to be <0.003Å measured on single crystal silicon and <0.02Å measured on small (10-30Å) specimen areas. These values are ×10 times larger than predicted by theory. Furthermore, the measured precision is observed to be independent on signal-to-noise ratio (determined by the number of averaged TV frames). Obviously, the precision is restricted by geometric distortion mainly caused by the TV camera. For this reason, we are replacing the Gatan 622 TV camera with a modern high-grade CCD-based camera system. Such a system not only has negligible geometric distortion, but also high dynamic range (>10,000) and high resolution (1024x1024 pixels). The geometric distortion of the projector lenses can be measured, and corrected through re-sampling of the digitized image.

1477: Durability of Next Generation Flexible Ureteroscopes: Randomized Prospective Study

2004 ◽  
Vol 171 (4S) ◽  
pp. 389-389
Author(s):  
Manoj Monga ◽  
Ramakrishna Venkatesh ◽  
Sara Best ◽  
Caroline D. Ames ◽  
Courtney Lee ◽  
...  
Keyword(s):  
Prospective Study ◽  
Next Generation ◽  
Flexible Ureteroscopes
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