Sample records for nanometer-resolution hyperspectral passive

  1. Passive micromechanical tags. An investigation into writing information at nanometer resolution on micrometer size objects

    Schmieder, R.W.; Bastasz, R.J.


    The authors have completed a 3-year study of the technology related to the development of micron-sized passive micromechanical tags. The project was motivated by the discovery in 1990 by the present authors that low energy, high charge state ions (e.g., Xe +44 ) can produce nanometer-size damage sites on solid surfaces, and the realization that a pattern of these sites represents information. It was envisioned that extremely small, chemically inert, mechanical tags carrying a large label could be fabricated for a variety of applications, including tracking of controlled substances, document verification, process control, research, and engineering. Potential applications exist in the data storage, chemical, food, security, and other industries. The goals of this project were fully accomplished, and they are fully documented here. The work was both experimental and developmental. Most of the experimental effort was a search for appropriate tag materials. Several good materials were found, and the upper limits of information density were determined (ca. 10 12 bit/cm 2 ). Most of the developmental work involved inventing systems and strategies for using these tags, and compiling available technologies for implementing them. The technology provided herein is application-specific: first, the application must be specified, then the tag can be developed for it. The project was not intended to develop a single tag for a single application or for all possible applications. Rather, it was meant to provide the enabling technology for fabricating tags for a range of applications. The results of this project provide sufficient information to proceed directly with such development

  2. Passive micromechanical tags. An investigation into writing information at nanometer resolution on micrometer size objects

    Schmieder, R.W.; Bastasz, R.J.


    The authors have completed a 3-year study of the technology related to the development of micron-sized passive micromechanical tags. The project was motivated by the discovery in 1990 by the present authors that low energy, high charge state ions (e.g., Xe{sup +44}) can produce nanometer-size damage sites on solid surfaces, and the realization that a pattern of these sites represents information. It was envisioned that extremely small, chemically inert, mechanical tags carrying a large label could be fabricated for a variety of applications, including tracking of controlled substances, document verification, process control, research, and engineering. Potential applications exist in the data storage, chemical, food, security, and other industries. The goals of this project were fully accomplished, and they are fully documented here. The work was both experimental and developmental. Most of the experimental effort was a search for appropriate tag materials. Several good materials were found, and the upper limits of information density were determined (ca. 10{sup 12} bit/cm{sup 2}). Most of the developmental work involved inventing systems and strategies for using these tags, and compiling available technologies for implementing them. The technology provided herein is application-specific: first, the application must be specified, then the tag can be developed for it. The project was not intended to develop a single tag for a single application or for all possible applications. Rather, it was meant to provide the enabling technology for fabricating tags for a range of applications. The results of this project provide sufficient information to proceed directly with such development.




    While hard x-rays have wavelengths in the nanometer and sub-nanometer range, the ability to focus them is limited by the quality of sources and optics, and not by the wavelength. A few options, including reflective (mirrors), diffractive (zone plates) and refractive (CRL's) are available, each with their own limitations. Here we present our work with kinoform lenses which are refractive lenses with all material causing redundant 2{pi} phase shifts removed to reduce the absorption problems inherently limiting the resolution of refractive lenses. By stacking kinoform lenses together, the effective numerical aperture, and thus the focusing resolution, can be increased. The present status of kinoform lens fabrication and testing at Brookhaven is presented as well as future plans toward achieving nanometer resolution.

  4. Research on long-range grating interferometry with nanometer resolution

    Chu, Xingchun; Zhao, Shanghong; Lü, Haibao


    Grating interferometry that features long range and nanometer resolution is presented. The optical system was established based on a single long metrology grating. The large fringe multiplication was achieved by properly selecting two high-order diffraction beams to form a fringe pattern. The fringe pattern collected by a linear array was first tailored to a few multiples of fringes in order to suppress the effect of the energy leakage on phase-extracting precision when the fast Fourier transform (FFT) algorithm was used to calculate its phase. Thus, the phase-extracting precision of a tailored fringe pattern by FFT was greatly improved. Based on this, a novel subdividing method, which exploited the time-shift property of FFT, was developed to subdivide the fringe with large multiple and high accuracy. Numerical results show that the system resolution reaches 1 nm. The experimental results obtained against a capacitive sensor in the sub-mm range show that the measurement precision of the system is less than 10 nm. (technical design note)

  5. Sub-nanometer resolution XPS depth profiling: Sensing of atoms

    Szklarczyk, Marek, E-mail: [Faculty of Chemistry, University of Warsaw, ul. Pasteura 1, 02-093 Warsaw (Poland); Shim-Pol, ul. Lubomirskiego 5, 05-080 Izabelin (Poland); Macak, Karol; Roberts, Adam J. [Kratos Analytical Ltd, Wharfside, Trafford Wharf Road, Manchester, M17 1GP (United Kingdom); Takahashi, Kazuhiro [Kratos XPS Section, Shimadzu Corp., 380-1 Horiyamashita, Hadano, Kanagawa 259-1304 (Japan); Hutton, Simon [Kratos Analytical Ltd, Wharfside, Trafford Wharf Road, Manchester, M17 1GP (United Kingdom); Głaszczka, Rafał [Shim-Pol, ul. Lubomirskiego 5, 05-080 Izabelin (Poland); Blomfield, Christopher [Kratos Analytical Ltd, Wharfside, Trafford Wharf Road, Manchester, M17 1GP (United Kingdom)


    Highlights: • Angle resolved photoelectron depth profiling of nano thin films. • Sensing atomic position in SAM films. • Detection of direction position of adsorbed molecules. - Abstract: The development of a method capable of distinguishing a single atom in a single molecule is important in many fields. The results reported herein demonstrate sub-nanometer resolution for angularly resolved X-ray photoelectron spectroscopy (ARXPS). This is made possible by the incorporation of a Maximum Entropy Method (MEM) model, which utilize density corrected electronic emission factors to the X-ray photoelectron spectroscopy (XPS) experimental results. In this paper we report on the comparison between experimental ARXPS results and reconstructed for both inorganic and organic thin film samples. Unexpected deviations between experimental data and calculated points are explained by the inaccuracy of the constants and standards used for the calculation, e.g. emission factors, scattering intensity and atomic density through the studied thickness. The positions of iron, nitrogen and fluorine atoms were determined in the molecules of the studied self-assembled monolayers. It has been shown that reconstruction of real spectroscopic data with 0.2 nm resolution is possible.

  6. A scanning tunneling microscope with a scanning range from hundreds of micrometers down to nanometer resolution.

    Kalkan, Fatih; Zaum, Christopher; Morgenstern, Karina


    A beetle type stage and a flexure scanning stage are combined to form a two stages scanning tunneling microscope (STM). It operates at room temperature in ultrahigh vacuum and is capable of scanning areas up to 300 μm × 450 μm down to resolution on the nanometer scale. This multi-scale STM has been designed and constructed in order to investigate prestructured metallic or semiconducting micro- and nano-structures in real space from atomic-sized structures up to the large-scale environment. The principle of the instrument is demonstrated on two different systems. Gallium nitride based micropillars demonstrate scan areas up to hundreds of micrometers; a Au(111) surface demonstrates nanometer resolution.

  7. Crossed Ga2O3/SnO2 multiwire architecture: a local structure study with nanometer resolution.

    Martínez-Criado, Gema; Segura-Ruiz, Jaime; Chu, Manh-Hung; Tucoulou, Remi; López, Iñaki; Nogales, Emilio; Mendez, Bianchi; Piqueras, Javier


    Crossed nanowire structures are the basis for high-density integration of a variety of nanodevices. Owing to the critical role of nanowires intersections in creating hybrid architectures, it has become a challenge to investigate the local structure in crossing points in metal oxide nanowires. Thus, if intentionally grown crossed nanowires are well-patterned, an ideal model to study the junction is formed. By combining electron and synchrotron beam nanoprobes, we show here experimental evidence of the role of impurities in the coupling formation, structural modifications, and atomic site configuration based on crossed Ga2O3/SnO2 nanowires. Our experiment opens new avenues for further local structure studies with both nanometer resolution and elemental sensitivity.

  8. Passive thermal infrared hyperspectral imaging for quantitative imaging of shale gas leaks

    Gagnon, Marc-André; Tremblay, Pierre; Savary, Simon; Farley, Vincent; Guyot, Éric; Lagueux, Philippe; Morton, Vince; Giroux, Jean; Chamberland, Martin


    There are many types of natural gas fields including shale formations that are common especially in the St-Lawrence Valley (Canada). Since methane (CH4), the major component of shale gas, is odorless, colorless and highly flammable, in addition to being a greenhouse gas, methane emanations and/or leaks are important to consider for both safety and environmental reasons. Telops recently launched on the market the Hyper-Cam Methane, a field-deployable thermal infrared hyperspectral camera specially tuned for detecting methane infrared spectral features under ambient conditions and over large distances. In order to illustrate the benefits of this novel research instrument for natural gas imaging, the instrument was brought on a site where shale gas leaks unexpectedly happened during a geological survey near the Enfant-Jesus hospital in Quebec City, Canada, during December 2014. Quantitative methane imaging was carried out based on methane's unique infrared spectral signature. Optical flow analysis was also carried out on the data to estimate the methane mass flow rate. The results show how this novel technique could be used for advanced research on shale gases.

  9. Hyperspectral remote sensing

    Eismann, Michael Theodore


    ..., and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment...

  10. Hyperspectral imaging flow cytometer

    Sinclair, Michael B.; Jones, Howland D. T.


    A hyperspectral imaging flow cytometer can acquire high-resolution hyperspectral images of particles, such as biological cells, flowing through a microfluidic system. The hyperspectral imaging flow cytometer can provide detailed spatial maps of multiple emitting species, cell morphology information, and state of health. An optimized system can image about 20 cells per second. The hyperspectral imaging flow cytometer enables many thousands of cells to be characterized in a single session.

  11. Hyperspectral remote sensing

    Eismann, Michael


    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. This book provides a holistic treatment that captures its multidisciplinary nature, emphasizing the physical principles of hyperspectral remote sensing.

  12. Hyperspectral image processing methods

    Hyperspectral image processing refers to the use of computer algorithms to extract, store and manipulate both spatial and spectral information contained in hyperspectral images across the visible and near-infrared portion of the electromagnetic spectrum. A typical hyperspectral image processing work...

  13. Hyperspectral cytometry.

    Grégori, Gérald; Rajwa, Bartek; Patsekin, Valery; Jones, James; Furuki, Motohiro; Yamamoto, Masanobu; Paul Robinson, J


    Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system-the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.

  14. Hyperspectral sensing of forests

    Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash


    Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.

  15. Analytic Hyperspectral Sensing

    Coifman, Ronald R


    In the last year (no-cost extension), Plain Sight Systems reached the goal of successfully building its second NIR standoff hyperspectral imaging system, NSTIS, the Near-Infrared Spectral Target Identification System...

  16. Hyperspectral image processing

    Wang, Liguo


    Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping, and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

  17. Hyperspectral fundus imager

    Truitt, Paul W.; Soliz, Peter; Meigs, Andrew D.; Otten, Leonard John, III


    A Fourier Transform hyperspectral imager was integrated onto a standard clinical fundus camera, a Zeiss FF3, for the purposes of spectrally characterizing normal anatomical and pathological features in the human ocular fundus. To develop this instrument an existing FDA approved retinal camera was selected to avoid the difficulties of obtaining new FDA approval. Because of this, several unusual design constraints were imposed on the optical configuration. Techniques to calibrate the sensor and to define where the hyperspectral pushbroom stripe was located on the retina were developed, including the manufacturing of an artificial eye with calibration features suitable for a spectral imager. In this implementation the Fourier transform hyperspectral imager can collect over a hundred 86 cm-1 spectrally resolved bands with 12 micro meter/pixel spatial resolution within the 1050 nm to 450 nm band. This equates to 2 nm to 8 nm spectral resolution depending on the wavelength. For retinal observations the band of interest tends to lie between 475 nm and 790 nm. The instrument has been in use over the last year successfully collecting hyperspectral images of the optic disc, retinal vessels, choroidal vessels, retinal backgrounds, and macula diabetic macular edema, and lesions of age-related macular degeneration.

  18. Simulation of Hyperspectral Images

    Richsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.


    A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data.

  19. Planetary Hyperspectral Imager (PHI)

    Silvergate, Peter


    A hyperspectral imaging spectrometer was breadboarded. Key innovations were use of a sapphire prism and single InSb focal plane to cover the entire spectral range, and a novel slit optic and relay optics to reduce thermal background. Operation over a spectral range of 450 - 4950 nm (approximately 3.5 spectral octaves) was demonstrated. Thermal background reduction by a factor of 8 - 10 was also demonstrated.

  20. Nitrogen concentration estimation with hyperspectral LiDAR

    O. Nevalainen


    Full Text Available Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging (LiDAR instrument has been developed at the Finnish Geodetic Institute (FGI. The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point which offers great potential in the field of remote sensing of environment. This study investigates the performance of the hyperspectral LiDAR instrument in nitrogen estimation. The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out cross-validation. The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant improvement to the remote sensing of environment.

  1. Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR

    Nevalainen, O.; Hakala, T.; Suomalainen, J.M.; Mäkipää, R.; Peltoniemi, M.; Krooks, A.; Kaasalainen, S.


    We propose an empirical method for nondestructive estimation of chlorophyll in tree canopies. The first prototype of a full waveform hyperspectral LiDAR instrument has been developed by the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of passive and active


    A. Roncat


    Full Text Available In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a “single-wavelength reflectometer” to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

  3. Multipurpose Hyperspectral Imaging System

    Mao, Chengye; Smith, David; Lanoue, Mark A.; Poole, Gavin H.; Heitschmidt, Jerry; Martinez, Luis; Windham, William A.; Lawrence, Kurt C.; Park, Bosoon


    A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral imaging with or without relative movement of the imaging system, and it can be used to scan a target of any size as long as the target can be imaged at the focal plane; for example, automated inspection of food items and identification of single-celled organisms. The spectral resolution of this system is greater than that of prior terrestrial multispectral imaging systems. Moreover, unlike prior high-spectral resolution airborne and spaceborne hyperspectral imaging systems, this system does not rely on relative movement of the target and the imaging system to sweep an imaging line across a scene. This compact system (see figure) consists of a front objective mounted at a translation stage with a motorized actuator, and a line-slit imaging spectrograph mounted within a rotary assembly with a rear adaptor to a charged-coupled-device (CCD) camera. Push-broom scanning is carried out by the motorized actuator which can be controlled either manually by an operator or automatically by a computer to drive the line-slit across an image at a focal plane of the front objective. To reduce the cost, the system has been designed to integrate as many as possible off-the-shelf components including the CCD camera and spectrograph. The system has achieved high spectral and spatial resolutions by using a high-quality CCD camera, spectrograph, and front objective lens. Fixtures for attachment of the system to a microscope (U.S. Patent 6,495,818 B1) make it possible to acquire multispectral images of single cells and other microscopic objects.

  4. Infrared upconversion hyperspectral imaging

    Kehlet, Louis Martinus; Tidemand-Lichtenberg, Peter; Dam, Jeppe Seidelin


    In this Letter, hyperspectral imaging in the mid-IR spectral region is demonstrated based on nonlinear frequency upconversion and subsequent imaging using a standard Si-based CCD camera. A series of upconverted images are acquired with different phase match conditions for the nonlinear frequency...... conversion process. From this, a sequence of monochromatic images in the 3.2-3.4 mu m range is generated. The imaged object consists of a standard United States Air Force resolution target combined with a polystyrene film, resulting in the presence of both spatial and spectral information in the infrared...... image. (C) 2015 Optical Society of America...

  5. Passive safety; Passive Sicherheit

    Rueckert, J. [Skoda Auto a.s., Mlada Boleslav (Czech Republic). Interieurentwicklung und Versuche; Hau, M. [Skoda Auto a.s., Mlada Boleslav (Czech Republic). Koordination der Fahrzeugsicherung


    The specifications for passive safety are partly based on the legal requirements for all export markets combined with the strict internal standards of Volkswagen Group. The Euro NCAP tests and their precisely defined testing methods using the new point assessment are very important. (orig.)

  6. Sparse Representations of Hyperspectral Images

    Swanson, Robin J.


    Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.

  7. Sparse Representations of Hyperspectral Images

    Swanson, Robin J.


    Hyperspectral image data has long been an important tool for many areas of sci- ence. The addition of spectral data yields significant improvements in areas such as object and image classification, chemical and mineral composition detection, and astronomy. Traditional capture methods for hyperspectral data often require each wavelength to be captured individually, or by sacrificing spatial resolution. Recently there have been significant improvements in snapshot hyperspectral captures using, in particular, compressed sensing methods. As we move to a compressed sensing image formation model the need for strong image priors to shape our reconstruction, as well as sparse basis become more important. Here we compare several several methods for representing hyperspectral images including learned three dimensional dictionaries, sparse convolutional coding, and decomposable nonlocal tensor dictionaries. Addi- tionally, we further explore their parameter space to identify which parameters provide the most faithful and sparse representations.

  8. Hyperspectral image analysis. A tutorial

    Amigo Rubio, Jose Manuel; Babamoradi, Hamid; Elcoroaristizabal Martin, Saioa


    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processi...... to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case....... will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology...

  9. Image Segmentation of Hyperspectral Imagery

    Wellman, Mark


    .... Army tactical applications. An important tactical application of infrared (IR) hyperspectral imagery is the detection of low-contrast targets, including those targets that may employ camouflage, concealment, and deception (CCD) techniques 1, 2...

  10. Hyperspectral image analysis. A tutorial

    Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa


    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares – Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. - Highlights: • Comprehensive tutorial of Hyperspectral Image analysis. • Hierarchical discrimination of six classes of plastics containing flame retardant. • Step by step guidelines to perform class-modeling on hyperspectral images. • Fusion of multivariate data analysis and digital image processing methods. • Promising methodology for real-time detection of plastics containing flame retardant.

  11. Medical hyperspectral imaging: a review

    Lu, Guolan; Fei, Baowei


    Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

  12. Multiband and Lossless Compression of Hyperspectral Images

    Raffaele Pizzolante


    Full Text Available Hyperspectral images are widely used in several real-life applications. In this paper, we investigate on the compression of hyperspectral images by considering different aspects, including the optimization of the computational complexity in order to allow implementations on limited hardware (i.e., hyperspectral sensors, etc.. We present an approach that relies on a three-dimensional predictive structure. Our predictive structure, 3D-MBLP, uses one or more previous bands as references to exploit the redundancies among the third dimension. The achieved results are comparable, and often better, with respect to the other state-of-art lossless compression techniques for hyperspectral images.

  13. Passive Education

    Bojesen, Emile


    This paper does not present an advocacy of a passive education as opposed to an active education nor does it propose that passive education is in any way 'better' or more important than active education. Through readings of Maurice Blanchot, Jacques Derrida and B.S. Johnson, and gentle critiques of Jacques Rancière and John Dewey, passive…

  14. Hyperspectral remote sensing of vegetation

    Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo


    Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research.

  15. Hyperspectral discrimination of camouflaged target

    Bárta, Vojtěch; Racek, František


    The article deals with detection of camouflaged objects during winter season. Winter camouflage is a marginal affair in most countries due to short time period of the snow cover. In the geographical condition of Central Europe the winter period with snow occurs less than 1/12 of year. The LWIR or SWIR spectral areas are used for detection of camouflaged objects. For those spectral regions the difference in chemical composition and temperature express in spectral features. Exploitation of the LWIR and SWIR devices is demanding due to their large dimension and expensiveness. Therefore, the article deals with estimation of utilization of VIS region for detecting of camouflaged object on snow background. The multispectral image output for the various spectral filters is simulated. Hyperspectral indices are determined to detect the camouflaged objects in the winter. The multispectral image simulation is based on the hyperspectral datacube obtained in real conditions.

  16. Evaluation of Yield and Drought Using Active and Passive Spectral Sensing Systems at the Reproductive Stage in Wheat

    Becker, Elisabeth; Schmidhalter, Urs


    Active and passive sensors are available for ground-based, high-throughput phenotyping in the field. However, these sensor systems have seldom been compared with respect to their determination of plant water status and water use efficiency related parameters under drought conditions. In this study, five passive and active reflectance sensors, including a hyperspectral passive sensor, an active flash sensor (AFS), the Crop Circle, and the GreenSeeker, were evaluated to assess drought-related d...

  17. Hyperspectral anomaly detection using Sony PlayStation 3

    Rosario, Dalton; Romano, João; Sepulveda, Rene


    We present a proof-of-principle demonstration using Sony's IBM Cell processor-based PlayStation 3 (PS3) to run-in near real-time-a hyperspectral anomaly detection algorithm (HADA) on real hyperspectral (HS) long-wave infrared imagery. The PS3 console proved to be ideal for doing precisely the kind of heavy computational lifting HS based algorithms require, and the fact that it is a relatively open platform makes programming scientific applications feasible. The PS3 HADA is a unique parallel-random sampling based anomaly detection approach that does not require prior spectra of the clutter background. The PS3 HADA is designed to handle known underlying difficulties (e.g., target shape/scale uncertainties) often ignored in the development of autonomous anomaly detection algorithms. The effort is part of an ongoing cooperative contribution between the Army Research Laboratory and the Army's Armament, Research, Development and Engineering Center, which aims at demonstrating performance of innovative algorithmic approaches for applications requiring autonomous anomaly detection using passive sensors.

  18. Common hyperspectral image database design

    Tian, Lixun; Liao, Ningfang; Chai, Ali


    This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

  19. Hyperspectral forest monitoring and imaging implications

    Goodenough, David G.; Bannon, David


    The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

  20. Spherical stochastic neighbor embedding of hyperspectral data

    Lunga, D


    Full Text Available and manifold learning in Euclidean spaces, very few attempts have focused on non-Euclidean spaces. Here, we propose a novel approach that embeds hyperspectral data, transformed into bilateral probability similarities, onto a nonlinear unit norm coordinate...

  1. Target Detection Using an AOTF Hyperspectral Imager

    Cheng, L-J.; Mahoney, J.; Reyes, F.; Suiter, H.


    This paper reports results of a recent field experiment using a prototype system to evaluate the acousto-optic tunable filter polarimetric hyperspectral imaging technology for target detection applications.

  2. Distributed Parallel Endmember Extraction of Hyperspectral Data Based on Spark

    Zebin Wu


    Full Text Available Due to the increasing dimensionality and volume of remotely sensed hyperspectral data, the development of acceleration techniques for massive hyperspectral image analysis approaches is a very important challenge. Cloud computing offers many possibilities of distributed processing of hyperspectral datasets. This paper proposes a novel distributed parallel endmember extraction method based on iterative error analysis that utilizes cloud computing principles to efficiently process massive hyperspectral data. The proposed method takes advantage of technologies including MapReduce programming model, Hadoop Distributed File System (HDFS, and Apache Spark to realize distributed parallel implementation for hyperspectral endmember extraction, which significantly accelerates the computation of hyperspectral processing and provides high throughput access to large hyperspectral data. The experimental results, which are obtained by extracting endmembers of hyperspectral datasets on a cloud computing platform built on a cluster, demonstrate the effectiveness and computational efficiency of the proposed method.

  3. Manifold learning based feature extraction for classification of hyperspectral data

    Lunga, D


    Full Text Available in analysis of hyperspectral imagery. High spectral resolution and the typically continuous bands of hyperspectral image (HSI) data enable discrimination between spectrally similar targets of interest, provide capability to estimate within pixel abundances...

  4. Multi- and hyperspectral scene modeling

    Borel, Christoph C.; Tuttle, Ronald F.


    This paper shows how to use a public domain raytracer POV-Ray (Persistence Of Vision Raytracer) to render multiand hyper-spectral scenes. The scripting environment allows automatic changing of the reflectance and transmittance parameters. The radiosity rendering mode allows accurate simulation of multiple-reflections between surfaces and also allows semi-transparent surfaces such as plant leaves. We show that POV-Ray computes occlusion accurately using a test scene with two blocks under a uniform sky. A complex scene representing a plant canopy is generated using a few lines of script. With appropriate rendering settings, shadows cast by leaves are rendered in many bands. Comparing single and multiple reflection renderings, the effect of multiple reflections is clearly visible and accounts for 25% of the overall apparent canopy reflectance in the near infrared.

  5. Hyperspectral remote sensing of plant pigments.

    Blackburn, George Alan


    The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.

  6. Design and Test of Portable Hyperspectral Imaging Spectrometer

    Chunbo Zou


    Full Text Available We design and implement a portable hyperspectral imaging spectrometer, which has high spectral resolution, high spatial resolution, small volume, and low weight. The flight test has been conducted, and the hyperspectral images are acquired successfully. To achieve high performance, small volume, and regular appearance, an improved Dyson structure is designed and used in the hyperspectral imaging spectrometer. The hyperspectral imaging spectrometer is suitable for the small platform such as CubeSat and UAV (unmanned aerial vehicle, and it is also convenient to use for hyperspectral imaging acquiring in the laboratory and the field.

  7. A new hyperspectral image compression paradigm based on fusion

    Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto


    The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

  8. Hyperspectral imaging and its applications

    Serranti, S.; Bonifazi, G.


    Hyperspectral imaging (HSI) is an emerging technique that combines the imaging properties of a digital camera with the spectroscopic properties of a spectrometer able to detect the spectral attributes of each pixel in an image. For these characteristics, HSI allows to qualitatively and quantitatively evaluate the effects of the interactions of light with organic and/or inorganic materials. The results of this interaction are usually displayed as a spectral signature characterized by a sequence of energy values, in a pre-defined wavelength interval, for each of the investigated/collected wavelength. Following this approach, it is thus possible to collect, in a fast and reliable way, spectral information that are strictly linked to chemical-physical characteristics of the investigated materials and/or products. Considering that in an hyperspectral image the spectrum of each pixel can be analyzed, HSI can be considered as one of the best nondestructive technology allowing to perform the most accurate and detailed information extraction. HSI can be applied in different wavelength fields, the most common are the visible (VIS: 400-700 nm), the near infrared (NIR: 1000-1700 nm) and the short wave infrared (SWIR: 1000-2500 nm). It can be applied for inspections from micro- to macro-scale, up to remote sensing. HSI produces a large amount of information due to the great number of continuous collected spectral bands. Such an approach, when successful, is quite challenging being usually reliable, robust and characterized by lower costs, if compared with those usually associated to commonly applied analytical off-line and/or on-line analytical approaches. More and more applications have been thus developed and tested, in these last years, especially in food inspection, with a large range of investigated products, such as fruits and vegetables, meat, fish, eggs and cereals, but also in medicine and pharmaceutical sector, in cultural heritage, in material characterization and in

  9. The hyperspectral imaging trade-off

    Carstensen, Jens Michael

    , this will be the standard situation, and it enables the detection of small spectral features like peaks, valleys and shoulders for a wide range of chemistries. Everything else being equal this is what you would wish for, and hyperspectral imaging is often used in research and in remote sensing because of the needs and cost......Although it has no clear-cut definition, hyperspectral imaging in the UV-Visible-NIR wavelength region seems to mean spectral image sampling in bands from 10 nm width or narrower that enables spectral reconstruction over some wavelength interval. For non-imaging spectral applications...... structures in these projects. However, hyperspectral imaging is a sampling choice within spectral imaging that typically will impose some trade-offs, and these trade-offs will not be optimal for many applications. The purpose of this presentation is to point out and increase the awareness of these trade...

  10. Compositional properties of passivity

    Kerber, Florian; van der Schaft, Arjan


    The classical passivity theorem states that the negative feedback interconnection of passive systems is again passive. The converse statement, - passivity of the interconnected system implies passivity of the subsystems -, turns out to be equally valid. This result implies that among all feasible

  11. Hyperspectral analysis of clay minerals

    Janaki Rama Suresh, G.; Sreenivas, K.; Sivasamy, R.


    A study was carried out by collecting soil samples from parts of Gwalior and Shivpuri district, Madhya Pradesh in order to assess the dominant clay mineral of these soils using hyperspectral data, as 0.4 to 2.5 μm spectral range provides abundant and unique information about many important earth-surface minerals. Understanding the spectral response along with the soil chemical properties can provide important clues for retrieval of mineralogical soil properties. The soil samples were collected based on stratified random sampling approach and dominant clay minerals were identified through XRD analysis. The absorption feature parameters like depth, width, area and asymmetry of the absorption peaks were derived from spectral profile of soil samples through DISPEC tool. The derived absorption feature parameters were used as inputs for modelling the dominant soil clay mineral present in the unknown samples using Random forest approach which resulted in kappa accuracy of 0.795. Besides, an attempt was made to classify the Hyperion data using Spectral Angle Mapper (SAM) algorithm with an overall accuracy of 68.43 %. Results showed that kaolinite was the dominant mineral present in the soils followed by montmorillonite in the study area.

  12. Manifold structure preservative for hyperspectral target detection

    Imani, Maryam


    A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.

  13. Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data

    Huang, Jingfeng; Wei, Chen; Zhang, Yao; Blackburn, George Alan; Wang, Xiuzhen; Wei, Chuanwen; Wang, Jing


    Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a. PMID:26356842

  14. Meta-Analysis of the Detection of Plant Pigment Concentrations Using Hyperspectral Remotely Sensed Data.

    Jingfeng Huang

    Full Text Available Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550-560nm and red edge (680-750nm regions; chlorophyll b on the red, (630-660nm, red edge (670-710nm and the near-infrared (800-810nm; carotenoids on the 500-580nm region; and anthocyanins on the green (550-560nm, red edge (700-710nm and near-infrared (780-790nm. For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.

  15. Hyperspectral remote sensing of postfire soil properties

    Sarah A. Lewis; Peter R. Robichaud; William J. Elliot; Bruce E. Frazier; Joan Q. Wu


    Forest fires may induce changes in soil organic properties that often lead to water repellent conditions within the soil profile that decrease soil infiltration capacity. The remote detection of water repellent soils after forest fires would lead to quicker and more accurate assessment of erosion potential. An airborne hyperspectral image was acquired over the Hayman...

  16. Demystifying autofluorescence with excitation scanning hyperspectral imaging

    Deal, Joshua; Harris, Bradley; Martin, Will; Lall, Malvika; Lopez, Carmen; Rider, Paul; Boudreaux, Carole; Rich, Thomas; Leavesley, Silas J.


    Autofluorescence has historically been considered a nuisance in medical imaging. Many endogenous fluorophores, specifically, collagen, elastin, NADH, and FAD, are found throughout the human body. Diagnostically, these signals can be prohibitive since they can outcompete signals introduced for diagnostic purposes. Recent advances in hyperspectral imaging have allowed the acquisition of significantly more data in a shorter time period by scanning the excitation spectra of fluorophores. The reduced acquisition time and increased signal-to-noise ratio allow for separation of significantly more fluorophores than previously possible. Here, we propose to utilize excitation-scanning of autofluorescence to examine tissues and diagnose pathologies. Spectra of autofluorescent molecules were obtained using a custom inverted microscope (TE-2000, Nikon Instruments) with a Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) Scans utilized excitation wavelengths from 360 nm to 550 nm in 5 nm increments. The resultant spectra were used to examine hyperspectral image stacks from various collaborative studies, including an atherosclerotic rat model and a colon cancer study. Hyperspectral images were analyzed with ENVI and custom Matlab scripts including linear spectral unmixing (LSU) and principal component analysis (PCA). Initial results suggest the ability to separate the signals of endogenous fluorophores and measure the relative concentrations of fluorophores among healthy and diseased states of similar tissues. These results suggest pathology-specific changes to endogenous fluorophores can be detected using excitationscanning hyperspectral imaging. Future work will expand the library of pure molecules and will examine more defined disease states.

  17. Hyperspectral data exploitation theory and applications

    Chang, Chein-I


    Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.

  18. Airborne hyperspectral remote sensing in Italy

    Bianchi, Remo; Marino, Carlo M.; Pignatti, Stefano


    The Italian National Research Council (CNR) in the framework of its `Strategic Project for Climate and Environment in Southern Italy' established a new laboratory for airborne hyperspectral imaging devoted to environmental problems. Since the end of June 1994, the LARA (Laboratorio Aereo per Ricerche Ambientali -- Airborne Laboratory for Environmental Studies) Project is fully operative to provide hyperspectral data to the national and international scientific community by means of deployments of its CASA-212 aircraft carrying the Daedalus AA5000 MIVIS (multispectral infrared and visible imaging spectrometer) system. MIVIS is a modular instrument consisting of 102 spectral channels that use independent optical sensors simultaneously sampled and recorded onto a compact computer compatible magnetic tape medium with a data capacity of 10.2 Gbytes. To support the preprocessing and production pipeline of the large hyperspectral data sets CNR housed in Pomezia, a town close to Rome, a ground based computer system with a software designed to handle MIVIS data. The software (MIDAS-Multispectral Interactive Data Analysis System), besides the data production management, gives to users a powerful and highly extensible hyperspectral analysis system. The Pomezia's ground station is designed to maintain and check the MIVIS instrument performance through the evaluation of data quality (like spectral accuracy, signal to noise performance, signal variations, etc.), and to produce, archive, and diffuse MIVIS data in the form of geometrically and radiometrically corrected data sets on low cost and easy access CC media.

  19. Novel hyperspectral prediction method and apparatus

    Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf


    Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

  20. Hyperspectral signature analysis of skin parameters

    Vyas, Saurabh; Banerjee, Amit; Garza, Luis; Kang, Sewon; Burlina, Philippe


    The temporal analysis of changes in biological skin parameters, including melanosome concentration, collagen concentration and blood oxygenation, may serve as a valuable tool in diagnosing the progression of malignant skin cancers and in understanding the pathophysiology of cancerous tumors. Quantitative knowledge of these parameters can also be useful in applications such as wound assessment, and point-of-care diagnostics, amongst others. We propose an approach to estimate in vivo skin parameters using a forward computational model based on Kubelka-Munk theory and the Fresnel Equations. We use this model to map the skin parameters to their corresponding hyperspectral signature. We then use machine learning based regression to develop an inverse map from hyperspectral signatures to skin parameters. In particular, we employ support vector machine based regression to estimate the in vivo skin parameters given their corresponding hyperspectral signature. We build on our work from SPIE 2012, and validate our methodology on an in vivo dataset. This dataset consists of 241 signatures collected from in vivo hyperspectral imaging of patients of both genders and Caucasian, Asian and African American ethnicities. In addition, we also extend our methodology past the visible region and through the short-wave infrared region of the electromagnetic spectrum. We find promising results when comparing the estimated skin parameters to the ground truth, demonstrating good agreement with well-established physiological precepts. This methodology can have potential use in non-invasive skin anomaly detection and for developing minimally invasive pre-screening tools.

  1. Sparse-Based Modeling of Hyperspectral Data

    Calvini, Rosalba; Ulrici, Alessandro; Amigo Rubio, Jose Manuel


    One of the main issues of hyperspectral imaging data is to unravel the relevant, yet overlapped, huge amount of information contained in the spatial and spectral dimensions. When dealing with the application of multivariate models in such high-dimensional data, sparsity can improve...

  2. Hyperspectral Unmixing with Robust Collaborative Sparse Regression

    Chang Li


    Full Text Available Recently, sparse unmixing (SU of hyperspectral data has received particular attention for analyzing remote sensing images. However, most SU methods are based on the commonly admitted linear mixing model (LMM, which ignores the possible nonlinear effects (i.e., nonlinearity. In this paper, we propose a new method named robust collaborative sparse regression (RCSR based on the robust LMM (rLMM for hyperspectral unmixing. The rLMM takes the nonlinearity into consideration, and the nonlinearity is merely treated as outlier, which has the underlying sparse property. The RCSR simultaneously takes the collaborative sparse property of the abundance and sparsely distributed additive property of the outlier into consideration, which can be formed as a robust joint sparse regression problem. The inexact augmented Lagrangian method (IALM is used to optimize the proposed RCSR. The qualitative and quantitative experiments on synthetic datasets and real hyperspectral images demonstrate that the proposed RCSR is efficient for solving the hyperspectral SU problem compared with the other four state-of-the-art algorithms.

  3. Kernel based subspace projection of hyperspectral images

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  4. Mapping Soil Organic Matter with Hyperspectral Imaging

    Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel


    Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our

  5. Illumination compensation in ground based hyperspectral imaging

    Wendel, Alexander; Underwood, James


    Hyperspectral imaging has emerged as an important tool for analysing vegetation data in agricultural applications. Recently, low altitude and ground based hyperspectral imaging solutions have come to the fore, providing very high resolution data for mapping and studying large areas of crops in detail. However, these platforms introduce a unique set of challenges that need to be overcome to ensure consistent, accurate and timely acquisition of data. One particular problem is dealing with changes in environmental illumination while operating with natural light under cloud cover, which can have considerable effects on spectral shape. In the past this has been commonly achieved by imaging known reference targets at the time of data acquisition, direct measurement of irradiance, or atmospheric modelling. While capturing a reference panel continuously or very frequently allows accurate compensation for illumination changes, this is often not practical with ground based platforms, and impossible in aerial applications. This paper examines the use of an autonomous unmanned ground vehicle (UGV) to gather high resolution hyperspectral imaging data of crops under natural illumination. A process of illumination compensation is performed to extract the inherent reflectance properties of the crops, despite variable illumination. This work adapts a previously developed subspace model approach to reflectance and illumination recovery. Though tested on a ground vehicle in this paper, it is applicable to low altitude unmanned aerial hyperspectral imagery also. The method uses occasional observations of reference panel training data from within the same or other datasets, which enables a practical field protocol that minimises in-field manual labour. This paper tests the new approach, comparing it against traditional methods. Several illumination compensation protocols for high volume ground based data collection are presented based on the results. The findings in this paper are

  6. Development of a compressive sampling hyperspectral imager prototype

    Barducci, Alessandro; Guzzi, Donatella; Lastri, Cinzia; Nardino, Vanni; Marcoionni, Paolo; Pippi, Ivan


    Compressive sensing (CS) is a new technology that investigates the chance to sample signals at a lower rate than the traditional sampling theory. The main advantage of CS is that compression takes place during the sampling phase, making possible significant savings in terms of the ADC, data storage memory, down-link bandwidth, and electrical power absorption. The CS technology could have primary importance for spaceborne missions and technology, paving the way to noteworthy reductions of payload mass, volume, and cost. On the contrary, the main CS disadvantage is made by the intensive off-line data processing necessary to obtain the desired source estimation. In this paper we summarize the CS architecture and its possible implementations for Earth observation, giving evidence of possible bottlenecks hindering this technology. CS necessarily employs a multiplexing scheme, which should produce some SNR disadvantage. Moreover, this approach would necessitate optical light modulators and 2-dim detector arrays of high frame rate. This paper describes the development of a sensor prototype at laboratory level that will be utilized for the experimental assessment of CS performance and the related reconstruction errors. The experimental test-bed adopts a push-broom imaging spectrometer, a liquid crystal plate, a standard CCD camera and a Silicon PhotoMultiplier (SiPM) matrix. The prototype is being developed within the framework of the ESA ITI-B Project titled "Hyperspectral Passive Satellite Imaging via Compressive Sensing".

  7. Passive solar technology

    Watson, D


    The present status of passive solar technology is summarized, including passive solar heating, cooling and daylighting. The key roles of the passive solar system designer and of innovation in the building industry are described. After definitions of passive design and a summary of passive design principles are given, performance and costs of passive solar technology are discussed. Passive energy design concepts or methods are then considered in the context of the overall process by which building decisions are made to achieve the integration of new techniques into conventional design. (LEW).

  8. A Gimbal-Stabilized Compact Hyperspectral Imaging System, Phase II

    National Aeronautics and Space Administration — The Gimbal-stabilized Compact Hyperspectral Imaging System (GCHIS) fully integrates multi-sensor spectral imaging, stereovision, GPS and inertial measurement,...

  9. Fundamental studies of passivity and passivity breakdown

    Macdonald, D.D.; Urquidi-Macdonald, M.; Song, H.; Biaggio-Rocha, S.; Searson, P.


    This report summarizes the findings of our fundamental research program on passivity and passivity breakdown. During the past three and one half years in this program (including the three year incrementally-funded grant prior to the present grant), we developed and experimentally tested various physical models for the growth and breakdown of passive films on metal surfaces. These models belong to a general class termed ''point defects models'' (PDMs), in which the growth and breakdown of passive films are described in terms of the movement of anion and cation vacancies

  10. Advances in hyperspectral remote sensing I: The visible Fourier transform hyperspectral imager

    J. Bruce Rafert


    Full Text Available We discuss early hyperspectral research and development activities during the 1990s that led to the deployment of aircraft and satellite payloads whose heritage was based on the use of visible, spatially modulated, imaging Fourier transform spectrometers, beginning with early experiments at the Florida Institute of Technology, through successful launch and deployment of the Visible Fourier Transform Hyperspectral Imager on MightySat II.1 on 19 July 2000. In addition to a brief chronological overview, we also discuss several of the most interesting optical engineering challenges that were addressed over this timeframe, present some as-yet un-exploited features of field-widened (slit-less SMIFTS instruments, and present some images from ground-based, aircraft-based and satellite-based instruments that helped provide the impetus for the proliferation and development of entire new families of instruments and countless new applications for hyperspectral imaging.

  11. Classification of High Spatial Resolution, Hyperspectral ...

    EPA announced the availability of the final report,Classification of High Spatial Resolution, Hyperspectral Remote Sensing Imagery of the Little Miami River Watershed in Southwest Ohio, USA . This report and associated land use/land cover (LULC) coverage is the result of a collaborative effort among an interdisciplinary team of scientists with the U.S. Environmental Protection Agency's (U.S. EPA's) Office of Research and Development in Cincinnati, Ohio. A primary goal of this project is to enhance the use of geography and spatial analytic tools in risk assessment, and to improve the scientific basis for risk management decisions affecting drinking water and water quality. The land use/land cover classification is derived from 82 flight lines of Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery acquired from July 24 through August 9, 2002 via fixed-wing aircraft.

  12. Software for Simulation of Hyperspectral Images

    Richtsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.


    A package of software generates simulated hyperspectral images for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport as well as surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, 'ground truth' is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces and the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for and a supplement to field validation data.

  13. Hyperspectral Image Analysis of Food Quality

    Arngren, Morten

    inspection.Near-infrared spectroscopy can address these issues by offering a fast and objectiveanalysis of the food quality. A natural extension to these single spectrumNIR systems is to include image information such that each pixel holds a NIRspectrum. This augmented image information offers several......Assessing the quality of food is a vital step in any food processing line to ensurethe best food quality and maximum profit for the farmer and food manufacturer.Traditional quality evaluation methods are often destructive and labourintensive procedures relying on wet chemistry or subjective human...... extensions to the analysis offood quality. This dissertation is concerned with hyperspectral image analysisused to assess the quality of single grain kernels. The focus is to highlight thebenefits and challenges of using hyperspectral imaging for food quality presentedin two research directions. Initially...

  14. Estimating physiological skin parameters from hyperspectral signatures

    Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe


    We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

  15. Atmospheric correction of APEX hyperspectral data

    Sterckx Sindy


    Full Text Available Atmospheric correction plays a crucial role among the processing steps applied to remotely sensed hyperspectral data. Atmospheric correction comprises a group of procedures needed to remove atmospheric effects from observed spectra, i.e. the transformation from at-sensor radiances to at-surface radiances or reflectances. In this paper we present the different steps in the atmospheric correction process for APEX hyperspectral data as applied by the Central Data Processing Center (CDPC at the Flemish Institute for Technological Research (VITO, Mol, Belgium. The MODerate resolution atmospheric TRANsmission program (MODTRAN is used to determine the source of radiation and for applying the actual atmospheric correction. As part of the overall correction process, supporting algorithms are provided in order to derive MODTRAN configuration parameters and to account for specific effects, e.g. correction for adjacency effects, haze and shadow correction, and topographic BRDF correction. The methods and theory underlying these corrections and an example of an application are presented.

  16. LIFTERS-hyperspectral imaging at LLNL

    Fields, D. [Lawrence Livermore National Lab., CA (United States); Bennett, C.; Carter, M.


    LIFTIRS, the Livermore Imaging Fourier Transform InfraRed Spectrometer, recently developed at LLNL, is an instrument which enables extremely efficient collection and analysis of hyperspectral imaging data. LIFTIRS produces a spatial format of 128x128 pixels, with spectral resolution arbitrarily variable up to a maximum of 0.25 inverse centimeters. Time resolution and spectral resolution can be traded off for each other with great flexibility. We will discuss recent measurements made with this instrument, and present typical images and spectra.

  17. Ore minerals textural characterization by hyperspectral imaging

    Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia


    The utilization of hyperspectral detection devices, for natural resources mapping/exploitation through remote sensing techniques, dates back to the early 1970s. From the first devices utilizing a one-dimensional profile spectrometer, HyperSpectral Imaging (HSI) devices have been developed. Thus, from specific-customized devices, originally developed by Governmental Agencies (e.g. NASA, specialized research labs, etc.), a lot of HSI based equipment are today available at commercial level. Parallel to this huge increase of hyperspectral systems development/manufacturing, addressed to airborne application, a strong increase also occurred in developing HSI based devices for "ground" utilization that is sensing units able to play inside a laboratory, a processing plant and/or in an open field. Thanks to this diffusion more and more applications have been developed and tested in this last years also in the materials sectors. Such an approach, when successful, is quite challenging being usually reliable, robust and characterised by lower costs if compared with those usually associated to commonly applied analytical off- and/or on-line analytical approaches. In this paper such an approach is presented with reference to ore minerals characterization. According to the different phases and stages of ore minerals and products characterization, and starting from the analyses of the detected hyperspectral firms, it is possible to derive useful information about mineral flow stream properties and their physical-chemical attributes. This last aspect can be utilized to define innovative process mineralogy strategies and to implement on-line procedures at processing level. The present study discusses the effects related to the adoption of different hardware configurations, the utilization of different logics to perform the analysis and the selection of different algorithms according to the different characterization, inspection and quality control actions to apply.

  18. Distributed Unmixing of Hyperspectral Datawith Sparsity Constraint

    Khoshsokhan, S.; Rajabi, R.; Zayyani, H.


    Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in a blind problem, nonnegative matrix factorization (NMF) and its developments are used widely in the SU problem. One of the constraints which was added to NMF is sparsity constraint that was regularized by L1/2 norm. In this paper, a new algorithm based on distributed optimization has been used for spectral unmixing. In the proposed algorithm, a network including single-node clusters has been employed. Each pixel in hyperspectral images considered as a node in this network. The distributed unmixing with sparsity constraint has been optimized with diffusion LMS strategy, and then the update equations for fractional abundance and signature matrices are obtained. Simulation results based on defined performance metrics, illustrate advantage of the proposed algorithm in spectral unmixing of hyperspectral data compared with other methods. The results show that the AAD and SAD of the proposed approach are improved respectively about 6 and 27 percent toward distributed unmixing in SNR=25dB.

  19. Hyperspectral image classification using Support Vector Machine

    Moughal, T A


    Classification of land cover hyperspectral images is a very challenging task due to the unfavourable ratio between the number of spectral bands and the number of training samples. The focus in many applications is to investigate an effective classifier in terms of accuracy. The conventional multiclass classifiers have the ability to map the class of interest but the considerable efforts and large training sets are required to fully describe the classes spectrally. Support Vector Machine (SVM) is suggested in this paper to deal with the multiclass problem of hyperspectral imagery. The attraction to this method is that it locates the optimal hyper plane between the class of interest and the rest of the classes to separate them in a new high-dimensional feature space by taking into account only the training samples that lie on the edge of the class distributions known as support vectors and the use of the kernel functions made the classifier more flexible by making it robust against the outliers. A comparative study has undertaken to find an effective classifier by comparing Support Vector Machine (SVM) to the other two well known classifiers i.e. Maximum likelihood (ML) and Spectral Angle Mapper (SAM). At first, the Minimum Noise Fraction (MNF) was applied to extract the best possible features form the hyperspectral imagery and then the resulting subset of the features was applied to the classifiers. Experimental results illustrate that the integration of MNF and SVM technique significantly reduced the classification complexity and improves the classification accuracy.

  20. PET and PVC Separation with Hyperspectral Imagery

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; La Marca, Floriana


    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers—polyethylene terephthalate (PET) and polyvinyl chloride (PVC)—in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900–1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry. PMID:25609050

  1. PET and PVC separation with hyperspectral imagery.

    Moroni, Monica; Mei, Alessandro; Leonardi, Alessandra; Lupo, Emanuela; Marca, Floriana La


    Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density). Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers--polyethylene terephthalate (PET) and polyvinyl chloride (PVC)--in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials) to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900-1700 nm) reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry.

  2. Evaluation of camouflage effectiveness using hyperspectral images

    Zavvartorbati, Ahmad; Dehghani, Hamid; Rashidi, Ali Jabar


    Recent advances in camouflage engineering have made it more difficult to detect targets. Assessing the effectiveness of camouflage against different target detection methods leads to identifying the strengths and weaknesses of camouflage designs. One of the target detection methods is to analyze the content of the scene using remote sensing hyperspectral images. In the process of evaluating camouflage designs, there must be comprehensive and efficient evaluation criteria. Three parameters were considered as the main factors affecting the target detection and based on these factors, camouflage effectiveness assessment criteria were proposed. To combine the criteria in the form of a single equation, the equation used in target visual search models was employed and for determining the criteria, a model was presented based on the structure of the computational visual attention systems. Also, in software implementations on the HyMap hyperspectral image, a variety of camouflage levels were created for the real targets in the image. Assessing the camouflage levels using the proposed criteria, comparing and analyzing the results can show that the provided criteria and model are effective for the evaluation of camouflage designs using hyperspectral images.

  3. PET and PVC Separation with Hyperspectral Imagery

    Monica Moroni


    Full Text Available Traditional plants for plastic separation in homogeneous products employ material physical properties (for instance density. Due to the small intervals of variability of different polymer properties, the output quality may not be adequate. Sensing technologies based on hyperspectral imaging have been introduced in order to classify materials and to increase the quality of recycled products, which have to comply with specific standards determined by industrial applications. This paper presents the results of the characterization of two different plastic polymers—polyethylene terephthalate (PET and polyvinyl chloride (PVC—in different phases of their life cycle (primary raw materials, urban and urban-assimilated waste and secondary raw materials to show the contribution of hyperspectral sensors in the field of material recycling. This is accomplished via near-infrared (900–1700 nm reflectance spectra extracted from hyperspectral images acquired with a two-linear-spectrometer apparatus. Results have shown that a rapid and reliable identification of PET and PVC can be achieved by using a simple two near-infrared wavelength operator coupled to an analysis of reflectance spectra. This resulted in 100% classification accuracy. A sensor based on this identification method appears suitable and inexpensive to build and provides the necessary speed and performance required by the recycling industry.

  4. Hyperspectral microscopy to identify foodborne bacteria with optimum lighting source

    Hyperspectral microscopy is an emerging technology for rapid detection of foodborne pathogenic bacteria. Since scattering spectral signatures from hyperspectral microscopic images (HMI) vary with lighting sources, it is important to select optimal lights. The objective of this study is to compare t...

  5. D Reconstruction from Uav-Based Hyperspectral Images

    Liu, L.; Xu, L.; Peng, J.


    Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

  6. Postfire soil burn severity mapping with hyperspectral image unmixing

    Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio


    Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

  7. Blind estimation of blur in hyperspectral images

    Zhang, Mo; Vozel, Benoit; Chehdi, Kacem; Uss, Mykhail; Abramov, Sergey; Lukin, Vladimir


    Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. When no knowledge is available about the degradations present on the original image, blind restoration methods can only be considered. By blind, we mean absolutely no knowledge neither of the blur point spread function (PSF) nor the original latent channel and the noise level. In this study, we address the blind restoration of the degraded channels component-wise, according to a sequential scheme. For each degraded channel, the sequential scheme estimates the blur point spread function (PSF) in a first stage and deconvolves the degraded channel in a second and final stage by means of using the PSF previously estimated. We propose a new component-wise blind method for estimating effectively and accurately the blur point spread function. This method follows recent approaches suggesting the detection, selection and use of sufficiently salient edges in the current processed channel for supporting the regularized blur PSF estimation. Several modifications are beneficially introduced in our work. A new selection of salient edges through thresholding adequately the cumulative distribution of their corresponding gradient magnitudes is introduced. Besides, quasi-automatic and spatially adaptive tuning of the involved regularization parameters is considered. To prove applicability and higher efficiency of the proposed method, we compare it against the method it originates from and four representative edge-sparsifying regularized methods of the literature already assessed in a previous work. Our attention is mainly paid to the objective analysis (via ݈l1-norm) of the blur PSF error estimation accuracy. The tests are performed on a synthetic hyperspectral image. This synthetic hyperspectral image has been built from various samples from classified areas of a real-life hyperspectral image, in order to benefit from realistic spatial

  8. Volcanic Eruption Observations from an Elevated Point of the Stromboli Using Thermal Infrared Hyperspectral Imaging

    Morton, V.; Gagnon, M. A.; Marcotte, F.; Gouhier, M.; Smekens, J. F.


    Many urban areas are located near active volcanoes around the world. Therefore, scientific research on different indicators of imminent eruptions is carried out on an ongoing basis. Due to the hazardous and unpredictable behavior of volcanoes, remote sensing technologies are normally preferred for investigations. Over the years, the Telops Hyper-Cam, a high-performance infrared hyperspectral camera, has established itself as a reference tool for investigating gas clouds over large distances. In order to illustrate the benefits of standoff infrared hyperspectral imaging for characterizing volcanic processes, many different measurements were carried out from an elevated point ( 800 m) of the Stromboli volcano (Italy) by researchers from the Université Blaise-Pascal (Clermont-Ferrand, France). The Stromboli volcano is well known for its periodic eruptions of small magnitude containing various proportions of ash, lava and gases. Imaging was carried out at a relatively high spectral and spatial resolution before and during eruptions from the North-East (NE) craters. Both sulfur dioxide (SO2) and sulfur tetrafluoride (SiF4) could be successfully identified within the volcano's plume from their distinct spectral features. During the passive degassing phase, a total amount of 3.3 kg of SO2 and 0.8 g of SiF4 were estimated. A violent eruption from NE1 crater was then observed and a total of 45 g and and 7 g of SO2 and SiF4 were estimated respectively. These results are in good agreement with previous work using a UV-SO2 camera. Finally, a smaller eruption from NE2 crater was observed. Total amounts of 3 kg and 17 g of SO2 and SiF4 were estimated respectively. Quantitative chemical maps for both gases will be presented. The results show that standoff thermal infrared hyperspectral imaging provides unique insights for a better understanding of volcanic eruptions.

  9. Immunizations: Active vs. Passive

    ... Issues Health Issues Health Issues Conditions Injuries & Emergencies Vaccine Preventable Diseases ... Children > Safety & Prevention > Immunizations > Immunizations: Active vs. Passive Safety & ...

  10. Hydrogenation of passivated contacts

    Nemeth, William; Yuan, Hao-Chih; LaSalvia, Vincenzo; Stradins, Pauls; Page, Matthew R.


    Methods of hydrogenation of passivated contacts using materials having hydrogen impurities are provided. An example method includes applying, to a passivated contact, a layer of a material, the material containing hydrogen impurities. The method further includes subsequently annealing the material and subsequently removing the material from the passivated contact.

  11. Research on hyperspectral dynamic scene and image sequence simulation

    Sun, Dandan; Liu, Fang; Gao, Jiaobo; Sun, Kefeng; Hu, Yu; Li, Yu; Xie, Junhu; Zhang, Lei


    This paper presents a simulation method of hyperspectral dynamic scene and image sequence for hyperspectral equipment evaluation and target detection algorithm. Because of high spectral resolution, strong band continuity, anti-interference and other advantages, in recent years, hyperspectral imaging technology has been rapidly developed and is widely used in many areas such as optoelectronic target detection, military defense and remote sensing systems. Digital imaging simulation, as a crucial part of hardware in loop simulation, can be applied to testing and evaluation hyperspectral imaging equipment with lower development cost and shorter development period. Meanwhile, visual simulation can produce a lot of original image data under various conditions for hyperspectral image feature extraction and classification algorithm. Based on radiation physic model and material characteristic parameters this paper proposes a generation method of digital scene. By building multiple sensor models under different bands and different bandwidths, hyperspectral scenes in visible, MWIR, LWIR band, with spectral resolution 0.01μm, 0.05μm and 0.1μm have been simulated in this paper. The final dynamic scenes have high real-time and realistic, with frequency up to 100 HZ. By means of saving all the scene gray data in the same viewpoint image sequence is obtained. The analysis results show whether in the infrared band or the visible band, the grayscale variations of simulated hyperspectral images are consistent with the theoretical analysis results.

  12. Using hyperspectral imaging technology to identify diseased tomato leaves

    Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei


    In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

  13. Reconfigurable Hardware for Compressing Hyperspectral Image Data

    Aranki, Nazeeh; Namkung, Jeffrey; Villapando, Carlos; Kiely, Aaron; Klimesh, Matthew; Xie, Hua


    High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of

  14. Inland excess water mapping using hyperspectral imagery

    Csendes Bálint


    Full Text Available Hyperspectral imaging combined with the potentials of airborne scanning is a powerful tool to monitor environmental processes. The aim of this research was to use high resolution remotely sensed data to map the spatial extent of inland excess water patches in a Hungarian study area that is known for its oil and gas production facilities. Periodic floodings show high spatial and temporal variability, nevertheless, former studies have proven that the affected soil surfaces can be accurately identified. Besides separability measurements, we performed spectral angle classification, which gave a result of 85% overall accuracy and we also compared the generated land cover map with LIDAR elevation data.

  15. Snapshot hyperspectral imaging and practical applications

    Wong, G


    Traditional broadband imaging involves the digital representation of a remote scene within a reduced colour space. Hyperspectral imaging exploits the full spectral dimension, which better reflects the continuous nature of actual spectra. Conventional techniques are all time-delayed whereby spatial or spectral scanning is required for hypercube generation. An innovative and patented technique developed at Heriot-Watt University offers significant potential as a snapshot sensor, to enable benefits for the wider public beyond aerospace imaging. This student-authored paper seeks to promote awareness of this field within the photonic community and its potential advantages for real-time practical applications.

  16. Hyperspectral image compressing using wavelet-based method

    Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng


    Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

  17. Dried fruits quality assessment by hyperspectral imaging

    Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe


    Dried fruits products present different market values according to their quality. Such a quality is usually quantified in terms of freshness of the products, as well as presence of contaminants (pieces of shell, husk, and small stones), defects, mould and decays. The combination of these parameters, in terms of relative presence, represent a fundamental set of attributes conditioning dried fruits humans-senses-detectable-attributes (visual appearance, organolectic properties, etc.) and their overall quality in terms of marketable products. Sorting-selection strategies exist but sometimes they fail when a higher degree of detection is required especially if addressed to discriminate between dried fruits of relatively small dimensions and when aiming to perform an "early detection" of pathogen agents responsible of future moulds and decays development. Surface characteristics of dried fruits can be investigated by hyperspectral imaging (HSI). In this paper, specific and "ad hoc" applications addressed to propose quality detection logics, adopting a hyperspectral imaging (HSI) based approach, are described, compared and critically evaluated. Reflectance spectra of selected dried fruits (hazelnuts) of different quality and characterized by the presence of different contaminants and defects have been acquired by a laboratory device equipped with two HSI systems working in two different spectral ranges: visible-near infrared field (400-1000 nm) and near infrared field (1000-1700 nm). The spectra have been processed and results evaluated adopting both a simple and fast wavelength band ratio approach and a more sophisticated classification logic based on principal component (PCA) analysis.

  18. Hyperspectral monitoring of chemically sensitive plant sentinels

    Simmons, Danielle A.; Kerekes, John P.; Raqueno, Nina G.


    Automated detection of chemical threats is essential for an early warning of a potential attack. Harnessing plants as bio-sensors allows for distributed sensing without a power supply. Monitoring the bio-sensors requires a specifically tailored hyperspectral system. Tobacco plants have been genetically engineered to de-green when a material of interest (e.g. zinc, TNT) is introduced to their immediate vicinity. The reflectance spectra of the bio-sensors must be accurately characterized during the de-greening process for them to play a role in an effective warning system. Hyperspectral data have been collected under laboratory conditions to determine the key regions in the reflectance spectra associated with the degreening phenomenon. Bio-sensor plants and control (nongenetically engineered) plants were exposed to TNT over the course of two days and their spectra were measured every six hours. Rochester Institute of Technologys Digital Imaging and Remote Sensing Image Generation Model (DIRSIG) was used to simulate detection of de-greened plants in the field. The simulated scene contains a brick school building, sidewalks, trees and the bio-sensors placed at the entrances to the buildings. Trade studies of the bio-sensor monitoring system were also conducted using DIRSIG simulations. System performance was studied as a function of field of view, pixel size, illumination conditions, radiometric noise, spectral waveband dependence and spectral resolution. Preliminary results show that the most significant change in reflectance during the degreening period occurs in the near infrared region.

  19. Maximum Margin Clustering of Hyperspectral Data

    Niazmardi, S.; Safari, A.; Homayouni, S.


    In recent decades, large margin methods such as Support Vector Machines (SVMs) are supposed to be the state-of-the-art of supervised learning methods for classification of hyperspectral data. However, the results of these algorithms mainly depend on the quality and quantity of available training data. To tackle down the problems associated with the training data, the researcher put effort into extending the capability of large margin algorithms for unsupervised learning. One of the recent proposed algorithms is Maximum Margin Clustering (MMC). The MMC is an unsupervised SVMs algorithm that simultaneously estimates both the labels and the hyperplane parameters. Nevertheless, the optimization of the MMC algorithm is a non-convex problem. Most of the existing MMC methods rely on the reformulating and the relaxing of the non-convex optimization problem as semi-definite programs (SDP), which are computationally very expensive and only can handle small data sets. Moreover, most of these algorithms are two-class classification, which cannot be used for classification of remotely sensed data. In this paper, a new MMC algorithm is used that solve the original non-convex problem using Alternative Optimization method. This algorithm is also extended for multi-class classification and its performance is evaluated. The results of the proposed algorithm show that the algorithm has acceptable results for hyperspectral data clustering.

  20. Geometric correction of APEX hyperspectral data

    Vreys Kristin


    Full Text Available Hyperspectral imagery originating from airborne sensors is nowadays widely used for the detailed characterization of land surface. The correct mapping of the pixel positions to ground locations largely contributes to the success of the applications. Accurate geometric correction, also referred to as “orthorectification”, is thus an important prerequisite which must be performed prior to using airborne imagery for evaluations like change detection, or mapping or overlaying the imagery with existing data sets or maps. A so-called “ortho-image” provides an accurate representation of the earth’s surface, having been adjusted for lens distortions, camera tilt and topographic relief. In this paper, we describe the different steps in the geometric correction process of APEX hyperspectral data, as applied in the Central Data Processing Center (CDPC at the Flemish Institute for Technological Research (VITO, Mol, Belgium. APEX ortho-images are generated through direct georeferencing of the raw images, thereby making use of sensor interior and exterior orientation data, boresight calibration data and elevation data. They can be referenced to any userspecified output projection system and can be resampled to any output pixel size.

  1. APEX - the Hyperspectral ESA Airborne Prism Experiment

    Koen Meuleman


    Full Text Available The airborne ESA-APEX (Airborne Prism Experiment hyperspectral mission simulator is described with its distinct specifications to provide high quality remote sensing data. The concept of an automatic calibration, performed in the Calibration Home Base (CHB by using the Control Test Master (CTM, the In-Flight Calibration facility (IFC, quality flagging (QF and specific processing in a dedicated Processing and Archiving Facility (PAF, and vicarious calibration experiments are presented. A preview on major applications and the corresponding development efforts to provide scientific data products up to level 2/3 to the user is presented for limnology, vegetation, aerosols, general classification routines and rapid mapping tasks. BRDF (Bidirectional Reflectance Distribution Function issues are discussed and the spectral database SPECCHIO (Spectral Input/Output introduced. The optical performance as well as the dedicated software utilities make APEX a state-of-the-art hyperspectral sensor, capable of (a satisfying the needs of several research communities and (b helping the understanding of the Earth’s complex mechanisms.

  2. A novel capacitive absolute positioning sensor based on time grating with nanometer resolution

    Pu, Hongji; Liu, Hongzhong; Liu, Xiaokang; Peng, Kai; Yu, Zhicheng


    The present work proposes a novel capacitive absolute positioning sensor based on time grating. The sensor includes a fine incremental-displacement measurement component combined with a coarse absolute-position measurement component to obtain high-resolution absolute positioning measurements. A single row type sensor was proposed to achieve fine displacement measurement, which combines the two electrode rows of a previously proposed double-row type capacitive displacement sensor based on time grating into a single row. To achieve absolute positioning measurement, the coarse measurement component is designed as a single-row type displacement sensor employing a single spatial period over the entire measurement range. In addition, this component employs a rectangular induction electrode and four groups of orthogonal discrete excitation electrodes with half-sinusoidal envelope shapes, which were formed by alternately extending the rectangular electrodes of the fine measurement component. The fine and coarse measurement components are tightly integrated to form a compact absolute positioning sensor. A prototype sensor was manufactured using printed circuit board technology for testing and optimization of the design in conjunction with simulations. Experimental results show that the prototype sensor achieves a ±300 nm measurement accuracy with a 1 nm resolution over a displacement range of 200 mm when employing error compensation. The proposed sensor is an excellent alternative to presently available long-range absolute nanometrology sensors owing to its low cost, simple structure, and ease of manufacturing.

  3. Sub-nanometer-resolution imaging of peptide nanotubes in water using frequency modulation atomic force microscopy

    Sugihara, Tomoki; Hayashi, Itsuho; Onishi, Hiroshi [Department of Chemistry, Graduate School of Science, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501 (Japan); Kimura, Kenjiro, E-mail: [Department of Chemistry, Graduate School of Science, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501 (Japan); Tamura, Atsuo [Department of Chemistry, Graduate School of Science, Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe 657-8501 (Japan)


    Highlights: ► Peptide nanotubes were aligned on highly oriented pyrolytic graphite surface. ► We visualized sub-nanometer-scale structure on peptide nanotube surface in water. ► We observed hydration structure at a peptide nanotube/water interface. - Abstract: Peptide nanotubes are self-assembled fibrous materials composed of cyclic polypeptides. Recently, various aspects of peptide nanotubes have been studied, in particular the utility of different methods for making peptide nanotubes with diverse designed functions. In order to investigate the relationship between formation, function and stability, it is essential to analyze the precise structure of peptide nanotubes. Atomic-scale surface imaging in liquids was recently achieved using frequency modulation atomic force microscopy with improved force sensing. Here we provide a precise surface structural analysis of peptide nanotubes in water without crystallizing them obtained by imaging the nanotubes at the sub-nanometer scale in water. In addition, the local hydration structure around the peptide nanotubes was observed at the nanotube/water interface.

  4. Nanometer-resolution electron microscopy through micrometers-thick water layers

    Jonge, Niels de, E-mail: [Vanderbilt University Medical Center, Department of Molecular Physiology and Biophysics, Nashville, TN 37232-0615 (United States); Oak Ridge National Laboratory, Materials Science and Technology Division, Oak Ridge, TN 37831-6064 (United States); Poirier-Demers, Nicolas; Demers, Hendrix [Universite de Sherbrooke, Electrical and Computer Engineering, Sherbrooke, Quebec J1K 2R1 (Canada); Peckys, Diana B. [Oak Ridge National Laboratory, Materials Science and Technology Division, Oak Ridge, TN 37831-6064 (United States); University of Tennessee, Center for Environmental Biotechnology, Knoxville, TN 37996-1605 (United States); Drouin, Dominique [Universite de Sherbrooke, Electrical and Computer Engineering, Sherbrooke, Quebec J1K 2R1 (Canada)


    Scanning transmission electron microscopy (STEM) was used to image gold nanoparticles on top of and below saline water layers of several micrometers thickness. The smallest gold nanoparticles studied had diameters of 1.4 nm and were visible for a liquid thickness of up to 3.3 {mu}m. The imaging of gold nanoparticles below several micrometers of liquid was limited by broadening of the electron probe caused by scattering of the electron beam in the liquid. The experimental data corresponded to analytical models of the resolution and of the electron probe broadening as function of the liquid thickness. The results were also compared with Monte Carlo simulations of the STEM imaging on modeled specimens of similar geometry and composition as used for the experiments. Applications of STEM imaging in liquid can be found in cell biology, e.g., to study tagged proteins in whole eukaryotic cells in liquid and in materials science to study the interaction of solid:liquid interfaces at the nanoscale.

  5. Helium Ion Microscopy (HIM) for the imaging of biological samples at sub-nanometer resolution

    Joens, Matthew S.; Huynh, Chuong; Kasuboski, James M.; Ferranti, David; Sigal, Yury J.; Zeitvogel, Fabian; Obst, Martin; Burkhardt, Claus J.; Curran, Kevin P.; Chalasani, Sreekanth H.; Stern, Lewis A.; Goetze, Bernhard; Fitzpatrick, James A. J.


    Scanning Electron Microscopy (SEM) has long been the standard in imaging the sub-micrometer surface ultrastructure of both hard and soft materials. In the case of biological samples, it has provided great insights into their physical architecture. However, three of the fundamental challenges in the SEM imaging of soft materials are that of limited imaging resolution at high magnification, charging caused by the insulating properties of most biological samples and the loss of subtle surface features by heavy metal coating. These challenges have recently been overcome with the development of the Helium Ion Microscope (HIM), which boasts advances in charge reduction, minimized sample damage, high surface contrast without the need for metal coating, increased depth of field, and 5 angstrom imaging resolution. We demonstrate the advantages of HIM for imaging biological surfaces as well as compare and contrast the effects of sample preparation techniques and their consequences on sub-nanometer ultrastructure.

  6. Hyperspectral stimulated emission depletion microscopy and methods of use thereof

    Timlin, Jerilyn A; Aaron, Jesse S


    A hyperspectral stimulated emission depletion ("STED") microscope system for high-resolution imaging of samples labeled with multiple fluorophores (e.g., two to ten fluorophores). The hyperspectral STED microscope includes a light source, optical systems configured for generating an excitation light beam and a depletion light beam, optical systems configured for focusing the excitation and depletion light beams on a sample, and systems for collecting and processing data generated by interaction of the excitation and depletion light beams with the sample. Hyperspectral STED data may be analyzed using multivariate curve resolution analysis techniques to deconvolute emission from the multiple fluorophores. The hyperspectral STED microscope described herein can be used for multi-color, subdiffraction imaging of samples (e.g., materials and biological materials) and for analyzing a tissue by Forster Resonance Energy Transfer ("FRET").

  7. Hyperspectral imaging for non-contact analysis of forensic traces

    Edelman, G. J.; Gaston, E.; van Leeuwen, T. G.; Cullen, P. J.; Aalders, M. C. G.


    Hyperspectral imaging (HSI) integrates conventional imaging and spectroscopy, to obtain both spatial and spectral information from a specimen. This technique enables investigators to analyze the chemical composition of traces and simultaneously visualize their spatial distribution. HSI offers

  8. Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

    Ochilov, S.; Alam, M. S.; Bal, A.


    Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

  9. Upconversion applied for mid-IR hyperspectral image acquisition

    Tidemand-Lichtenberg, Peter; Kehlet, Louis Martinus; Sanders, Nicolai Højer


    Different schemes for upconversion mid-IR hyperspectral imaging is implemented and compared in terms of spectral coverage, spectral resolution, speed and noise. Phasematch scanning and scanning of the object within the field of view is considered....

  10. A survey of landmine detection using hyperspectral imaging

    Makki, Ihab; Younes, Rafic; Francis, Clovis; Bianchi, Tiziano; Zucchetti, Massimo


    Hyperspectral imaging is a trending technique in remote sensing that finds its application in many different areas, such as agriculture, mapping, target detection, food quality monitoring, etc. This technique gives the ability to remotely identify the composition of each pixel of the image. Therefore, it is a natural candidate for the purpose of landmine detection, thanks to its inherent safety and fast response time. In this paper, we will present the results of several studies that employed hyperspectral imaging for the purpose of landmine detection, discussing the different signal processing techniques used in this framework for hyperspectral image processing and target detection. Our purpose is to highlight the progresses attained in the detection of landmines using hyperspectral imaging and to identify possible perspectives for future work, in order to achieve a better detection in real-time operation mode.

  11. Hyperspectral image classification based on local binary patterns and PCANet

    Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang


    Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

  12. Parallel Hyperspectral Image Processing on Distributed Multi-Cluster Systems

    Liu, F.; Seinstra, F.J.; Plaza, A.J.


    Computationally efficient processing of hyperspectral image cubes can be greatly beneficial in many application domains, including environmental modeling, risk/hazard prevention and response, and defense/security. As individual cluster computers often cannot satisfy the computational demands of

  13. Automated Feature Extraction from Hyperspectral Imagery, Phase II

    National Aeronautics and Space Administration — The proposed activities will result in the development of a novel hyperspectral feature-extraction toolkit that will provide a simple, automated, and accurate...

  14. Automated Feature Extraction from Hyperspectral Imagery, Phase I

    National Aeronautics and Space Administration — In response to NASA Topic S7.01, Visual Learning Systems, Inc. (VLS) will develop a novel hyperspectral plug-in toolkit for its award winning Feature AnalystREG...

  15. Dental caries imaging using hyperspectral stimulated Raman scattering microscopy

    Wang, Zi; Zheng, Wei; Jian, Lin; Huang, Zhiwei


    We report the development of a polarization-resolved hyperspectral stimulated Raman scattering (SRS) imaging technique based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of dental caries. In our imaging system, hyperspectral SRS images (512×512 pixels) in both fingerprint region (800-1800 cm-1) and high-wavenumber region (2800-3600 cm-1) are acquired in minutes by scanning the wavelength of OPO output, which is a thousand times faster than conventional confocal micro Raman imaging. SRS spectra variations from normal enamel to caries obtained from the hyperspectral SRS images show the loss of phosphate and carbonate in the carious region. While polarization-resolved SRS images at 959 cm-1 demonstrate that the caries has higher depolarization ratio. Our results demonstrate that the polarization resolved-hyperspectral SRS imaging technique developed allows for rapid identification of the biochemical and structural changes of dental caries.

  16. Processing of hyperspectral medical images applications in dermatology using Matlab

    Koprowski, Robert


    This book presents new methods of analyzing and processing hyperspectral medical images, which can be used in diagnostics, for example for dermatological images. The algorithms proposed are fully automatic and the results obtained are fully reproducible. Their operation was tested on a set of several thousands of hyperspectral images and they were implemented in Matlab. The presented source code can be used without licensing restrictions. This is a valuable resource for computer scientists, bioengineers, doctoral students, and dermatologists interested in contemporary analysis methods.


    W. Pervez


    Full Text Available Rapid advancement in remote sensing open new avenues to explore the hyperspectral Hyperion imagery pre-processing techniques, analysis and application for land use mapping. The hyperspectral data consists of 242 bands out of which 196 calibrated/useful bands are available for hyperspectral applications. Atmospheric correction applied to the hyperspectral calibrated bands make the data more useful for its further processing/ application. Principal component (PC analysis applied to the hyperspectral calibrated bands reduced the dimensionality of the data and it is found that 99% of the data is held in first 10 PCs. Feature extraction is one of the important application by using vegetation delineation and normalized difference vegetation index. The machine learning classifiers uses the technique to identify the pixels having significant difference in the spectral signature which is very useful for classification of an image. Supervised machine learning classifier technique has been used for classification of hyperspectral image which resulted in overall efficiency of 86.6703 and Kappa co-efficient of 0.7998.

  18. Passive magnetic bearing configurations

    Post, Richard F [Walnut Creek, CA


    A journal bearing provides vertical and radial stability to a rotor of a passive magnetic bearing system when the rotor is not rotating and when it is rotating. In the passive magnetic bearing system, the rotor has a vertical axis of rotation. Without the journal bearing, the rotor is vertically and radially unstable when stationary, and is vertically stable and radially unstable when rotating.

  19. Infrared hyperspectral imaging miniaturized for UAV applications

    Hinnrichs, Michele; Hinnrichs, Bradford; McCutchen, Earl


    Pacific Advanced Technology (PAT) has developed an infrared hyperspectral camera, both MWIR and LWIR, small enough to serve as a payload on a miniature unmanned aerial vehicles. The optical system has been integrated into the cold-shield of the sensor enabling the small size and weight of the sensor. This new and innovative approach to infrared hyperspectral imaging spectrometer uses micro-optics and will be explained in this paper. The micro-optics are made up of an area array of diffractive optical elements where each element is tuned to image a different spectral region on a common focal plane array. The lenslet array is embedded in the cold-shield of the sensor and actuated with a miniature piezo-electric motor. This approach enables rapid infrared spectral imaging with multiple spectral images collected and processed simultaneously each frame of the camera. This paper will present our optical mechanical design approach which results in an infrared hyper-spectral imaging system that is small enough for a payload on a mini-UAV or commercial quadcopter. Also, an example of how this technology can easily be used to quantify a hydrocarbon gas leak's volume and mass flowrates. The diffractive optical elements used in the lenslet array are blazed gratings where each lenslet is tuned for a different spectral bandpass. The lenslets are configured in an area array placed a few millimeters above the focal plane and embedded in the cold-shield to reduce the background signal normally associated with the optics. We have developed various systems using a different number of lenslets in the area array. Depending on the size of the focal plane and the diameter of the lenslet array will determine the spatial resolution. A 2 x 2 lenslet array will image four different spectral images of the scene each frame and when coupled with a 512 x 512 focal plane array will give spatial resolution of 256 x 256 pixel each spectral image. Another system that we developed uses a 4 x 4

  20. Passive solar construction handbook

    Levy, E.; Evans, D.; Gardstein, C.


    Many of the basic elements of passive solar design are reviewed. The unique design constraints presented in passive homes are introduced and many of the salient issues influencing design decisions are described briefly. Passive solar construction is described for each passive system type: direct gain, thermal storage wall, attached sunspace, thermal storage roof, and convective loop. For each system type, important design and construction issues are discussed and case studies illustrating designed and built examples of the system type are presented. Construction details are given and construction and thermal performance information is given for the materials used in collector components, storage components, and control components. Included are glazing materials, framing systems, caulking and sealants, concrete masonry, concrete, brick, shading, reflectors, and insulators. The Load Collector Ratio method for estimating passive system performance is appended, and other analysis methods are briefly summarized. (LEW)

  1. Hyperspectral Longwave Infrared Focal Plane Array and Camera Based on Quantum Well Infrared Photodetectors, Phase I

    National Aeronautics and Space Administration — We propose to develop a hyperspectral focal plane array and camera imaging in a large number of sharp hyperspectral bands in the thermal infrared. The camera is...

  2. Manifold learning based feature extraction for classification of hyper-spectral data

    Lunga, D


    Full Text Available Advances in hyperspectral sensing provide new capability for characterizing spectral signatures in a wide range of physical and biological systems, while inspiring new methods for extracting information from these data. Hyperspectral image data...

  3. Detection of environmental change using hyperspectral remote sensing at Olkiluoto repository site

    Tuominen, J.; Lipping, T.


    In this report methods related to hyperspectral monitoring of Olkiluoto repository site are described. A short introduction to environmental remote sensing is presented, followed by more detailed description of hyperspectral imaging and a review of applications of hyperspectral remote sensing presented in the literature. The trends of future hyperspectral imaging are discussed exploring the possibilities of long-wave infrared hyperspectral imaging. A detailed description of HYPE08 hyperspectral flight campaign at the Olkiluoto region in 2008 is presented. In addition, related pre-processing and atmospheric correction methods, necessary in monitoring use, and the quality control methods applied, are described. Various change detection methods presented in the literature are described, too. Finally, a system for hyperspectral monitoring is proposed. The system is based on continued hyperspectral airborne flight campaigns and precisely defined data processing procedure. (orig.)

  4. A lightweight hyperspectral mapping system and photogrammetric processing chain for unmanned aerial vehicles

    Suomalainen, J.M.; Anders, N.S.; Iqbal, S.; Roerink, G.J.; Franke, G.J.; Wenting, P.F.M.; Hünniger, D.; Bartholomeus, H.; Becker, R.; Kooistra, L.


    During the last years commercial hyperspectral imaging sensors have been miniaturized and their performance has been demonstrated on Unmanned Aerial Vehicles (UAV). However currently the commercial hyperspectral systems still require minimum payload capacity of approximately 3 kg, forcing usage of

  5. Band Subset Selection for Hyperspectral Image Classification

    Chunyan Yu


    Full Text Available This paper develops a new approach to band subset selection (BSS for hyperspectral image classification (HSIC which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS, rather than one band at a time sequentially, referred to as sequential multiple band selection (SQMBS, as most traditional band selection methods do. In doing so, a criterion is particularly developed for BSS that can be used for HSIC. It is a linearly constrained minimum variance (LCMV derived from adaptive beamforming in array signal processing which can be used to model misclassification errors as the minimum variance. To avoid an exhaustive search for all possible band subsets, two numerical algorithms, referred to as sequential (SQ and successive (SC algorithms are also developed for LCMV-based SMMBS, called SQ LCMV-BSS and SC LCMV-BSS. Experimental results demonstrate that LCMV-based BSS has advantages over SQMBS.

  6. Hyperspectral Image Classification Using Discriminative Dictionary Learning

    Zongze, Y; Hao, S; Kefeng, J; Huanxin, Z


    The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

  7. Recent applications of hyperspectral imaging in microbiology.

    Gowen, Aoife A; Feng, Yaoze; Gaston, Edurne; Valdramidis, Vasilis


    Hyperspectral chemical imaging (HSI) is a broad term encompassing spatially resolved spectral data obtained through a variety of modalities (e.g. Raman scattering, Fourier transform infrared microscopy, fluorescence and near-infrared chemical imaging). It goes beyond the capabilities of conventional imaging and spectroscopy by obtaining spatially resolved spectra from objects at spatial resolutions varying from the level of single cells up to macroscopic objects (e.g. foods). In tandem with recent developments in instrumentation and sampling protocols, applications of HSI in microbiology have increased rapidly. This article gives a brief overview of the fundamentals of HSI and a comprehensive review of applications of HSI in microbiology over the past 10 years. Technical challenges and future perspectives for these techniques are also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Hyperspectral remote sensing for light pollution monitoring

    P. Marcoionni


    Full Text Available industries. In this paper we introduce the results from a remote sensing campaign performed in September 2001 at night time. For the first time nocturnal light pollution was measured at high spatial and spectral resolution using two airborne hyperspectral sensors, namely the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS and the Visible InfraRed Scanner (VIRS-200. These imagers, generally employed for day-time Earth remote sensing, were flown over the Tuscany coast (Italy on board of a Casa 212/200 airplane from an altitude of 1.5-2.0 km. We describe the experimental activities which preceded the remote sensing campaign, the optimization of sensor configuration, and the images as far acquired. The obtained results point out the novelty of the performed measurements and highlight the need to employ advanced remote sensing techniques as a spectroscopic tool for light pollution monitoring.

  9. Metric Learning for Hyperspectral Image Segmentation

    Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca


    We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

  10. Interest point detection for hyperspectral imagery

    Dorado-Muñoz, Leidy P.; Vélez-Reyes, Miguel; Roysam, Badrinath; Mukherjee, Amit


    This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature.

  11. Passivity and Evolutionary Game Dynamics

    Park, Shinkyu; Shamma, Jeff S.; Martins, Nuno C.


    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  12. Passivity and Evolutionary Game Dynamics

    Park, Shinkyu


    This paper investigates an energy conservation and dissipation -- passivity -- aspect of dynamic models in evolutionary game theory. We define a notion of passivity using the state-space representation of the models, and we devise systematic methods to examine passivity and to identify properties of passive dynamic models. Based on the methods, we describe how passivity is connected to stability in population games and illustrate stability of passive dynamic models using numerical simulations.

  13. Aktiv kontra passiv forvaltning

    Bechmann, Ken L.; Pedersen, Lasse Heje


    Fordele og ulemper ved aktiv og passiv forvaltning har fået fornyet opmærksomhed blandt andet i forbindelse med den forestående implementering af MiFID II. Som bidrag til denne diskussion indeholder dette nummer af Finans/Invest tre artikler, der behandler aktiv og passiv forvaltning fra...... forskellige vinkler. Denne leder forklarer, hvorfor valget mellem aktiv og passiv forvaltning er mere kompliceret, end hvad man kunne tro ved første øjekast, og konkluderer, at der vil være plads til - og behov for - begge typer forvaltning....

  14. Most energetic passive states.

    Perarnau-Llobet, Martí; Hovhannisyan, Karen V; Huber, Marcus; Skrzypczyk, Paul; Tura, Jordi; Acín, Antonio


    Passive states are defined as those states that do not allow for work extraction in a cyclic (unitary) process. Within the set of passive states, thermal states are the most stable ones: they maximize the entropy for a given energy, and similarly they minimize the energy for a given entropy. Here we find the passive states lying in the other extreme, i.e., those that maximize the energy for a given entropy, which we show also minimize the entropy when the energy is fixed. These extremal properties make these states useful to obtain fundamental bounds for the thermodynamics of finite-dimensional quantum systems, which we show in several scenarios.

  15. Techniques for active passivation

    Roscioli, Joseph R.; Herndon, Scott C.; Nelson, Jr., David D.


    In one embodiment, active (continuous or intermittent) passivation may be employed to prevent interaction of sticky molecules with interfaces inside of an instrument (e.g., an infrared absorption spectrometer) and thereby improve response time. A passivation species may be continuously or intermittently applied to an inlet of the instrument while a sample gas stream is being applied. The passivation species may have a highly polar functional group that strongly binds to either water or polar groups of the interfaces, and once bound presents a non-polar group to the gas phase in order to prevent further binding of polar molecules. The instrument may be actively used to detect the sticky molecules while the passivation species is being applied.

  16. Passive radon daughter dosimeters

    McElroy, R.G.C.; Johnson, J.R.


    On the basis of an extensive review of the recent literature concerning passive radon daughter dosimeters, we have reached the following conclusions: 1) Passive dosimeters for measuring radon are available and reliable. 2) There does not presently exist an acceptable passive dosimeter for radon daughters. There is little if any hope for the development of such a device in the foreseeable future. 3) We are pessimistic about the potential of 'semi-passive dosimeters' but are less firm about stating categorically that these devices cannot be developed into a useful radon daughter dosimeter. This report documents and justifies these conclusions. It does not address the question of the worker's acceptance of these devices because at the present time, no device is sufficiently advanced for this question to be meaningful. 118 refs

  17. Passive Mixing inside Microdroplets

    Chengmin Chen


    Full Text Available Droplet-based micromixers are essential units in many microfluidic devices for widespread applications, such as diagnostics and synthesis. The mixers can be either passive or active. When compared to active methods, the passive mixer is widely used because it does not require extra energy input apart from the pump drive. In recent years, several passive droplet-based mixers were developed, where mixing was characterized by both experiments and simulation. A unified physical understanding of both experimental processes and simulation models is beneficial for effectively developing new and efficient mixing techniques. This review covers the state-of-the-art passive droplet-based micromixers in microfluidics, which mainly focuses on three aspects: (1 Mixing parameters and analysis method; (2 Typical mixing element designs and the mixing characters in experiments; and, (3 Comprehensive introduction of numerical models used in microfluidic flow and diffusion.

  18. CANDU passive shutdown systems

    Hart, R S; Olmstead, R A [AECL CANDU, Sheridan Park Research Community, Mississauga, ON (Canada)


    CANDU incorporates two diverse, passive shutdown systems, independent of each other and from the reactor regulating system. Both shutdown systems function in the low pressure, low temperature, moderator which surrounds the fuel channels. The shutdown systems are functionally different, physically separate, and passive since the driving force for SDS1 is gravity and the driving force for SDS2 is stored energy. The physics of the reactor core itself ensures a degree of passive safety in that the relatively long prompt neutron generation time inherent in the design of CANDU reactors tend to retard power excursions and reduces the speed required for shutdown action, even for large postulated reactivity increases. All passive systems include a number of active components or initiators. Hence, an important aspect of passive systems is the inclusion of fail safe (activated by active component failure) operation. The mechanisms that achieve the fail safe action should be passive. Consequently the passive performance of the CANDU shutdown systems extends beyond their basic modes of operation to include fail safe operation based on natural phenomenon or stored energy. For example, loss of power to the SDS1 clutches results in the drop of the shutdown rods by gravity, loss of power or instrument air to the injection valves of SDS2 results in valve opening via spring action, and rigorous self checking of logic, data and timing by the shutdown systems computers assures a fail safe reactor trip through the collapse of a fluctuating magnetic field or the discharge of a capacitor. Event statistics from operating CANDU stations indicate a significant decrease in protection system faults that could lead to loss of production and elimination of protection system faults that could lead to loss of protection. This paper provides a comprehensive description of the passive shutdown systems employed by CANDU. (author). 4 figs, 3 tabs.


    X. Yang


    Full Text Available Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

  20. Information Extraction in Tomb Pit Using Hyperspectral Data

    Yang, X.; Hou, M.; Lyu, S.; Ma, S.; Gao, Z.; Bai, S.; Gu, M.; Liu, Y.


    Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

  1. Secure and Efficient Transmission of Hyperspectral Images for Geosciences Applications

    Carpentieri, Bruno; Pizzolante, Raffaele


    Hyperspectral images are acquired through air-borne or space-borne special cameras (sensors) that collect information coming from the electromagnetic spectrum of the observed terrains. Hyperspectral remote sensing and hyperspectral images are used for a wide range of purposes: originally, they were developed for mining applications and for geology because of the capability of this kind of images to correctly identify various types of underground minerals by analysing the reflected spectrums, but their usage has spread in other application fields, such as ecology, military and surveillance, historical research and even archaeology. The large amount of data obtained by the hyperspectral sensors, the fact that these images are acquired at a high cost by air-borne sensors and that they are generally transmitted to a base, makes it necessary to provide an efficient and secure transmission protocol. In this paper, we propose a novel framework that allows secure and efficient transmission of hyperspectral images, by combining a reversible invisible watermarking scheme, used in conjunction with digital signature techniques, and a state-of-art predictive-based lossless compression algorithm.

  2. The Possibility of Passive Whale Tracking With the Use of An Hyperspectral Sensor

    Barnes, Christina


    ...) Sensor to detect and recognize whales. This paper gives a detailed discussion of the sensor, describes the spectral image processing used to detect and enhance the whale images, provides sample imagery products, and finally discusses...



    Education and Training Command in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Jacob A. Martin, B.S, M.S. Civilian...such as estimating the thickness of a thin film of material on a bulk substrate, but these are outside the scope of this project and thus won’t be

  4. Real-time progressive hyperspectral image processing endmember finding and anomaly detection

    Chang, Chein-I


    The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new concepts of real time hyperspectral image processing, Progressive Hyperspectral Imaging (PHSI) and Recursive Hyperspectral Imaging (RHSI). Both of these can be used to design algorithms and also form an integral part of real time hyperpsectral image processing. This book focuses on progressive nature in algorithms on their real-time and causal processing implementation in two major applications, endmember finding and anomaly detection, both of which are fundamental tasks in hyperspectral imaging but generally not encountered in multispectral imaging. This book is written to particularly address PHSI in real time processing, while a book, Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation (Springer 2016) can be considered as its companion book. Includes preliminary background which is essential to those who work in hyperspectral ima...

  5. Passive House Solutions

    Strom, I.; Joosten, L.; Boonstra, C. [DHV Sustainability Consultants, Eindhoiven (Netherlands)


    PEP stands for 'Promotion of European Passive Houses' and is a consortium of European partners, supported by the European Commission, Directorate General for Energy and Transport. In this working paper an overview is given of Passive House solutions. An inventory has been made of Passive House solutions for new build residences applied in each country. Based on this, the most common basic solutions have been identified and described in further detail, including the extent to which solutions are applied in common and best practice and expected barriers for the implementation in each country. An inventory per country is included in the appendix. The analysis of Passive House solutions in partner countries shows high priority with regard to the performance of the thermal envelope, such as high insulation of walls, roofs, floors and windows/ doors, thermal bridge-free construction and air tightness. Due to the required air tightness, special attention must be paid to indoor air quality through proper ventilation. Finally, efficient ((semi-)solar) heating systems for combined space and DHW heating still require a significant amount of attention in most partner countries. Other basic Passive House solutions show a smaller discrepancy with common practice and fewer barriers have been encountered in partner countries. In the next section, the general barriers in partner countries have been inventoried. For each type of barrier a suggested approach has been given. Most frequently encountered barriers in partner countries are: limited know-how; limited contractor skills; and acceptation of Passive Houses in the market. Based on the suggested approaches to overcoming barriers, this means that a great deal of attention must be paid to providing practical information and solutions to building professionals, providing practical training to installers and contractors and communication about the Passive House concept to the market.

  6. A Novel Measurement Matrix Optimization Approach for Hyperspectral Unmixing

    Su Xu


    Full Text Available Each pixel in the hyperspectral unmixing process is modeled as a linear combination of endmembers, which can be expressed in the form of linear combinations of a number of pure spectral signatures that are known in advance. However, the limitation of Gaussian random variables on its computational complexity or sparsity affects the efficiency and accuracy. This paper proposes a novel approach for the optimization of measurement matrix in compressive sensing (CS theory for hyperspectral unmixing. Firstly, a new Toeplitz-structured chaotic measurement matrix (TSCMM is formed by pseudo-random chaotic elements, which can be implemented by a simple hardware; secondly, rank revealing QR factorization with eigenvalue decomposition is presented to speed up the measurement time; finally, orthogonal gradient descent method for measurement matrix optimization is used to achieve optimal incoherence. Experimental results demonstrate that the proposed approach can lead to better CS reconstruction performance with low extra computational cost in hyperspectral unmixing.

  7. Parallel computation for blood cell classification in medical hyperspectral imagery

    Li, Wei; Wu, Lucheng; Qiu, Xianbo; Ran, Qiong; Xie, Xiaoming


    With the advantage of fine spectral resolution, hyperspectral imagery provides great potential for cell classification. This paper provides a promising classification system including the following three stages: (1) band selection for a subset of spectral bands with distinctive and informative features, (2) spectral-spatial feature extraction, such as local binary patterns (LBP), and (3) followed by an effective classifier. Moreover, these three steps are further implemented on graphics processing units (GPU) respectively, which makes the system real-time and more practical. The GPU parallel implementation is compared with the serial implementation on central processing units (CPU). Experimental results based on real medical hyperspectral data demonstrate that the proposed system is able to offer high accuracy and fast speed, which are appealing for cell classification in medical hyperspectral imagery. (paper)

  8. A system design for storing, archiving, and retrieving hyperspectral data

    Dedecker, Ralph G.; Whittaker, Tom; Garcia, Raymond K.; Knuteson, Robert O.


    Hyperspectral data and products derived from instrumentation such as the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the GOES-R Hyperspectral Environmental Suite (HES) will impose storage and data retrieval requirements that far exceed the demands of earlier generation remote sensing instrumentation used for atmospheric science research. A new architecture designed to address projected real time and research needs is undergoing prototype design and development. The system is designed using proven aspects of distributed data storage networks, descriptive metadata associated with stored files, data cataloging and database search schemes, and a data delivery approach that obeys accepted standards. Preliminary implementation and testing of some components of this architecture indicate that the design approach shows promise of an improved method for storage and library functionality for the data volumes associated with operational hyperspectral instrumentation.

  9. High-resolution hyperspectral ground mapping for robotic vision

    Neuhaus, Frank; Fuchs, Christian; Paulus, Dietrich


    Recently released hyperspectral cameras use large, mosaiced filter patterns to capture different ranges of the light's spectrum in each of the camera's pixels. Spectral information is sparse, as it is not fully available in each location. We propose an online method that avoids explicit demosaicing of camera images by fusing raw, unprocessed, hyperspectral camera frames inside an ego-centric ground surface map. It is represented as a multilayer heightmap data structure, whose geometry is estimated by combining a visual odometry system with either dense 3D reconstruction or 3D laser data. We use a publicly available dataset to show that our approach is capable of constructing an accurate hyperspectral representation of the surface surrounding the vehicle. We show that in many cases our approach increases spatial resolution over a demosaicing approach, while providing the same amount of spectral information.

  10. Spatial and temporal variability of hyperspectral signatures of terrain

    Jones, K. F.; Perovich, D. K.; Koenig, G. G.


    Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

  11. Hyperspectral Cubesat Constellation for Rapid Natural Hazard Response

    Mandl, D.; Huemmrich, K. F.; Ly, V. T.; Handy, M.; Ong, L.; Crum, G.


    With the advent of high performance space networks that provide total coverage for Cubesats, the paradigm for low cost, high temporal coverage with hyperspectral instruments becomes more feasible. The combination of ground cloud computing resources, high performance with low power consumption onboard processing, total coverage for the cubesats and social media provide an opprotunity for an architecture that provides cost-effective hyperspectral data products for natural hazard response and decision support. This paper provides a series of pathfinder efforts to create a scalable Intelligent Payload Module(IPM) that has flown on a variety of airborne vehicles including Cessna airplanes, Citation jets and a helicopter and will fly on an Unmanned Aerial System (UAS) hexacopter to monitor natural phenomena. The IPM's developed thus far were developed on platforms that emulate a satellite environment which use real satellite flight software, real ground software. In addition, science processing software has been developed that perform hyperspectral processing onboard using various parallel processing techniques to enable creation of onboard hyperspectral data products while consuming low power. A cubesat design was developed that is low cost and that is scalable to larger consteallations and thus can provide daily hyperspectral observations for any spot on earth. The design was based on the existing IPM prototypes and metrics that were developed over the past few years and a shrunken IPM that can perform up to 800 Mbps throughput. Thus this constellation of hyperspectral cubesats could be constantly monitoring spectra with spectral angle mappers after Level 0, Level 1 Radiometric Correction, Atmospheric Correction processing. This provides the opportunity daily monitoring of any spot on earth on a daily basis at 30 meter resolution which is not available today.

  12. Measure Guideline: Passive Vents

    Berger, David [Consortium for Advanced Residential Buildings, Norwalk, CT (United States); Neri, Robin [Consortium for Advanced Residential Buildings, Norwalk, CT (United States)


    This document addresses the use of passive vents as a source of outdoor air in multifamily buildings. The challenges associated with implementing passive vents and the factors affecting performance are outlined. A comprehensive design methodology and quantified performance metrics are provided. Two hypothetical design examples are provided to illustrate the process. This document is intended to be useful to designers, decision-makers, and contractors implementing passive ventilation strategies. It is also intended to be a resource for those responsible for setting high-performance building program requirements, especially pertaining to ventilation and outdoor air. To ensure good indoor air quality, a dedicated source of outdoor air is an integral part of high-performance buildings. Presently, there is a lack of guidance pertaining to the design and installation of passive vents, resulting in poor system performance. This report details the criteria necessary for designing, constructing, and testing passive vent systems to enable them to provide consistent and reliable levels of ventilation air from outdoors.

  13. An Unsupervised Deep Hyperspectral Anomaly Detector

    Ning Ma


    Full Text Available Hyperspectral image (HSI based detection has attracted considerable attention recently in agriculture, environmental protection and military applications as different wavelengths of light can be advantageously used to discriminate different types of objects. Unfortunately, estimating the background distribution and the detection of interesting local objects is not straightforward, and anomaly detectors may give false alarms. In this paper, a Deep Belief Network (DBN based anomaly detector is proposed. The high-level features and reconstruction errors are learned through the network in a manner which is not affected by previous background distribution assumption. To reduce contamination by local anomalies, adaptive weights are constructed from reconstruction errors and statistical information. By using the code image which is generated during the inference of DBN and modified by adaptively updated weights, a local Euclidean distance between under test pixels and their neighboring pixels is used to determine the anomaly targets. Experimental results on synthetic and recorded HSI datasets show the performance of proposed method outperforms the classic global Reed-Xiaoli detector (RXD, local RX detector (LRXD and the-state-of-the-art Collaborative Representation detector (CRD.

  14. Unmixing hyperspectral images using Markov random fields

    Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves


    This paper proposes a new spectral unmixing strategy based on the normal compositional model that exploits the spatial correlations between the image pixels. The pure materials (referred to as endmembers) contained in the image are assumed to be available (they can be obtained by using an appropriate endmember extraction algorithm), while the corresponding fractions (referred to as abundances) are estimated by the proposed algorithm. Due to physical constraints, the abundances have to satisfy positivity and sum-to-one constraints. The image is divided into homogeneous distinct regions having the same statistical properties for the abundance coefficients. The spatial dependencies within each class are modeled thanks to Potts-Markov random fields. Within a Bayesian framework, prior distributions for the abundances and the associated hyperparameters are introduced. A reparametrization of the abundance coefficients is proposed to handle the physical constraints (positivity and sum-to-one) inherent to hyperspectral imagery. The parameters (abundances), hyperparameters (abundance mean and variance for each class) and the classification map indicating the classes of all pixels in the image are inferred from the resulting joint posterior distribution. To overcome the complexity of the joint posterior distribution, Markov chain Monte Carlo methods are used to generate samples asymptotically distributed according to the joint posterior of interest. Simulations conducted on synthetic and real data are presented to illustrate the performance of the proposed algorithm.

  15. MWIR hyperspectral imaging with the MIDAS instrument

    Honniball, Casey I.; Wright, Rob; Lucey, Paul G.


    Hyperspectral imaging (HSI) in the Mid-Wave InfraRed (MWIR, 3-5 microns) can provide information on a variety of science applications from determining the chemical composition of lava lakes on Jupiter's moon Io, to investigating the amount of carbon liberated into the Earth's atmosphere during a wildfire. The limited signal available in the MWIR presents technical challenges to achieving high signal-to-noise ratios, and therefore it is typically necessary to cryogenically cool MWIR instruments. With recent improvements in microbolometer technology and emerging interferometric techniques, we have shown that uncooled microbolometers coupled with a Sagnac interferometer can achieve high signal-to-noise ratios for long-wave infrared HSI. To explore if this technique can be applied to the MWIR, this project, with funding from NASA, has built the Miniaturized Infrared Detector of Atmospheric Species (MIDAS). Standard characterization tests are used to compare MIDAS against a cryogenically cooled photon detector to evaluate the MIDAS instruments' ability to quantify gas concentrations. Atmospheric radiative transfer codes are in development to explore the limitations of MIDAS and identify the range of science objectives that MIDAS will most likely excel at. We will simulate science applications with gas cells filled with varying gas concentrations and varying source temperatures to verify our results from lab characterization and our atmospheric modeling code.

  16. Evaluation of Algorithms for Compressing Hyperspectral Data

    Cook, Sid; Harsanyi, Joseph; Faber, Vance


    With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

  17. Hyperspectral aerosol optical depths from TCAP flights

    Shinozuka, Yohei [NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States); Bay Area Environmental REsearch Institute; Johnson, Roy R [NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States); Flynn, Connor J [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Russell, Philip B [NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States); Schmid, Beat [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)


    4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research), a hyperspectral airborne sunphotometer, acquired aerosol optical depths (AOD) at 1 Hz during all July 2012 flights of the Two Column Aerosol Project (TCAP). Root-mean-square differences from AERONET ground-based observations were 0.01 at wavelengths between 500-1020 nm, 0.02 at 380 and 1640 nm and 0.03 at 440 nm in four clear-sky fly-over events, and similar in ground side-by-side comparisons. Changes in the above-aircraft AOD across 3- km-deep spirals were typically consistent with integrals of coincident in situ (on DOE Gulfstream 1 with 4STAR) and lidar (on NASA B200) extinction measurements within 0.01, 0.03, 0.01, 0.02, 0.02, 0.02 at 355, 450, 532, 550, 700, 1064 nm, respectively, despite atmospheric variations and combined measurement uncertainties. Finer vertical differentials of the 4STAR measurements matched the in situ ambient extinction profile within 14% for one homogeneous column. For the AOD observed between 350-1660 nm, excluding strong

  18. Resolving Mixed Algal Species in Hyperspectral Images

    Mehrube Mehrubeoglu


    Full Text Available We investigated a lab-based hyperspectral imaging system’s response from pure (single and mixed (two algal cultures containing known algae types and volumetric combinations to characterize the system’s performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert’s law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements.

  19. High Throughput System for Plant Height and Hyperspectral Measurement

    Zhao, H.; Xu, L.; Jiang, H.; Shi, S.; Chen, D.


    Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV) extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

  20. Detecting brain tumor in pathological slides using hyperspectral imaging.

    Ortega, Samuel; Fabelo, Himar; Camacho, Rafael; de la Luz Plaza, María; Callicó, Gustavo M; Sarmiento, Roberto


    Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides.

  1. Bread Water Content Measurement Based on Hyperspectral Imaging

    Liu, Zhi; Møller, Flemming


    Water content is one of the most important properties of the bread for tasting assesment or store monitoring. Traditional bread water content measurement methods mostly are processed manually, which is destructive and time consuming. This paper proposes an automated water content measurement...... for bread quality based on near-infrared hyperspectral imaging against the conventional manual loss-in-weight method. For this purpose, the hyperspectral components unmixing technology is used for measuring the water content quantitatively. And the definition on bread water content index is presented...

  2. Hyperspectral imaging using the single-pixel Fourier transform technique

    Jin, Senlin; Hui, Wangwei; Wang, Yunlong; Huang, Kaicheng; Shi, Qiushuai; Ying, Cuifeng; Liu, Dongqi; Ye, Qing; Zhou, Wenyuan; Tian, Jianguo


    Hyperspectral imaging technology is playing an increasingly important role in the fields of food analysis, medicine and biotechnology. To improve the speed of operation and increase the light throughput in a compact equipment structure, a Fourier transform hyperspectral imaging system based on a single-pixel technique is proposed in this study. Compared with current imaging spectrometry approaches, the proposed system has a wider spectral range (400-1100 nm), a better spectral resolution (1 nm) and requires fewer measurement data (a sample rate of 6.25%). The performance of this system was verified by its application to the non-destructive testing of potatoes.


    H. Zhao


    Full Text Available Hyperspectral and three-dimensional measurement can obtain the intrinsic physicochemical properties and external geometrical characteristics of objects, respectively. Currently, a variety of sensors are integrated into a system to collect spectral and morphological information in agriculture. However, previous experiments were usually performed with several commercial devices on a single platform. Inadequate registration and synchronization among instruments often resulted in mismatch between spectral and 3D information of the same target. And narrow field of view (FOV extends the working hours in farms. Therefore, we propose a high throughput prototype that combines stereo vision and grating dispersion to simultaneously acquire hyperspectral and 3D information.

  4. Constructing passive houses

    Oehler, S. [Oehler Faigle Archkom Solar Architektur, Bretten (Germany)


    Everybody can learn to build energy-efficient. It needs theoretical and practical experience. 1997 we built the first freestanding Passive House in Europe, the Passive House Oehler. There had been a lot of questions, starting with the insecurity, whether the calculation program of the Passive House Institute, the PHPP, is working properly in our case. Nobody knew at that time because nobody tried it out before. It took us a lot of time to find out and every detail of the construction hat to be invented to meet the very high demand of thermal quality. All the following houses needed less time and had fewer open questions, adding one piece of experience with every building. 2002 we realised the biggest Passive House, the office building Energon Ulm with 420 working spaces. In the meantime we have learned a lot like how to produce prefabricated timber elements for the facades, providing good insulation, air tightness and avoiding serious thermal bridges. We have proofed, that any kind of building type can be a Passive House. And with increasing experience the freedom of design and construction is growing. Even the economical efficiency increased. The Energon Ulm is providing a much better indoor climate than any other office building and was build 10 % cheaper than an average German office building. At present the Passive House Standard is the most efficient solution for the user to live in the desired comfort zone between 20 C and 25 C. This zone of individual feeling-well can be described with the term ''operative temperature''. This term is defined by factors like air temperature, radiation temperature of warm and cold surfaces, air speed and humidity. The result of all these factors has to be within 18 C to 25 C without accepting one of the factors getting extreme.

  5. Passive containment system

    Kleimola, F.W.


    Disclosed is a containment system that provides complete protection entirely by passive means for the loss of coolant accident in a nuclear power plant and wherein all stored energy released in the coolant blowdown is contained and absorbed while the nuclear fuel is prevented from over-heating by a high containment back-pressure and a reactor vessel refill system. The primary containment vessel is restored to a high sub-atmospheric pressure within a few minutes after accident initiation and the decay heat is safely transferred to the environment while radiolytic hydrogen is contained by passive means. 20 claims, 14 figures

  6. Wireless passive radiation sensor

    Pfeifer, Kent B; Rumpf, Arthur N; Yelton, William G; Limmer, Steven J


    A novel measurement technique is employed using surface acoustic wave (SAW) devices, passive RF, and radiation-sensitive films to provide a wireless passive radiation sensor that requires no batteries, outside wiring, or regular maintenance. The sensor is small (<1 cm.sup.2), physically robust, and will operate unattended for decades. In addition, the sensor can be insensitive to measurement position and read distance due to a novel self-referencing technique eliminating the need to measure absolute responses that are dependent on RF transmitter location and power.

  7. Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

    Julie Transon


    Full Text Available In the last few decades, researchers have developed a plethora of hyperspectral Earth Observation (EO remote sensing techniques, analysis and applications. While hyperspectral exploratory sensors are demonstrating their potential, Sentinel-2 multispectral satellite remote sensing is now providing free, open, global and systematic high resolution visible and infrared imagery at a short revisit time. Its recent launch suggests potential synergies between multi- and hyper-spectral data. This study, therefore, reviews 20 years of research and applications in satellite hyperspectral remote sensing through the analysis of Earth observation hyperspectral sensors’ publications that cover the Sentinel-2 spectrum range: Hyperion, TianGong-1, PRISMA, HISUI, EnMAP, Shalom, HyspIRI and HypXIM. More specifically, this study (i brings face to face past and future hyperspectral sensors’ applications with Sentinel-2’s and (ii analyzes the applications’ requirements in terms of spatial and temporal resolutions. Eight main application topics were analyzed including vegetation, agriculture, soil, geology, urban, land use, water resources and disaster. Medium spatial resolution, long revisit time and low signal-to-noise ratio in the short-wave infrared of some hyperspectral sensors were highlighted as major limitations for some applications compared to the Sentinel-2 system. However, these constraints mainly concerned past hyperspectral sensors, while they will probably be overcome by forthcoming instruments. Therefore, this study is putting forward the compatibility of hyperspectral sensors and Sentinel-2 systems for resolution enhancement techniques in order to increase the panel of hyperspectral uses.

  8. Hyperspectral image reconstruction using RGB color for foodborne pathogen detection on agar plates

    Yoon, Seung-Chul; Shin, Tae-Sung; Park, Bosoon; Lawrence, Kurt C.; Heitschmidt, Gerald W.


    This paper reports the latest development of a color vision technique for detecting colonies of foodborne pathogens grown on agar plates with a hyperspectral image classification model that was developed using full hyperspectral data. The hyperspectral classification model depended on reflectance spectra measured in the visible and near-infrared spectral range from 400 and 1,000 nm (473 narrow spectral bands). Multivariate regression methods were used to estimate and predict hyperspectral data from RGB color values. The six representative non-O157 Shiga-toxin producing Eschetichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) were grown on Rainbow agar plates. A line-scan pushbroom hyperspectral image sensor was used to scan 36 agar plates grown with pure STEC colonies at each plate. The 36 hyperspectral images of the agar plates were divided in half to create training and test sets. The mean Rsquared value for hyperspectral image estimation was about 0.98 in the spectral range between 400 and 700 nm for linear, quadratic and cubic polynomial regression models and the detection accuracy of the hyperspectral image classification model with the principal component analysis and k-nearest neighbors for the test set was up to 92% (99% with the original hyperspectral images). Thus, the results of the study suggested that color-based detection may be viable as a multispectral imaging solution without much loss of prediction accuracy compared to hyperspectral imaging.

  9. Passiv-Sammler

    Fritsche, U.


    The invention relates to a passive collector for air pollution for the determination of emission rates for dry and wet deposits on construction materials such as natural stone, whereby the collector has a surrogate surface of the stone under investigation, the surrogate surface being linked to a collecting vessel such that any dry or wet contamination occurring can be collected.

  10. Passive houses in Norway

    Halse, Andreas


    The paper analyzes the introduction of passive houses in the Norwegian house market. Passive houses are houses with extremely low levels of energy consumption for heating, and have not yet been built in Norway, but have started to enter the market in Germany and some other countries. The construction sector is analyzed as a sectoral innovation system. The different elements of the innovation system are studied. This includes government agencies, producers, consumers, finance and education. The analysis shows that passive and low-energy houses are on the verge of market breakthrough. This can partly be explained by economic calculations, and partly by processes of learning and change in the institutional set-up of the sector. The construction sector is a sector characterized by low innovative intensity and little interaction between different agents. Those working to promote passive houses have to some extent managed to cope with these challenges. This has happened by breaking away from the traditional focus of Norwegian energy efficiency policies on technology and the economically rational agents, by instead focusing on knowledge and institutional change at the level of the producers. (Author)

  11. Hood River Passive House

    Hales, David [BA-PIRC, Spokane, WA (United States)


    The Hood River Passive Project was developed by Root Design Build of Hood River Oregon using the Passive House Planning Package (PHPP) to meet all of the requirements for certification under the European Passive House standards. The Passive House design approach has been gaining momentum among residential designers for custom homes and BEopt modeling indicates that these designs may actually exceed the goal of the U.S. Department of Energy's (DOE) Building America program to "reduce home energy use by 30%-50% (compared to 2009 energy codes for new homes). This report documents the short term test results of the Shift House and compares the results of PHPP and BEopt modeling of the project. The design includes high R-Value assemblies, extremely tight construction, high performance doors and windows, solar thermal DHW, heat recovery ventilation, moveable external shutters and a high performance ductless mini-split heat pump. Cost analysis indicates that many of the measures implemented in this project did not meet the BA standard for cost neutrality. The ductless mini-split heat pump, lighting and advanced air leakage control were the most cost effective measures. The future challenge will be to value engineer the performance levels indicated here in modeling using production based practices at a significantly lower cost.

  12. Passive THz metamaterials

    Lavrinenko, Andrei; Malureanu, Radu; Zalkovskij, Maksim


    In this work we present our activities in the fabrication and characterization of passive THz metamaterials. We use two fabrication processes to develop metamaterials either as free-standing metallic membranes or patterned metallic multi-layers on the substrates to achieve different functionalities...

  13. Improved Scanners for Microscopic Hyperspectral Imaging

    Mao, Chengye


    Improved scanners to be incorporated into hyperspectral microscope-based imaging systems have been invented. Heretofore, in microscopic imaging, including spectral imaging, it has been customary to either move the specimen relative to the optical assembly that includes the microscope or else move the entire assembly relative to the specimen. It becomes extremely difficult to control such scanning when submicron translation increments are required, because the high magnification of the microscope enlarges all movements in the specimen image on the focal plane. To overcome this difficulty, in a system based on this invention, no attempt would be made to move either the specimen or the optical assembly. Instead, an objective lens would be moved within the assembly so as to cause translation of the image at the focal plane: the effect would be equivalent to scanning in the focal plane. The upper part of the figure depicts a generic proposed microscope-based hyperspectral imaging system incorporating the invention. The optical assembly of this system would include an objective lens (normally, a microscope objective lens) and a charge-coupled-device (CCD) camera. The objective lens would be mounted on a servomotor-driven translation stage, which would be capable of moving the lens in precisely controlled increments, relative to the camera, parallel to the focal-plane scan axis. The output of the CCD camera would be digitized and fed to a frame grabber in a computer. The computer would store the frame-grabber output for subsequent viewing and/or processing of images. The computer would contain a position-control interface board, through which it would control the servomotor. There are several versions of the invention. An essential feature common to all versions is that the stationary optical subassembly containing the camera would also contain a spatial window, at the focal plane of the objective lens, that would pass only a selected portion of the image. In one version

  14. Hyperspectral remote sensing of wild oyster reefs

    Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent


    The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal


    Abdi Sukmono


    Full Text Available Klorofil merupakan pigmen yang paling penting dalam proses fotosintesis. Tanaman sehat yang mampu tumbuh maksimum umumnya  memiliki jumlah klorofil yang lebih besar daripada tanaman yang tidak sehat. Dalam Estimasi kandungan klorofil tanaman padi dengan airborne hyperspectral dibutuhkan algoritma khusus untuk mendaaptkan akurasi yang baik. Objek dari penelitian ini mengembangkan reflektan in situ menjadi model algoritma   estimasi kandungan klorofil tanaman padi untuk airborne hyperspectral.  Dalam penelitian ini beberapa indeks vegetasi seperti normalized difference vegetation index (NDVI, modified simple ratio (MSR  , modified/transformed chlorophyll absorption ratio index (MCARI, TCARI dan bentuk integrasi (MCARI/OSAVI and TCARI/OSAVI digunakan untuk membentuk model estimasi dengan metode regresi linear. Selain itu juga digunakan  Blue/Green/Yellow/Red Edge Absorption Clhorophyll Index. Dari proses regresi di dapatkan tiga ground model yang mempunyai korelasi kuat (R2≥0.5 terhadap klorofil tanaman padi. Ketiga model tersebut yaitu MSR (705,750 dengan R2 sebesar 0.51, TCARI/OSAVI (705, 750 dengan R2 sebesar 0.52 dan REACL 2 dengan R2 sebesar 0.57. Dari ketiga tersebut dipilih groun model terbaik REACL 2 untuk di upscalling ke model algoritma airborne hyperspectral.  Pembentukan algoritma dengan data airborne hyperspectral sensor Hymap dan REACL 2 menghasilkan model algoritma ( Klorofil (SPAD unit = 3.031((B22-B18/(B18-B13 + 31.596 dengan R2 sebesar 0.78

  16. Characterisation of a Tunisian coastal lagoon through hyperspectral ...

    In 2008 an optical procedure was developed and applied in Ghar El Melh, a Tunisian lagoon which has been increasingly impacted by pollutant loading, especially from agriculture. In situ hyperspectral irradiance was measured at several stations, from which the apparent optical properties (AOPs), namely the irradiance ...

  17. Objective Color Classification of Ecstasy Tablets by Hyperspectral Imaging

    Edelman, Gerda; Lopatka, Martin; Aalders, Maurice


    The general procedure followed in the examination of ecstasy tablets for profiling purposes includes a color description, which depends highly on the observers' perception. This study aims to provide objective quantitative color information using visible hyperspectral imaging. Both self-manufactured

  18. The challenges of analysing blood stains with hyperspectral imaging

    Kuula, J.; Puupponen, H.-H.; Rinta, H.; Pölönen, I.


    Hyperspectral imaging is a potential noninvasive technology for detecting, separating and identifying various substances. In the forensic and military medicine and other CBRNE related use it could be a potential method for analyzing blood and for scanning other human based fluids. For example, it would be valuable to easily detect whether some traces of blood are from one or more persons or if there are some irrelevant substances or anomalies in the blood. This article represents an experiment of separating four persons' blood stains on a white cotton fabric with a SWIR hyperspectral camera and FT-NIR spectrometer. Each tested sample includes standardized 75 _l of 100 % blood. The results suggest that on the basis of the amount of erythrocytes in the blood, different people's blood might be separable by hyperspectral analysis. And, referring to the indication given by erythrocytes, there might be a possibility to find some other traces in the blood as well. However, these assumptions need to be verified with wider tests, as the number of samples in the study was small. According to the study there also seems to be several biological, chemical and physical factors which affect alone and together on the hyperspectral analyzing results of blood on fabric textures, and these factors need to be considered before making any further conclusions on the analysis of blood on various materials.

  19. Hyperspectral remote sensing of canopy biodiversity in Hawaiian lowland rainforests

    Kimberly M. Carlson; Gregory P. Asner; R. Flint Hughes; Rebecca Ostertag; Roberta E. Martin


    Mapping biological diversity is a high priority for conservation research, management and policy development, but few studies have provided diversity data at high spatial resolution from remote sensing. We used airborne imaging spectroscopy to map woody vascular plant species richness in lowland tropical forest ecosystems in Hawaii. Hyperspectral signatures spanning...

  20. Bathymetry from fusion of airborne hyperspectral and laser data

    Kappus, Mary E.; Davis, Curtiss O.; Rhea, W. Joseph


    Airborne hyperspectral and nadir-viewing laser data can be combined to ascertain shallow water bathymetry. The combination emphasizes the advances and overcomes the disadvantages of each method used alone. For laser systems, both the hardware and software for obtaining off-nadir measurement are complicated and expensive, while for the nadir view the conversion of laser pulse travel time to depth is straightforward. The hyperspectral systems can easily collect data in a full swath, but interpretation for water depth requires careful calibration and correction for transmittance through the atmosphere and water. Relative depths are apparent in displays of several subsets of hyperspectral data, for example, single blue-green wavelengths, endmembers that represent the pure water component of the data, or ratios of deep to shallow water endmembers. A relationship between one of these values and the depth measured by the aligned nadir laser can be determined, and then applied to the rest of the swath to obtain depth in physical units for the entire area covered. We demonstrate this technique using bathymetric charts as a proxy for laser data, and hyperspectral data taken by AVIRIS over Lake Tahoe and Key West.

  1. Identifying saltcedar with hyperspectral data and support vector machines

    Saltcedar (Tamarix spp.) are a group of dense phreatophytic shrubs and trees that are invasive to riparian areas throughout the United States. This study determined the feasibility of using hyperspectral data and a support vector machine (SVM) classifier to discriminate saltcedar from other cover t...

  2. Biologically-inspired data decorrelation for hyper-spectral imaging

    Ghita Ovidiu


    Full Text Available Abstract Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA, linear discriminant analysis (LDA, wavelet decomposition (WD, or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

  3. Classification of Salmonella serotypes with hyperspectral microscope imagery

    Previous research has demonstrated an optical method with acousto-optic tunable filter (AOTF) based hyperspectral microscope imaging (HMI) had potential for classifying gram-negative from gram-positive foodborne pathogenic bacteria rapidly and nondestructively with a minimum sample preparation. In t...

  4. Hyperspectral Imaging Sensors and the Marine Coastal Zone

    Richardson, Laurie L.


    Hyperspectral imaging sensors greatly expand the potential of remote sensing to assess, map, and monitor marine coastal zones. Each pixel in a hyperspectral image contains an entire spectrum of information. As a result, hyperspectral image data can be processed in two very different ways: by image classification techniques, to produce mapped outputs of features in the image on a regional scale; and by use of spectral analysis of the spectral data embedded within each pixel of the image. The latter is particularly useful in marine coastal zones because of the spectral complexity of suspended as well as benthic features found in these environments. Spectral-based analysis of hyperspectral (AVIRIS) imagery was carried out to investigate a marine coastal zone of South Florida, USA. Florida Bay is a phytoplankton-rich estuary characterized by taxonomically distinct phytoplankton assemblages and extensive seagrass beds. End-member spectra were extracted from AVIRIS image data corresponding to ground-truth sample stations and well-known field sites. Spectral libraries were constructed from the AVIRIS end-member spectra and used to classify images using the Spectral Angle Mapper (SAM) algorithm, a spectral-based approach that compares the spectrum, in each pixel of an image with each spectrum in a spectral library. Using this approach different phytoplankton assemblages containing diatoms, cyanobacteria, and green microalgae, as well as benthic community (seagrasses), were mapped.

  5. Enabling Searches on Wavelengths in a Hyperspectral Indices Database

    Piñuela, F.; Cerra, D.; Müller, R.


    Spectral indices derived from hyperspectral reflectance measurements are powerful tools to estimate physical parameters in a non-destructive and precise way for several fields of applications, among others vegetation health analysis, coastal and deep water constituents, geology, and atmosphere composition. In the last years, several micro-hyperspectral sensors have appeared, with both full-frame and push-broom acquisition technologies, while in the near future several hyperspectral spaceborne missions are planned to be launched. This is fostering the use of hyperspectral data in basic and applied research causing a large number of spectral indices to be defined and used in various applications. Ad hoc search engines are therefore needed to retrieve the most appropriate indices for a given application. In traditional systems, query input parameters are limited to alphanumeric strings, while characteristics such as spectral range/ bandwidth are not used in any existing search engine. Such information would be relevant, as it enables an inverse type of search: given the spectral capabilities of a given sensor or a specific spectral band, find all indices which can be derived from it. This paper describes a tool which enables a search as described above, by using the central wavelength or spectral range used by a given index as a search parameter. This offers the ability to manage numeric wavelength ranges in order to select indices which work at best in a given set of wavelengths or wavelength ranges.

  6. Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

    Kong, Seong G.; Chen, Yud-Ren; Kim, Intaek; Kim, Moon S.


    We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.

  7. Recent Advances in Techniques for Hyperspectral Image Processing

    Plaza, Antonio; Benediktsson, Jon Atli; Boardman, Joseph W.; Brazile, Jason; Bruzzone, Lorenzo; Camps-Valls, Gustavo; Chanussot, Jocelyn; Fauvel, Mathieu; Gamba, Paolo; Gualtieri, Anthony; hide


    Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than 30 years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspectral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the highdimensional nature of the data, and to integrate the spatial and spectral information. Performance of the discussed techniques is evaluated in different analysis scenarios. To satisfy time-critical constraints in specific applications, we also develop efficient parallel implementations of some of the discussed algorithms. Combined, these parts provide an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on future potentials and emerging challenges in the design of robust hyperspectral imaging algorithms

  8. Hyperspectral Imaging of Forest Resources: The Malaysian Experience

    Mohd Hasmadi, I.; Kamaruzaman, J.


    Remote sensing using satellite and aircraft images are well established technology. Remote sensing application of hyperspectral imaging, however, is relatively new to Malaysian forestry. Through a wide range of wavelengths hyperspectral data are precisely capable to capture narrow bands of spectra. Airborne sensors typically offer greatly enhanced spatial and spectral resolution over their satellite counterparts, and able to control experimental design closely during image acquisition. The first study using hyperspectral imaging for forest inventory in Malaysia were conducted by Professor Hj. Kamaruzaman from the Faculty of Forestry, Universiti Putra Malaysia in 2002 using the AISA sensor manufactured by Specim Ltd, Finland. The main objective has been to develop methods that are directly suited for practical tropical forestry application at the high level of accuracy. Forest inventory and tree classification including development of single spectral signatures have been the most important interest at the current practices. Experiences from the studies showed that retrieval of timber volume and tree discrimination using this system is well and some or rather is better than other remote sensing methods. This article reviews the research and application of airborne hyperspectral remote sensing for forest survey and assessment in Malaysia.

  9. Remote sensing of soil moisture using airborne hyperspectral data

    The Institute for Technology Development (ITD) has developed an airborne hyperspectral sensor system that collects electromagnetic reflectance data of the terrain. The system consists of sensors for three different sections of the electromagnetic spectrum; the Ultra-Violet (UV), Visible/Near Infrare...

  10. a Hyperspectral Image Classification Method Using Isomap and Rvm

    Chang, H.; Wang, T.; Fang, H.; Su, Y.


    Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes' ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.

  11. Use of Aerial Hyperspectral Imaging For Monitoring Forest Health

    Milton O. Smith; Nolan J. Hess; Stephen Gulick; Lori G. Eckhardt; Roger D. Menard


    This project evaluates the effectiveness of aerial hyperspectral digital imagery in the assessment of forest health of loblolly stands in central Alabama. The imagery covers 50 square miles, in Bibb and Hale Counties, south of Tuscaloosa, AL, which includes intensive managed forest industry sites and National Forest lands with multiple use objectives. Loblolly stands...

  12. Infrared hyperspectral upconversion imaging using spatial object translation

    Kehlet, Louis Martinus; Sanders, Nicolai Højer; Tidemand-Lichtenberg, Peter


    In this paper hyperspectral imaging in the mid-infrared wavelength region is realised using nonlinear frequency upconversion. The infrared light is converted to the near-infrared region for detection with a Si-based CCD camera. The object is translated in a predefined grid by motorized actuators...

  13. Manifold regularization for sparse unmixing of hyperspectral images.

    Liu, Junmin; Zhang, Chunxia; Zhang, Jiangshe; Li, Huirong; Gao, Yuelin


    Recently, sparse unmixing has been successfully applied to spectral mixture analysis of remotely sensed hyperspectral images. Based on the assumption that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance, unmixing of each mixed pixel in the scene is to find an optimal subset of signatures in a very large spectral library, which is cast into the framework of sparse regression. However, traditional sparse regression models, such as collaborative sparse regression , ignore the intrinsic geometric structure in the hyperspectral data. In this paper, we propose a novel model, called manifold regularized collaborative sparse regression , by introducing a manifold regularization to the collaborative sparse regression model. The manifold regularization utilizes a graph Laplacian to incorporate the locally geometrical structure of the hyperspectral data. An algorithm based on alternating direction method of multipliers has been developed for the manifold regularized collaborative sparse regression model. Experimental results on both the simulated and real hyperspectral data sets have demonstrated the effectiveness of our proposed model.

  14. Passive ranging using a filter-based non-imaging method based on oxygen absorption.

    Yu, Hao; Liu, Bingqi; Yan, Zongqun; Zhang, Yu


    To solve the problem of poor real-time measurement caused by a hyperspectral imaging system and to simplify the design in passive ranging technology based on oxygen absorption spectrum, a filter-based non-imaging ranging method is proposed. In this method, three bandpass filters are used to obtain the source radiation intensities that are located in the oxygen absorption band near 762 nm and the band's left and right non-absorption shoulders, and a photomultiplier tube is used as the non-imaging sensor of the passive ranging system. Range is estimated by comparing the calculated values of band-average transmission due to oxygen absorption, τ O 2 , against the predicted curve of τ O 2 versus range. The method is tested under short-range conditions. Accuracy of 6.5% is achieved with the designed experimental ranging system at the range of 400 m.

  15. Intrinsically Passive Handling and Grasping

    Stramigioli, Stefano; Scherpen, Jacquelien M.A.; Khodabandehloo, Koorosh


    The paper presents a control philosophy called Intrinsically Passive Control, which has the feature to properly behave during interaction with any passive objects. The controlled robot will never become unstable due to the physical structure of the controller.

  16. Tunable thin-film optical filters for hyperspectral microscopy

    Favreau, Peter F.; Rich, Thomas C.; Prabhat, Prashant; Leavesley, Silas J.


    Hyperspectral imaging was originally developed for use in remote sensing applications. More recently, it has been applied to biological imaging systems, such as fluorescence microscopes. The ability to distinguish molecules based on spectral differences has been especially advantageous for identifying fluorophores in highly autofluorescent tissues. A key component of hyperspectral imaging systems is wavelength filtering. Each filtering technology used for hyperspectral imaging has corresponding advantages and disadvantages. Recently, a new optical filtering technology has been developed that uses multi-layered thin-film optical filters that can be rotated, with respect to incident light, to control the center wavelength of the pass-band. Compared to the majority of tunable filter technologies, these filters have superior optical performance including greater than 90% transmission, steep spectral edges and high out-of-band blocking. Hence, tunable thin-film optical filters present optical characteristics that may make them well-suited for many biological spectral imaging applications. An array of tunable thin-film filters was implemented on an inverted fluorescence microscope (TE 2000, Nikon Instruments) to cover the full visible wavelength range. Images of a previously published model, GFP-expressing endothelial cells in the lung, were acquired using a charge-coupled device camera (Rolera EM-C2, Q-Imaging). This model sample presents fluorescently-labeled cells in a highly autofluorescent environment. Linear unmixing of hyperspectral images indicates that thin-film tunable filters provide equivalent spectral discrimination to our previous acousto-optic tunable filter-based approach, with increased signal-to-noise characteristics. Hence, tunable multi-layered thin film optical filters may provide greatly improved spectral filtering characteristics and therefore enable wider acceptance of hyperspectral widefield microscopy.

  17. The French proposal for a high spatial resolution Hyperspectral mission

    Carrère, Véronique; Briottet, Xavier; Jacquemoud, Stéphane; Marion, Rodolphe; Bourguignon, Anne; Chami, Malik; Chanussot, Jocelyn; Chevrel, Stéphane; Deliot, Philippe; Dumont, Marie; Foucher, Pierre-Yves; Gomez, Cécile; Roman-Minghelli, Audrey; Sheeren, David; Weber, Christiane; Lefèvre, Marie-José; Mandea, Mioara


    More than 25 years of airborne imaging spectroscopy and spaceborne sensors such as Hyperion or HICO have clearly demonstrated the ability of such a remote sensing technique to produce value added information regarding surface composition and physical properties for a large variety of applications. Scheduled missions such as EnMAP and PRISMA prove the increased interest of the scientific community for such a type of remote sensing data. In France, a group of Science and Defence users of imaging spectrometry data (Groupe de Synthèse Hyperspectral, GSH) established an up-to-date review of possible applications, define instrument specifications required for accurate, quantitative retrieval of diagnostic parameters, and identify fields of application where imaging spectrometry is a major contribution. From these conclusions, CNES (French Space Agency) decided a phase 0 study for an hyperspectral mission concept, named at this time HYPXIM (HYPerspectral-X IMagery), the main fields of applications are vegetation biodiversity, coastal and inland waters, geosciences, urban environment, atmospheric sciences, cryosphere and Defence. Results pointed out applications where high spatial resolution was necessary and would not be covered by the other foreseen hyperspectral missions. The phase A started at the beginning of 2013 based on the following HYPXIM characteristics: a hyperspectral camera covering the [0.4 - 2.5 µm] spectral range with a 8 m ground sampling distance (GSD) and a PAN camera with a 1.85 m GSD, onboard a mini-satellite platform. This phase A is currently stopped due to budget constraints. Nevertheless, the Science team is currently focusing on the preparation for the next CNES prospective meeting (March, 2014), an important step for the future of the mission. This paper will provide an update of the status of this mission and of new results obtained by the Science team.

  18. Colorectal cancer detection by hyperspectral imaging using fluorescence excitation scanning

    Leavesley, Silas J.; Deal, Joshua; Hill, Shante; Martin, Will A.; Lall, Malvika; Lopez, Carmen; Rider, Paul F.; Rich, Thomas C.; Boudreaux, Carole W.


    Hyperspectral imaging technologies have shown great promise for biomedical applications. These techniques have been especially useful for detection of molecular events and characterization of cell, tissue, and biomaterial composition. Unfortunately, hyperspectral imaging technologies have been slow to translate to clinical devices - likely due to increased cost and complexity of the technology as well as long acquisition times often required to sample a spectral image. We have demonstrated that hyperspectral imaging approaches which scan the fluorescence excitation spectrum can provide increased signal strength and faster imaging, compared to traditional emission-scanning approaches. We have also demonstrated that excitation-scanning approaches may be able to detect spectral differences between colonic adenomas and adenocarcinomas and normal mucosa in flash-frozen tissues. Here, we report feasibility results from using excitation-scanning hyperspectral imaging to screen pairs of fresh tumoral and nontumoral colorectal tissues. Tissues were imaged using a novel hyperspectral imaging fluorescence excitation scanning microscope, sampling a wavelength range of 360-550 nm, at 5 nm increments. Image data were corrected to achieve a NIST-traceable flat spectral response. Image data were then analyzed using a range of supervised and unsupervised classification approaches within ENVI software (Harris Geospatial Solutions). Supervised classification resulted in >99% accuracy for single-patient image data, but only 64% accuracy for multi-patient classification (n=9 to date), with the drop in accuracy due to increased false-positive detection rates. Hence, initial data indicate that this approach may be a viable detection approach, but that larger patient sample sizes need to be evaluated and the effects of inter-patient variability studied.

  19. Real-time recursive hyperspectral sample and band processing algorithm architecture and implementation

    Chang, Chein-I


    This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016. Explores recursive structures in algorithm architecture Implements algorithmic recursive architecture in conjunction with progressive sample and band processing Derives Recursive Hyperspectral Sample Processing (RHSP) techniques according to Band-Interleaved Sample/Pixel (BIS/BIP) acquisition format Develops Recursive Hyperspectral Band Processing (RHBP) techniques according to Band SeQuential (BSQ) acquisition format for hyperspectral data.

  20. a Novel Deep Convolutional Neural Network for Spectral-Spatial Classification of Hyperspectral Data

    Li, N.; Wang, C.; Zhao, H.; Gong, X.; Wang, D.


    Spatial and spectral information are obtained simultaneously by hyperspectral remote sensing. Joint extraction of these information of hyperspectral image is one of most import methods for hyperspectral image classification. In this paper, a novel deep convolutional neural network (CNN) is proposed, which extracts spectral-spatial information of hyperspectral images correctly. The proposed model not only learns sufficient knowledge from the limited number of samples, but also has powerful generalization ability. The proposed framework based on three-dimensional convolution can extract spectral-spatial features of labeled samples effectively. Though CNN has shown its robustness to distortion, it cannot extract features of different scales through the traditional pooling layer that only have one size of pooling window. Hence, spatial pyramid pooling (SPP) is introduced into three-dimensional local convolutional filters for hyperspectral classification. Experimental results with a widely used hyperspectral remote sensing dataset show that the proposed model provides competitive performance.

  1. Survey of Hyperspectral Earth Observation Applications from Space in the Sentinel-2 Context

    Julie Transon; Raphaël d’Andrimont; Alexandre Maugnard; Pierre Defourny


    In the last few decades, researchers have developed a plethora of hyperspectral Earth Observation (EO) remote sensing techniques, analysis and applications. While hyperspectral exploratory sensors are demonstrating their potential, Sentinel-2 multispectral satellite remote sensing is now providing free, open, global and systematic high resolution visible and infrared imagery at a short revisit time. Its recent launch suggests potential synergies between multi- and hyper-spectral data. This st...

  2. SVM Classifiers: The Objects Identification on the Base of Their Hyperspectral Features

    Demidova Liliya


    Full Text Available The problem of the objects identification on the base of their hyperspectral features has been considered. It is offered to use the SVM classifiers on the base of the modified PSO algorithm, adapted to specifics of the problem of the objects identification on the base of their hyperspectral features. The results of the objects identification on the base of their hyperspectral features with using of the SVM classifiers have been presented.


    A. Roncat


    Full Text Available While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a make use of full-waveform information and (b operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA, i.e. the target surface. With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.

  4. Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

    Heasler, Patrick G.; Posse, Christian; Hylden, Jeff L.; Anderson, Kevin K.


    This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. This shows that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty.

  5. Passive solar heating

    Wiberg, K


    The present work treats the possibilities for heating according to the passive solar heating method. Problems of 'spatial organization in an energy-saving society' are distinguished from among other social problems. The final delimination of the actual problems under investigation consists of the use of passive solar heating and especially the 'consequences of such solar heating exploitation upon the form and structures' of planning and construction. In the concluding chapter an applied example shows how this method can be used in designing an urban area and what are its limitations. The results indicate the possibilities and difficulties in attempting to transfer this ideal and general method into models and directives for form and structure from which examples of the actual possibilities in practical planning can be given.

  6. Qademah Fault Passive Data

    Hanafy, Sherif M.


    OBJECTIVE: In this field trip we collect passive data to 1. Convert passive to surface waves 2. Locate Qademah fault using surface wave migration INTRODUCTION: In this field trip we collected passive data for several days. This data will be used to find the surface waves using interferometry and then compared to active-source seismic data collected at the same location. A total of 288 receivers are used. A 3D layout with 5 m inline intervals and 10 m cross line intervals is used, where we used 12 lines with 24 receivers at each line. You will need to download the file (rec_times.mat), it contains important information about 1. Field record no 2. Record day 3. Record month 4. Record hour 5. Record minute 6. Record second 7. Record length P.S. 1. All files are converted from original format (SEG-2) to matlab format P.S. 2. Overlaps between records (10 to 1.5 sec.) are already removed from these files

  7. Hyperspectral Soil Mapper (HYSOMA) software interface: Review and future plans

    Chabrillat, Sabine; Guillaso, Stephane; Eisele, Andreas; Rogass, Christian


    With the upcoming launch of the next generation of hyperspectral satellites that will routinely deliver high spectral resolution images for the entire globe (e.g. EnMAP, HISUI, HyspIRI, HypXIM, PRISMA), an increasing demand for the availability/accessibility of hyperspectral soil products is coming from the geoscience community. Indeed, many robust methods for the prediction of soil properties based on imaging spectroscopy already exist and have been successfully used for a wide range of soil mapping airborne applications. Nevertheless, these methods require expert know-how and fine-tuning, which makes them used sparingly. More developments are needed toward easy-to-access soil toolboxes as a major step toward the operational use of hyperspectral soil products for Earth's surface processes monitoring and modelling, to allow non-experienced users to obtain new information based on non-expensive software packages where repeatability of the results is an important prerequisite. In this frame, based on the EU-FP7 EUFAR (European Facility for Airborne Research) project and EnMAP satellite science program, higher performing soil algorithms were developed at the GFZ German Research Center for Geosciences as demonstrators for end-to-end processing chains with harmonized quality measures. The algorithms were built-in into the HYSOMA (Hyperspectral SOil MApper) software interface, providing an experimental platform for soil mapping applications of hyperspectral imagery that gives the choice of multiple algorithms for each soil parameter. The software interface focuses on fully automatic generation of semi-quantitative soil maps such as soil moisture, soil organic matter, iron oxide, clay content, and carbonate content. Additionally, a field calibration option calculates fully quantitative soil maps provided ground truth soil data are available. Implemented soil algorithms have been tested and validated using extensive in-situ ground truth data sets. The source of the HYSOMA

  8. Hyperspectral Imagery Target Detection Using Improved Anomaly Detection and Signature Matching Methods

    Smetek, Timothy E


    This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors...

  9. Concept research on general passive system

    Han Xu; Yang Yanhua; Zheng Mingguang


    This paper summarized the current passive techniques used in nuclear power plants. Through classification and analysis, the functional characteristics and inherent identification of passive systems were elucidated. By improving and extending the concept of passive system, the general passive concept was proposed, and space and time relativity was discussed and assumption of general passive system were illustrated. The function of idealized general passive system is equivalent with the current passive system, but the design of idealized general passive system is more flexible. (authors)

  10. 3D Spatial and Spectral Fusion of Terrestrial Hyperspectral Imagery and Lidar for Hyperspectral Image Shadow Restoration Applied to a Geologic Outcrop

    Hartzell, P. J.; Glennie, C. L.; Hauser, D. L.; Okyay, U.; Khan, S.; Finnegan, D. C.


    Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from an exclusively airborne technique to terrestrial modalities. This enables high resolution 3D spatial and spectral quantification of vertical geologic structures for applications such as virtual 3D rock outcrop models for hydrocarbon reservoir analog analysis and mineral quantification in open pit mining environments. In contrast to airborne observation geometry, the vertical surfaces observed by horizontal-viewing terrestrial HSI sensors are prone to extensive topography-induced solar shadowing, which leads to reduced pixel classification accuracy or outright removal of shadowed pixels from analysis tasks. Using a precisely calibrated and registered offset cylindrical linear array camera model, we demonstrate the use of 3D lidar data for sub-pixel HSI shadow detection and the restoration of the shadowed pixel spectra via empirical methods that utilize illuminated and shadowed pixels of similar material composition. We further introduce a new HSI shadow restoration technique that leverages collocated backscattered lidar intensity, which is resistant to solar conditions, obtained by projecting the 3D lidar points through the HSI camera model into HSI pixel space. Using ratios derived from the overlapping lidar laser and HSI wavelengths, restored shadow pixel spectra are approximated using a simple scale factor. Simulations of multiple lidar wavelengths, i.e., multi-spectral lidar, indicate the potential for robust HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance is quantified through HSI pixel classification consistency between full sun and partial sun exposures of a single geologic outcrop.

  11. The Hyperspectral Imager for the Coastal Ocean (HICO (trademark)) Provides a New View of the Coastal Ocean


    The calibrated data are then sent to NRL Stennis Space Center (NRL-SSC) for further processing using the NRL SSC Automated Processing System (APS...hyperspectral sensor in space we have not previously developed automated processing for hyperspectral ocean color data. The hyperspectral processing branch

  12. Support Vector Machines for Hyperspectral Remote Sensing Classification

    Gualtieri, J. Anthony; Cromp, R. F.


    The Support Vector Machine provides a new way to design classification algorithms which learn from examples (supervised learning) and generalize when applied to new data. We demonstrate its success on a difficult classification problem from hyperspectral remote sensing, where we obtain performances of 96%, and 87% correct for a 4 class problem, and a 16 class problem respectively. These results are somewhat better than other recent results on the same data. A key feature of this classifier is its ability to use high-dimensional data without the usual recourse to a feature selection step to reduce the dimensionality of the data. For this application, this is important, as hyperspectral data consists of several hundred contiguous spectral channels for each exemplar. We provide an introduction to this new approach, and demonstrate its application to classification of an agriculture scene.

  13. Hyperspectral optical imaging of two different species of lepidoptera

    Vukusic Pete


    Full Text Available Abstract In this article, we report a hyperspectral optical imaging application for measurement of the reflectance spectra of photonic structures that produce structural colors with high spatial resolution. The measurement of the spectral reflectance function is exemplified in the butterfly wings of two different species of Lepidoptera: the blue iridescence reflected by the nymphalid Morpho didius and the green iridescence of the papilionid Papilio palinurus. Color coordinates from reflectance spectra were calculated taking into account human spectral sensitivity. For each butterfly wing, the observed color is described by a characteristic color map in the chromaticity diagram and spreads over a limited volume in the color space. The results suggest that variability in the reflectance spectra is correlated with different random arrangements in the spatial distribution of the scales that cover the wing membranes. Hyperspectral optical imaging opens new ways for the non-invasive study and classification of different forms of irregularity in structural colors.

  14. Camouflage target detection via hyperspectral imaging plus information divergence measurement

    Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin


    Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.

  15. Overhead longwave infrared hyperspectral material identification using radiometric models

    Zelinski, M. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)


    Material detection algorithms used in hyperspectral data processing are computationally efficient but can produce relatively high numbers of false positives. Material identification performed as a secondary processing step on detected pixels can help separate true and false positives. This paper presents a material identification processing chain for longwave infrared hyperspectral data of solid materials collected from airborne platforms. The algorithms utilize unwhitened radiance data and an iterative algorithm that determines the temperature, humidity, and ozone of the atmospheric profile. Pixel unmixing is done using constrained linear regression and Bayesian Information Criteria for model selection. The resulting product includes an optimal atmospheric profile and full radiance material model that includes material temperature, abundance values, and several fit statistics. A logistic regression method utilizing all model parameters to improve identification is also presented. This paper details the processing chain and provides justification for the algorithms used. Several examples are provided using modeled data at different noise levels.

  16. A hyperspectral image analysis workbench for environmental science applications

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.


    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or ``hyperspectral`` imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne`s Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image ``texture spectra`` derived from fractal signatures computed for subimage tiles at each wavelength.

  17. A hyperspectral image analysis workbench for environmental science applications

    Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.; Slater, J.C.


    A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or hyperspectral'' imagery, for analysis, for mapping purposes, and for input to environmental modeling applications. As an initial response to this challenge, Argonne's Advanced Computer Applications Center has developed a workstation-based prototype software workbench which employs Al techniques and other advanced approaches to deduce surface characteristics and extract features from the hyperspectral images. Among its current capabilities, the prototype system can classify pixels by abstract surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image texture spectra'' derived from fractal signatures computed for subimage tiles at each wavelength.

  18. High-throughput optical system for HDES hyperspectral imager

    Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan


    Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

  19. Passive Power Filters

    Künzi, R.


    Power converters require passive low-pass filters which are capable of reducing voltage ripples effectively. In contrast to signal filters, the components of power filters must carry large currents or withstand large voltages, respectively. In this paper, three different suitable filter struc tures for d.c./d.c. power converters with inductive load are introduced. The formulas needed to calculate the filter components are derived step by step and practical examples are given. The behaviour of the three discussed filters is compared by means of the examples. P ractical aspects for the realization of power filters are also discussed.

  20. Hyperspectral Based Skin Detection for Person of Interest Identification


    short-wave infrared VIS visible spectrum PCA principal component analysis FCBF Fast Correlation- Based Filter POI person of interest ANN artificial artificial neural network (ANN) that is created in MATLAB® using the Neural Network Toolbox to identify a POI based on their skin spectral data. A...identifying a POI based on skin spectral data. She identified an optimal feature subset to be used with the hyperspectral data she collected using a

  1. Panchromatic cooperative hyperspectral adaptive wide band deletion repair method

    Jiang, Bitao; Shi, Chunyu


    In the hyperspectral data, the phenomenon of stripe deletion often occurs, which seriously affects the efficiency and accuracy of data analysis and application. Narrow band deletion can be directly repaired by interpolation, and this method is not ideal for wide band deletion repair. In this paper, an adaptive spectral wide band missing restoration method based on panchromatic information is proposed, and the effectiveness of the algorithm is verified by experiments.

  2. Classification of maize kernels using NIR hyperspectral imaging

    Williams, Paul; Kucheryavskiy, Sergey V.


    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

  3. Hyperspectral imaging as a diagnostic tool for chronic skin ulcers

    Denstedt, Martin; Pukstad, Brita S.; Paluchowski, Lukasz A.; Hernandez-Palacios, Julio E.; Randeberg, Lise L.


    The healing process of chronic wounds is complex, and the complete pathogenesis is not known. Diagnosis is currently based on visual inspection, biopsies and collection of samples from the wound surface. This is often time consuming, expensive and to some extent subjective procedures. Hyperspectral imaging has been shown to be a promising modality for optical diagnostics. The main objective of this study was to identify a suitable technique for reproducible classification of hyperspectral data from a wound and the surrounding tissue. Two statistical classification methods have been tested and compared to the performance of a dermatologist. Hyperspectral images (400-1000 nm) were collected from patients with venous leg ulcers using a pushbroom-scanning camera (VNIR 1600, Norsk Elektro Optikk AS).Wounds were examined regularly over 4 - 6 weeks. The patients were evaluated by a dermatologist at every appointment. One patient has been selected for presentation in this paper (female, age 53 years). The oxygen saturation of the wound area was determined by wavelength ratio metrics. Spectral angle mapping (SAM) and k-means clustering were used for classification. Automatic extraction of endmember spectra was employed to minimize human interaction. A comparison of the methods shows that k-means clustering is the most stable method over time, and shows the best overlap with the dermatologist's assessment of the wound border. The results are assumed to be affected by the data preprocessing and chosen endmember extraction algorithm. Results indicate that it is possible to develop an automated method for reliable classification of wounds based on hyperspectral data.

  4. Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection


    for matching biological spectra across a data base of hyperspectral pathology slides acquires with different instruments in different conditions, as...generalizing wavelets and similar scaling mechanisms. Plain Sight Systems, Inc. -7- Proprietary and Confidential To be specific, let the bi-Markov...remarkably well. Conventional nearest neighbor search , compared with a diffusion search. The data is a pathology slide ,each pixel is a digital

  5. Hyperspectral Imagery for Large Area Survey of Organophosphate Pesticides


    When the molecule is exposed to infrared radiation , the energy of these frequencies are absorbed. This is what created the unique spectral...medium. It has been used in the fields of food safety and quality, pharmaceuticals, and medical diagnostics and has potential for non-contact...forensic analysis. Hyperspectral imaging can be used for various parts of the electromagnetic spectrum (e.g. ultraviolet , visible, and infrared) (Edelmen

  6. Fast algorithm for exploring and compressing of large hyperspectral images

    Kucheryavskiy, Sergey


    A new method for calculation of latent variable space for exploratory analysis and dimension reduction of large hyperspectral images is proposed. The method is based on significant downsampling of image pixels with preservation of pixels’ structure in feature (variable) space. To achieve this, in...... can be used first of all for fast compression of large data arrays with principal component analysis or similar projection techniques....

  7. A hyperspectral image data exploration workbench for environmental science applications

    Woyna, M.A.; Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.


    The Hyperspectral Image Data Exploration Workbench (HIDEW) software system has been developed by Argonne National Laboratory to enable analysts at Unix workstations to conveniently access and manipulate high-resolution imagery data for analysis, mapping purposes, and input to environmental modeling applications. HIDEW is fully object-oriented, including the underlying database. This system was developed as an aid to site characterization work and atmospheric research projects

  8. Statistical Modeling of Natural Backgrounds in Hyperspectral LWIR Data


    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(6), 2337–2350 (2014). [4] Manolakis, D., Rossacci, M., Zhang, D... IEEE Signal Processing Magazine 31(1), 24–33 (2014). [2] Manolakis, D., Golowich, S., and DiPietro, R., “Long-wave infrared hyperspectral remote ... sensing of chemical clouds: A focus on signal processing approaches,” IEEE Signal Processing Magazine 31(4), 120–141 (2014). [3] Truslow, E.,

  9. A hyperspectral image data exploration workbench for environmental science applications

    Woyna, M.A.; Christiansen, J.H.; Zawada, D.G.; Simunich, K.L.


    The Hyperspectral Image Data Exploration Workbench (HIDEW) software system has been developed by Argonne National Laboratory to enable analysts at Unix workstations to conveniently access and manipulate high-resolution imagery data for analysis, mapping purposes, and input to environmental modeling applications. HIDEW is fully object-oriented, including the underlying database. This system was developed as an aid to site characterization work and atmospheric research projects.

  10. Expansion of passive safety function

    Inai, Nobuhiko; Nei, Hiromichi; Kumada, Toshiaki.


    Expansion of the use of passive safety functions is proposed. Two notions are presented. One is that, in the design of passive safety nuclear reactors where aversion of active components is stressed, some active components are purposely introduced, by which a system is built in such a way that it behaves in an apparently passive manner. The second notion is that, instead of using a passive safety function alone, a passive safety function is combined with some active components, relating the passivity in the safety function with enhanced controllability in normal operation. The nondormant system which the authors propose is one example of the first notion. This is a system in which a standby safety system is a portion of the normal operation system. An interpretation of the nondormant system via synergetics is made. As an example of the second notion, a PIUS density lock aided with active components is proposed and is discussed


    D. Akbari


    Full Text Available In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1 unsupervised feature extraction methods including principal component analysis (PCA, independent component analysis (ICA, and minimum noise fraction (MNF; (2 supervised feature extraction including decision boundary feature extraction (DBFE, discriminate analysis feature extraction (DAFE, and nonparametric weighted feature extraction (NWFE; (3 genetic algorithm (GA. The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

  12. Hyperspectral laser-induced autofluorescence imaging of dental caries

    Bürmen, Miran; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan


    Dental caries is a disease characterized by demineralization of enamel crystals leading to the penetration of bacteria into the dentine and pulp. Early detection of enamel demineralization resulting in increased enamel porosity, commonly known as white spots, is a difficult diagnostic task. Laser induced autofluorescence was shown to be a useful method for early detection of demineralization. The existing studies involved either a single point spectroscopic measurements or imaging at a single spectral band. In the case of spectroscopic measurements, very little or no spatial information is acquired and the measured autofluorescence signal strongly depends on the position and orientation of the probe. On the other hand, single-band spectral imaging can be substantially affected by local spectral artefacts. Such effects can significantly interfere with automated methods for detection of early caries lesions. In contrast, hyperspectral imaging effectively combines the spatial information of imaging methods with the spectral information of spectroscopic methods providing excellent basis for development of robust and reliable algorithms for automated classification and analysis of hard dental tissues. In this paper, we employ 405 nm laser excitation of natural caries lesions. The fluorescence signal is acquired by a state-of-the-art hyperspectral imaging system consisting of a high-resolution acousto-optic tunable filter (AOTF) and a highly sensitive Scientific CMOS camera in the spectral range from 550 nm to 800 nm. The results are compared to the contrast obtained by near-infrared hyperspectral imaging technique employed in the existing studies on early detection of dental caries.

  13. Reconstruction of hyperspectral image using matting model for classification

    Xie, Weiying; Li, Yunsong; Ge, Chiru


    Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.

  14. On the Atmospheric Correction of Antarctic Airborne Hyperspectral Data

    Martin Black


    Full Text Available The first airborne hyperspectral campaign in the Antarctic Peninsula region was carried out by the British Antarctic Survey and partners in February 2011. This paper presents an insight into the applicability of currently available radiative transfer modelling and atmospheric correction techniques for processing airborne hyperspectral data in this unique coastal Antarctic environment. Results from the Atmospheric and Topographic Correction version 4 (ATCOR-4 package reveal absolute reflectance values somewhat in line with laboratory measured spectra, with Root Mean Square Error (RMSE values of 5% in the visible near infrared (0.4–1 µm and 8% in the shortwave infrared (1–2.5 µm. Residual noise remains present due to the absorption by atmospheric gases and aerosols, but certain parts of the spectrum match laboratory measured features very well. This study demonstrates that commercially available packages for carrying out atmospheric correction are capable of correcting airborne hyperspectral data in the challenging environment present in Antarctica. However, it is anticipated that future results from atmospheric correction could be improved by measuring in situ atmospheric data to generate atmospheric profiles and aerosol models, or with the use of multiple ground targets for calibration and validation.

  15. SIBI: A compact hyperspectral camera in the mid-infrared

    Pola Fossi, Armande; Ferrec, Yann; Domel, Roland; Coudrain, Christophe; Guerineau, Nicolas; Roux, Nicolas; D'Almeida, Oscar; Bousquet, Marc; Kling, Emmanuel; Sauer, Hervé


    Recent developments in unmanned aerial vehicles have increased the demand for more and more compact optical systems. In order to bring solutions to this demand, several infrared systems are being developed at ONERA such as spectrometers, imaging devices, multispectral and hyperspectral imaging systems. In the field of compact infrared hyperspectral imaging devices, ONERA and Sagem Défense et Sécurité have collaborated to develop a prototype called SIBI, which stands for "Spectro-Imageur Birefringent Infrarouge". It is a static Fourier transform imaging spectrometer which operates in the mid-wavelength infrared spectral range and uses a birefringent lateral shearing interferometer. Up to now, birefringent interferometers have not been often used for hyperspectral imaging in the mid-infrared because of the lack of crystal manufacturers, contrary to the visible spectral domain where the production of uniaxial crystals like calcite are mastered for various optical applications. In the following, we will present the design and the realization of SIBI as well as the first experimental results.

  16. Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging.

    Mo, Changyeun; Kim, Giyoung; Lim, Jongguk; Kim, Moon S; Cho, Hyunjeong; Cho, Byoung-Kwan


    Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the 400-1000 nm wavelength range. The optimal wavebands for discriminating between discolored and sound lettuce surfaces were determined using one-way analysis of variance. Multi-spectral imaging algorithms developed using ratio and subtraction functions resulted in enhanced classification accuracy of above 99.9% for discolored and sound areas on both adaxial and abaxial lettuce surfaces. Ratio imaging (RI) and subtraction imaging (SI) algorithms at wavelengths of 552/701 nm and 557-701 nm, respectively, exhibited better classification performances compared to results obtained for all possible two-waveband combinations. These results suggest that hyperspectral reflectance imaging techniques can potentially be used to discriminate between discolored and sound fresh-cut lettuce.

  17. [Analysis of related factors of slope plant hyperspectral remote sensing].

    Sun, Wei-Qi; Zhao, Yun-Sheng; Tu, Lin-Ling


    In the present paper, the slope gradient, aspect, detection zenith angle and plant types were analyzed. In order to strengthen the theoretical discussion, the research was under laboratory condition, and modeled uniform slope for slope plant. Through experiments we found that these factors indeed have influence on plant hyperspectral remote sensing. When choosing slope gradient as the variate, the blade reflection first increases and then decreases as the slope gradient changes from 0° to 36°; When keeping other factors constant, and only detection zenith angle increasing from 0° to 60°, the spectral characteristic of slope plants do not change significantly in visible light band, but decreases gradually in near infrared band; With only slope aspect changing, when the dome meets the light direction, the blade reflectance gets maximum, and when the dome meets the backlit direction, the blade reflectance gets minimum, furthermore, setting the line of vertical intersection of incidence plane and the dome as an axis, the reflectance on the axis's both sides shows symmetric distribution; In addition, spectral curves of different plant types have a lot differences between each other, which means that the plant types also affect hyperspectral remote sensing results of slope plants. This research breaks through the limitations of the traditional vertical remote sensing data collection and uses the multi-angle and hyperspectral information to analyze spectral characteristics of slope plants. So this research has theoretical significance to the development of quantitative remote sensing, and has application value to the plant remote sensing monitoring.

  18. An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

    Akbari, D.


    In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

  19. Rapid hyperspectral image classification to enable autonomous search systems

    Raj Bridgelal


    Full Text Available The emergence of lightweight full-frame hyperspectral cameras is destined to enable autonomous search vehicles in the air, on the ground and in water. Self-contained and long-endurance systems will yield important new applications, for example, in emergency response and the timely identification of environmental hazards. One missing capability is rapid classification of hyperspectral scenes so that search vehicles can immediately take actions to verify potential targets. Onsite verifications minimise false positives and preclude the expense of repeat missions. Verifications will require enhanced image quality, which is achievable by either moving closer to the potential target or by adjusting the optical system. Such a solution, however, is currently impractical for small mobile platforms with finite energy sources. Rapid classifications with current methods demand large computing capacity that will quickly deplete the on-board battery or fuel. To develop the missing capability, the authors propose a low-complexity hyperspectral image classifier that approaches the performance of prevalent classifiers. This research determines that the new method will require at least 19-fold less computing capacity than the prevalent classifier. To assess relative performances, the authors developed a benchmark that compares a statistic of library endmember separability in their respective feature spaces.

  20. Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares

    Jianjun Liu


    Full Text Available As a widely used classifier, sparse representation classification (SRC has shown its good performance for hyperspectral image classification. Recent works have highlighted that it is the collaborative representation mechanism under SRC that makes SRC a highly effective technique for classification purposes. If the dimensionality and the discrimination capacity of a test pixel is high, other norms (e.g., ℓ 2 -norm can be used to regularize the coding coefficients, except for the sparsity ℓ 1 -norm. In this paper, we show that in the kernel space the nonnegative constraint can also play the same role, and thus suggest the investigation of kernel fully constrained least squares (KFCLS for hyperspectral image classification. Furthermore, in order to improve the classification performance of KFCLS by incorporating spatial-spectral information, we investigate two kinds of spatial-spectral methods using two regularization strategies: (1 the coefficient-level regularization strategy, and (2 the class-level regularization strategy. Experimental results conducted on four real hyperspectral images demonstrate the effectiveness of the proposed KFCLS, and show which way to incorporate spatial-spectral information efficiently in the regularization framework.

  1. GPU Lossless Hyperspectral Data Compression System for Space Applications

    Keymeulen, Didier; Aranki, Nazeeh; Hopson, Ben; Kiely, Aaron; Klimesh, Matthew; Benkrid, Khaled


    On-board lossless hyperspectral data compression reduces data volume in order to meet NASA and DoD limited downlink capabilities. At JPL, a novel, adaptive and predictive technique for lossless compression of hyperspectral data, named the Fast Lossless (FL) algorithm, was recently developed. This technique uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. Because of its outstanding performance and suitability for real-time onboard hardware implementation, the FL compressor is being formalized as the emerging CCSDS Standard for Lossless Multispectral & Hyperspectral image compression. The FL compressor is well-suited for parallel hardware implementation. A GPU hardware implementation was developed for FL targeting the current state-of-the-art GPUs from NVIDIA(Trademark). The GPU implementation on a NVIDIA(Trademark) GeForce(Trademark) GTX 580 achieves a throughput performance of 583.08 Mbits/sec (44.85 MSamples/sec) and an acceleration of at least 6 times a software implementation running on a 3.47 GHz single core Intel(Trademark) Xeon(Trademark) processor. This paper describes the design and implementation of the FL algorithm on the GPU. The massively parallel implementation will provide in the future a fast and practical real-time solution for airborne and space applications.

  2. Passive cooling containment study

    Shin, J.J.; Iotti, R.C.; Wright, R.F.


    Pressure and temperature transients of nuclear reactor containment following postulated loss of coolant accident with a coincident station blackout due to total loss of all alternating current power are studied analytically and experimentally for the full scale NPR (New Production Reactor). All the reactor and containment cooling under this condition would rely on the passive cooling system which removes reactor decay heat and provides emergency core and containment cooling. Containment passive cooling for this study takes place in the annulus between containment steel shell and concrete shield building by natural convection air flow and thermal radiation. Various heat transfer coefficients inside annular air space were investigated by running the modified CONTEMPT code CONTEMPT-NPR. In order to verify proper heat transfer coefficient, temperature, heat flux, and velocity profiles were measured inside annular air space of the test facility which is a 24 foot (7.3m) high, steam heated inner cylinder of three foot (.91m) diameter and five and half foot (1.7m) diameter outer cylinder. Comparison of CONTEMPT-NPR and WGOTHIC was done for reduced scale NPR

  3. Fly ash carbon passivation

    La Count, Robert B; Baltrus, John P; Kern, Douglas G


    A thermal method to passivate the carbon and/or other components in fly ash significantly decreases adsorption. The passivated carbon remains in the fly ash. Heating the fly ash to about 500 and 800 degrees C. under inert gas conditions sharply decreases the amount of surfactant adsorbed by the fly ash recovered after thermal treatment despite the fact that the carbon content remains in the fly ash. Using oxygen and inert gas mixtures, the present invention shows that a thermal treatment to about 500 degrees C. also sharply decreases the surfactant adsorption of the recovered fly ash even though most of the carbon remains intact. Also, thermal treatment to about 800 degrees C. under these same oxidative conditions shows a sharp decrease in surfactant adsorption of the recovered fly ash due to the fact that the carbon has been removed. This experiment simulates the various "carbon burnout" methods and is not a claim in this method. The present invention provides a thermal method of deactivating high carbon fly ash toward adsorption of AEAs while retaining the fly ash carbon. The fly ash can be used, for example, as a partial Portland cement replacement in air-entrained concrete, in conductive and other concretes, and for other applications.

  4. Surface Passivation in Empirical Tight Binding

    He, Yu; Tan, Yaohua; Jiang, Zhengping; Povolotskyi, Michael; Klimeck, Gerhard; Kubis, Tillmann


    Empirical Tight Binding (TB) methods are widely used in atomistic device simulations. Existing TB methods to passivate dangling bonds fall into two categories: 1) Method that explicitly includes passivation atoms is limited to passivation with atoms and small molecules only. 2) Method that implicitly incorporates passivation does not distinguish passivation atom types. This work introduces an implicit passivation method that is applicable to any passivation scenario with appropriate parameter...

  5. SVM-based feature extraction and classification of aflatoxin contaminated corn using fluorescence hyperspectral data

    Support Vector Machine (SVM) was used in the Genetic Algorithms (GA) process to select and classify a subset of hyperspectral image bands. The method was applied to fluorescence hyperspectral data for the detection of aflatoxin contamination in Aspergillus flavus infected single corn kernels. In the...

  6. A light-weight hyperspectral mapping system for unmanned aerial vehicles - The first results

    Suomalainen, Juha; Anders, Niels; Iqbal, Shahzad; Franke, Jappe; Wenting, Philip; Bartholomeus, Harm; Becker, Rolf; Kooistra, Lammert


    Research opportunities using UAV remote sensing techniques are limited by the payload of the platform. Therefore small UAV's are typically not suitable for hyperspectral imaging due to the weight of the mapping system. In this research, we are developing a light-weight hyperspectral mapping system

  7. Hyperspectral remote sensing analysis of short rotation woody crops grown with controlled nutrient and irrigation treatments

    Jungho Im; John R. Jensen; Mark Coleman; Eric. Nelson


    Hyperspectral remote sensing research was conducted to document the biophysical and biochemical characteristics of controlled forest plots subjected to various nutrient and irrigation treatments. The experimental plots were located on the Savannah River Site near Aiken, SC. AISA hyperspectral imagery were analysed using three approaches, including: (1) normalized...

  8. Hyperspectral microscope imaging methods to classify gram-positive and gram-negative foodborne pathogenic bacteria

    An acousto-optic tunable filter-based hyperspectral microscope imaging method has potential for identification of foodborne pathogenic bacteria from microcolony rapidly with a single cell level. We have successfully developed the method to acquire quality hyperspectral microscopic images from variou...

  9. Processing OMEGA/Mars Express hyperspectral imagery from radiance-at-sensor to surface reflectance

    Bakker, W.H.; Ruitenbeek, F.J.A. van; Werff, H.M.A. van der; Zegers, T.E.; Oosthoek, J.H.P.; Marsh, S.H.; Meer, F.D. van der


    OMEGA/Mars Express hyperspectral imagery is an excellent source of data for exploring the surface composition of the planet Mars. Compared to terrestrial hyperspectral imagery, the data are challenging to work with; scene-specific transmission models are lacking, spectral features are shallow making

  10. Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

    Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan


    Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

  11. Passive-solar construction handbook

    Levy, E.; Evans, D.; Gardstein, C.


    Many of the basic elements of passive solar design are reviewed. Passive solar construction is covered according to system type, each system type discussion including a general discussion of the important design and construction issues which apply to the particular system and case studies illustrating designed and built examples of the system type. The three basic types of passive solar systems discussed are direct gain, thermal storage wall, and attached sunspace. Thermal performance and construction information is presented for typical materials used in passive solar collector components, storage components, and control components. Appended are an overview of analysis methods and a technique for estimating performance. (LEW)

  12. Hyperspectral and thermal methodologies applied to landslide monitoring

    Vellico, Michela; Sterzai, Paolo; Pietrapertosa, Carla; Mora, Paolo; Berti, Matteo; Corsini, Alessandro; Ronchetti, Francesco; Giannini, Luciano; Vaselli, Orlando


    Landslide monitoring is a very actual topic. Landslides are a widespread phenomenon over the European territory and these phenomena have been responsible of huge economic losses. The aim of the WISELAND research project (Integrated Airborne and Wireless Sensor Network systems for Landslide Monitoring), funded by the Italian Government, is to test new monitoring techniques capable to rapidly and successfully characterize large landslides in fine soils. Two active earthflows in the Northern Italian Appenines have been chosen as test sites and investigated: Silla (Bologna Province) and Valoria (Modena Province). The project implies the use of remote sensing methodologies, with particular focus on the joint use of airborne Lidar, hyperspectral and thermal systems. These innovative techniques give promising results, since they allow to detect the principal landslide components and to evaluate the spatial distribution of parameters relevant to landslide dynamics such as surface water content and roughness. In this paper we put the attention on the response of the terrain related to the use of a hyperspectral system and its integration with the complementary information obtained using a thermal sensor. The potentiality of a hyperspectral dataset acquired in the VNIR (Visible Near Infrared field) and of the spectral response of the terrain could be high since they give important information both on the soil and on the vegetation status. Several significant indexes can be calculated, such as NDVI, obtained considering a band in the Red field and a band in the Infrared field; it gives information on the vegetation health and indirectly on the water content of soils. This is a key point that bridges hyperspectral and thermal datasets. Thermal infrared data are closely related to soil moisture, one of the most important parameter affecting surface stability in soil slopes. Effective stresses and shear strength in unsaturated soils are directly related to water content, and

  13. The study of active tectonic based on hyperspectral remote sensing

    Cui, J.; Zhang, S.; Zhang, J.; Shen, X.; Ding, R.; Xu, S.


    As of the latest technical methods, hyperspectral remote sensing technology has been widely used in each brach of the geosciences. However, it is still a blank for using the hyperspectral remote sensing to study the active structrure. Hyperspectral remote sensing, with high spectral resolution, continuous spectrum, continuous spatial data, low cost, etc, has great potentialities in the areas of stratum division and fault identification. Blind fault identification in plains and invisible fault discrimination in loess strata are the two hot problems in the current active fault research. Thus, the study of active fault based on the hyperspectral technology has great theoretical significance and practical value. Magnetic susceptibility (MS) records could reflect the rhythm alteration of the formation. Previous study shown that MS has correlation with spectral feature. In this study, the Emaokou section, located to the northwest of the town of Huairen, in Shanxi Province, has been chosen for invisible fault study. We collected data from the Emaokou section, including spectral data, hyperspectral image, MS data. MS models based on spectral features were established and applied to the UHD185 image for MS mapping. The results shown that MS map corresponded well to the loess sequences. It can recognize the stratum which can not identity by naked eyes. Invisible fault has been found in this section, which is useful for paleoearthquake analysis. The faults act as the conduit for migration of terrestrial gases, the fault zones, especially the structurally weak zones such as inrtersections or bends of fault, may has different material composition. We take Xiadian fault for study. Several samples cross-fault were collected and these samples were measured by ASD Field Spec 3 spectrometer. Spectral classification method has been used for spectral analysis, we found that the spectrum of the fault zone have four special spectral region(550-580nm, 600-700nm, 700-800nm and 800-900nm

  14. Passive magnetic bearing system

    Post, Richard F.


    An axial stabilizer for the rotor of a magnetic bearing provides external control of stiffness through switching in external inductances. External control also allows the stabilizer to become a part of a passive/active magnetic bearing system that requires no external source of power and no position sensor. Stabilizers for displacements transverse to the axis of rotation are provided that require only a single cylindrical Halbach array in its operation, and thus are especially suited for use in high rotation speed applications, such as flywheel energy storage systems. The elimination of the need of an inner cylindrical array solves the difficult mechanical problem of supplying support against centrifugal forces for the magnets of that array. Compensation is provided for the temperature variation of the strength of the magnetic fields of the permanent magnets in the levitating magnet arrays.

  15. European vehicle passive safety network

    Wismans, J.S.H.M.; Janssen, E.G.


    The general objective of the European Vehicle Passive Safety Network is to contribute to the reduction of the number of road traffic victims in Europe by passive safety measures. The aim of the road safety policy of the European Commission is to reduce the annual total of fatalities to 18000 in

  16. Passive films at the nanoscale

    Maurice, Vincent; Marcus, Philippe


    Highlights: ► Nanoscale data on growth, structure and local properties of passive films reviewed. ► Preferential role of defects of passive films on the corrosion resistance emphasized. ► Effect of grain boundaries on local electronic properties shown by new data. ► Use of atomistic modeling to test mechanistic hypotheses illustrated. - Abstract: The nanometer scale chemical and structural aspects of ultrathin oxide passive films providing self-protection against corrosion to metals and alloys in aqueous environments are reviewed. Data on the nucleation and growth of 2D anodic oxide films, details on the atomic structure and nanostructure of 3D passive films, the preferential role of surface step edges in dissolution in the passive state and the preferential role of grain boundaries of the passive films in passivity breakdown are presented. Future perspectives are discussed, and exemplified by new data obtained on the relationship between the nanostructure of oxide passive films and their local electronic properties. Atomistic corrosion modeling by ab initio density functional theory (DFT) is illustrated by the example of interactions of chloride ions with hydroxylated oxide surfaces, including the role of surface step edges. Data obtained on well-defined substrate surfaces with surface analytical techniques are emphasized.

  17. Udviklingen i bilers passive sikkerhed

    Hels, Tove; Lyckegaard, Allan; Prato, Carlo Giacomo

    man mellem aktiv og passiv sikkerhed, det vil sige faktorer, der nedsætter • risikoen for, at der sker et uheld (aktiv sikkerhed), henholdsvis • graden af alvorlighed, givet at uheldet er sket (passiv sikkerhed). Rapporten begrænser sig til at undersøge, om der kan påvises en generel sammenhæng mellem...

  18. The Passive in Singapore English.

    Bao, Zhiming; Wee, Lionel


    Presents an analysis of the two passive (or passive-like) constructions in Singapore English which exhibit substrate influence from Malay and Chinese. The paper shows that while substrate languages contribute to the grammar of Singapore English, the continued prestige of standard English exerts normative pressure and mitigates the effect of…

  19. Antireflection/Passivation Step For Silicon Cell

    Crotty, Gerald T.; Kachare, Akaram H.; Daud, Taher


    New process excludes usual silicon oxide passivation. Changes in principal electrical parameters during two kinds of processing suggest antireflection treatment almost as effective as oxide treatment in passivating cells. Does so without disadvantages of SiOx passivation.

  20. Dimensionality Reduction for Hyperspectral Data Based on Class-Aware Tensor Neighborhood Graph and Patch Alignment.

    Gao, Yang; Wang, Xuesong; Cheng, Yuhu; Wang, Z Jane


    To take full advantage of hyperspectral information, to avoid data redundancy and to address the curse of dimensionality concern, dimensionality reduction (DR) becomes particularly important to analyze hyperspectral data. Exploring the tensor characteristic of hyperspectral data, a DR algorithm based on class-aware tensor neighborhood graph and patch alignment is proposed here. First, hyperspectral data are represented in the tensor form through a window field to keep the spatial information of each pixel. Second, using a tensor distance criterion, a class-aware tensor neighborhood graph containing discriminating information is obtained. In the third step, employing the patch alignment framework extended to the tensor space, we can obtain global optimal spectral-spatial information. Finally, the solution of the tensor subspace is calculated using an iterative method and low-dimensional projection matrixes for hyperspectral data are obtained accordingly. The proposed method effectively explores the spectral and spatial information in hyperspectral data simultaneously. Experimental results on 3 real hyperspectral datasets show that, compared with some popular vector- and tensor-based DR algorithms, the proposed method can yield better performance with less tensor training samples required.

  1. Tree Classification with Fused Mobile Laser Scanning and Hyperspectral Data

    Puttonen, Eetu; Jaakkola, Anttoni; Litkey, Paula; Hyyppä, Juha


    Mobile Laser Scanning data were collected simultaneously with hyperspectral data using the Finnish Geodetic Institute Sensei system. The data were tested for tree species classification. The test area was an urban garden in the City of Espoo, Finland. Point clouds representing 168 individual tree specimens of 23 tree species were determined manually. The classification of the trees was done using first only the spatial data from point clouds, then with only the spectral data obtained with a spectrometer, and finally with the combined spatial and hyperspectral data from both sensors. Two classification tests were performed: the separation of coniferous and deciduous trees, and the identification of individual tree species. All determined tree specimens were used in distinguishing coniferous and deciduous trees. A subset of 133 trees and 10 tree species was used in the tree species classification. The best classification results for the fused data were 95.8% for the separation of the coniferous and deciduous classes. The best overall tree species classification succeeded with 83.5% accuracy for the best tested fused data feature combination. The respective results for paired structural features derived from the laser point cloud were 90.5% for the separation of the coniferous and deciduous classes and 65.4% for the species classification. Classification accuracies with paired hyperspectral reflectance value data were 90.5% for the separation of coniferous and deciduous classes and 62.4% for different species. The results are among the first of their kind and they show that mobile collected fused data outperformed single-sensor data in both classification tests and by a significant margin. PMID:22163894

  2. The software and algorithms for hyperspectral data processing

    Shyrayeva, Anhelina; Martinov, Anton; Ivanov, Victor; Katkovsky, Leonid


    Hyperspectral remote sensing technique is widely used for collecting and processing -information about the Earth's surface objects. Hyperspectral data are combined to form a three-dimensional (x, y, λ) data cube. Department of Aerospace Research of the Institute of Applied Physical Problems of the Belarusian State University presents a general model of the software for hyperspectral image data analysis and processing. The software runs in Windows XP/7/8/8.1/10 environment on any personal computer. This complex has been has been written in C++ language using QT framework and OpenGL for graphical data visualization. The software has flexible structure that consists of a set of independent plugins. Each plugin was compiled as Qt Plugin and represents Windows Dynamic library (dll). Plugins can be categorized in terms of data reading types, data visualization (3D, 2D, 1D) and data processing The software has various in-built functions for statistical and mathematical analysis, signal processing functions like direct smoothing function for moving average, Savitzky-Golay smoothing technique, RGB correction, histogram transformation, and atmospheric correction. The software provides two author's engineering techniques for the solution of atmospheric correction problem: iteration method of refinement of spectral albedo's parameters using Libradtran and analytical least square method. The main advantages of these methods are high rate of processing (several minutes for 1 GB data) and low relative error in albedo retrieval (less than 15%). Also, the software supports work with spectral libraries, region of interest (ROI) selection, spectral analysis such as cluster-type image classification and automatic hypercube spectrum comparison by similarity criterion with similar ones from spectral libraries, and vice versa. The software deals with different kinds of spectral information in order to identify and distinguish spectrally unique materials. Also, the following advantages

  3. Online hyperspectral imaging system for evaluating quality of agricultural products

    Mo, Changyeun; Kim, Giyoung; Lim, Jongguk


    The consumption of fresh-cut agricultural produce in Korea has been growing. The browning of fresh-cut vegetables that occurs during storage and foreign substances such as worms and slugs are some of the main causes of consumers' concerns with respect to safety and hygiene. The purpose of this study is to develop an on-line system for evaluating quality of agricultural products using hyperspectral imaging technology. The online evaluation system with single visible-near infrared hyperspectral camera in the range of 400 nm to 1000 nm that can assess quality of both surfaces of agricultural products such as fresh-cut lettuce was designed. Algorithms to detect browning surface were developed for this system. The optimal wavebands for discriminating between browning and sound lettuce as well as between browning lettuce and the conveyor belt were investigated using the correlation analysis and the one-way analysis of variance method. The imaging algorithms to discriminate the browning lettuces were developed using the optimal wavebands. The ratio image (RI) algorithm of the 533 nm and 697 nm images (RI533/697) for abaxial surface lettuce and the ratio image algorithm (RI533/697) and subtraction image (SI) algorithm (SI538-697) for adaxial surface lettuce had the highest classification accuracies. The classification accuracy of browning and sound lettuce was 100.0% and above 96.0%, respectively, for the both surfaces. The overall results show that the online hyperspectral imaging system could potentially be used to assess quality of agricultural products.

  4. Hyperspectral image segmentation using a cooperative nonparametric approach

    Taher, Akar; Chehdi, Kacem; Cariou, Claude


    In this paper a new unsupervised nonparametric cooperative and adaptive hyperspectral image segmentation approach is presented. The hyperspectral images are partitioned band by band in parallel and intermediate classification results are evaluated and fused, to get the final segmentation result. Two unsupervised nonparametric segmentation methods are used in parallel cooperation, namely the Fuzzy C-means (FCM) method, and the Linde-Buzo-Gray (LBG) algorithm, to segment each band of the image. The originality of the approach relies firstly on its local adaptation to the type of regions in an image (textured, non-textured), and secondly on the introduction of several levels of evaluation and validation of intermediate segmentation results before obtaining the final partitioning of the image. For the management of similar or conflicting results issued from the two classification methods, we gradually introduced various assessment steps that exploit the information of each spectral band and its adjacent bands, and finally the information of all the spectral bands. In our approach, the detected textured and non-textured regions are treated separately from feature extraction step, up to the final classification results. This approach was first evaluated on a large number of monocomponent images constructed from the Brodatz album. Then it was evaluated on two real applications using a respectively multispectral image for Cedar trees detection in the region of Baabdat (Lebanon) and a hyperspectral image for identification of invasive and non invasive vegetation in the region of Cieza (Spain). A correct classification rate (CCR) for the first application is over 97% and for the second application the average correct classification rate (ACCR) is over 99%.

  5. [Hyperspectral remote sensing in monitoring the vegetation heavy metal pollution].

    Li, Na; Lü, Jian-sheng; Altemann, W


    Mine exploitation aggravates the environment pollution. The large amount of heavy metal element in the drainage of slag from the mine pollutes the soil seriously, doing harm to the vegetation growing and human health. The investigation of mining environment pollution is urgent, in which remote sensing, as a new technique, helps a lot. In the present paper, copper mine in Dexing was selected as the study area and China sumac as the study plant. Samples and spectral data in field were gathered and analyzed in lab. The regression model from spectral characteristics for heavy metal content was built, and the feasibility of hyperspectral remote sensing in environment pollution monitoring was testified.


    Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.


    Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor ...

  7. Classification of fecal contamination on leafy greens by hyperspectral imaging

    Yang, Chun-Chieh; Jun, Won; Kim, Moon S.; Chao, Kaunglin; Kang, Sukwon; Chan, Diane E.; Lefcourt, Alan


    This paper reported the development of hyperspectral fluorescence imaging system using ultraviolet-A excitation (320-400 nm) for detection of bovine fecal contaminants on the abaxial and adaxial surfaces of romaine lettuce and baby spinach leaves. Six spots of fecal contamination were applied to each of 40 lettuce and 40 spinach leaves. In this study, the wavebands at 666 nm and 680 nm were selected by the correlation analysis. The two-band ratio, 666 nm / 680 nm, of fluorescence intensity was used to differentiate the contaminated spots from uncontaminated leaf area. The proposed method could accurately detect all of the contaminated spots.

  8. Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

    Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.


    The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time

  9. Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.

    Li, Qingli; Zhou, Mei; Liu, Hongying; Wang, Yiting; Guo, Fangmin


    Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.

  10. Pixelated camouflage patterns from the perspective of hyperspectral imaging

    Racek, František; Jobánek, Adam; Baláž, Teodor; Krejčí, Jaroslav


    Pixelated camouflage patterns fulfill the role of both principles the matching and the disrupting that are exploited for blending the target into the background. It means that pixelated pattern should respect natural background in spectral and spatial characteristics embodied in micro and macro patterns. The HS imaging plays the similar, however the reverse role in the field of reconnaissance systems. The HS camera fundamentally records and extracts both the spectral and spatial information belonging to the recorded scenery. Therefore, the article deals with problems of hyperspectral (HS) imaging and subsequent processing of HS images of pixelated camouflage patterns which are among others characterized by their specific spatial frequency heterogeneity.

  11. A robust background regression based score estimation algorithm for hyperspectral anomaly detection

    Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei


    Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement

  12. Development of nanometer resolution C-Band radio frequency beam position monitors in the Final Focus Test Beam

    Slaton, T.; Mazaheri, G. [Stanford Univ., CA (US). Stanford Linear Accelerator Center; Shintake, T. [National Lab. for High Energy Physics, Tsukuba, Ibaraki (Japan)


    Using a 47 GeV electron beam, the Final Focus Test Beam (FFTB) produces vertical spot sizes around 70 nm. These small beam sizes introduce an excellent opportunity to develop and test high resolution Radio Frequency Beam Position Monitors (RF-BPMs). These BPMs are designed to measure pulse to pulse beam motion (jitter) at a theoretical resolution of approximately 1 nm. The beam induces a TM{sub 110} mode with an amplitude linearly proportional to its charge and displacement from the BPM's (cylindrical cavity) axis. The C-band (5,712 MHz) TM{sub 110} signal is processed and converted into beam position for use by the Stanford Linear Collider (SLC) control system. Presented are the experimental procedures, acquisition, and analysis of data demonstrating resolution of jitter near 25 nm. With the design of future e{sup +}e{sup -} linear colliders requiring spot sizes close to 3 nm, understanding and developing RF-BPMs will be essential in resolving and controlling jitter.

  13. Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

    Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang


    Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

  14. Maskless X-Ray Writing of Electrical Devices on a Superconducting Oxide with Nanometer Resolution and Online Process Monitoring.

    Mino, Lorenzo; Bonino, Valentina; Agostino, Angelo; Prestipino, Carmelo; Borfecchia, Elisa; Lamberti, Carlo; Operti, Lorenza; Fretto, Matteo; De Leo, Natascia; Truccato, Marco


    X-ray nanofabrication has so far been usually limited to mask methods involving photoresist impression and subsequent etching. Herein we show that an innovative maskless X-ray nanopatterning approach allows writing electrical devices with nanometer feature size. In particular we fabricated a Josephson device on a Bi 2 Sr 2 CaCu 2 O 8+δ (Bi-2212) superconducting oxide micro-crystal by drawing two single lines of only 50 nm in width using a 17.4 keV synchrotron nano-beam. A precise control of the fabrication process was achieved by monitoring in situ the variations of the device electrical resistance during X-ray irradiation, thus finely tuning the irradiation time to drive the material into a non-superconducting state only in the irradiated regions, without significantly perturbing the crystal structure. Time-dependent finite element model simulations show that a possible microscopic origin of this effect can be related to the instantaneous temperature increase induced by the intense synchrotron picosecond X-ray pulses. These results prove that a conceptually new patterning method for oxide electrical devices, based on the local change of electrical properties, is actually possible with potential advantages in terms of heat dissipation, chemical contamination, miniaturization and high aspect ratio of the devices.

  15. Low volume, large force (>1mN) and nanometer resolution, electrostatic microactuator for low displacement applications

    Sarajlic, Edin; Berenschot, Johan W.; Krijnen, Gijsbertus J.M.; Elwenspoek, Michael Curt


    A compact electrostatic microactuator suitable for low displacement applications is proposed. The actuator employs a large number of basic units working in parallel together with a built-in mechanical transformation to generate large force. Influence of distinct design parameters on actuator

  16. Development of nanometer resolution C-Band radio frequency beam position monitors in the Final Focus Test Beam

    Slaton, T.; Mazaheri, G.


    Using a 47 GeV electron beam, the Final Focus Test Beam (FFTB) produces vertical spot sizes around 70 nm. These small beam sizes introduce an excellent opportunity to develop and test high resolution Radio Frequency Beam Position Monitors (RF-BPMs). These BPMs are designed to measure pulse to pulse beam motion (jitter) at a theoretical resolution of approximately 1 nm. The beam induces a TM 110 mode with an amplitude linearly proportional to its charge and displacement from the BPM's (cylindrical cavity) axis. The C-band (5,712 MHz) TM 110 signal is processed and converted into beam position for use by the Stanford Linear Collider (SLC) control system. Presented are the experimental procedures, acquisition, and analysis of data demonstrating resolution of jitter near 25 nm. With the design of future e + e - linear colliders requiring spot sizes close to 3 nm, understanding and developing RF-BPMs will be essential in resolving and controlling jitter

  17. [Prediction of Encapsulation Temperatures of Copolymer Films in Photovoltaic Cells Using Hyperspectral Imaging Techniques and Chemometrics].

    Lin, Ping; Chen, Yong-ming; Yao, Zhi-lei


    A novel method of combination of the chemometrics and the hyperspectral imaging techniques was presented to detect the temperatures of Ethylene-Vinyl Acetate copolymer (EVA) films in photovoltaic cells during the thermal encapsulation process. Four varieties of the EVA films which had been heated at the temperatures of 128, 132, 142 and 148 °C during the photovoltaic cells production process were used for investigation in this paper. These copolymer encapsulation films were firstly scanned by the hyperspectral imaging equipment (Spectral Imaging Ltd. Oulu, Finland). The scanning band range of hyperspectral equipemnt was set between 904.58 and 1700.01 nm. The hyperspectral dataset of copolymer films was randomly divided into two parts for the training and test purpose. Each type of the training set and test set contained 90 and 10 instances, respectively. The obtained hyperspectral images of EVA films were dealt with by using the ENVI (Exelis Visual Information Solutions, USA) software. The size of region of interest (ROI) of each obtained hyperspectral image of EVA film was set as 150 x 150 pixels. The average of reflectance hyper spectra of all the pixels in the ROI was used as the characteristic curve to represent the instance. There kinds of chemometrics methods including partial least squares regression (PLSR), multi-class support vector machine (SVM) and large margin nearest neighbor (LMNN) were used to correlate the characteristic hyper spectra with the encapsulation temperatures of of copolymer films. The plot of weighted regression coefficients illustrated that both bands of short- and long-wave near infrared hyperspectral data contributed to enhancing the prediction accuracy of the forecast model. Because the attained reflectance hyperspectral data of EVA materials displayed the strong nonlinearity, the prediction performance of linear modeling method of PLSR declined and the prediction precision only reached to 95%. The kernel-based forecast models were

  18. French concepts of ''passive safety''

    Dennielou, Y.; Serret, M.


    N 4 model, the French 1400 MW PWR of the 90's, exhibits many advanced features. As far as safety is concerned, the fully computerized control room design takes advantage of the operating experience feedback and largely improves the man machine interface. New post-accident procedures have been developed (the so-called ''physical states oriented procedures''). A complete consistent set of ''Fundamental Safety Rules'' have been issued. This however doesn't imply any significant modification of standard PWR with regard to the passive aspects of safety systems or functions. Nevertheless, traditional PWR safety systems largely use passive aspects: natural circulation, reactivity coefficients, gravity driven control rods, injection accumulators, so on. Moreover, probability calculations allow for comparison between the respective contributions of passive and of active failures. In the near future, eventual options of future French PWRs to be commissioned after 2000 will be evaluated; simplification, passive and forgiving aspects of safety systems will be thoroughly considered. (author)

  19. Effectiveness of passive alcohol sensors


    Author's abstract: The purpose of this study was to evaluate the effectiveness of passive alcohol sensors for youth alcohol enforcement conducted as part of normal or typical police operations. Three municipal police departments of 100 or more sworn ...

  20. Passive heat removal in CANDU

    Hart, R.S.


    CANDU has a tradition of incorporating passive systems and passive components whenever they are shown to offer performance that is equal to or better than that of active systems, and to be economic. Examples include the two independent shutdown systems that employ gravity and stored energy respectively, the dousing subsystem of the CANDU 6 containment system, and the ability of the moderator to cool the fuel in the event that all coolant is lost from the fuel channels. CANDU 9 continues this tradition, incorporating a reserve water system (RWS) that increases the inventory of water in the reactor building and profiles a passive source of makeup water and/or heat sinks to various key process systems. The key component of the CANDU 9 reserve water system is a large (2500 cubic metres) water tank located at a high elevation in the reactor building. The reserve water system, while incorporating the recovery system functions, and the non-dousing functions of the dousing tank in CANDU 6, embraces other key systems to significantly extend the passive makeup/heat sink capability. The capabilities of the reserve water system include makeup to the steam generators secondary side if all other sources of water are lost; makeup to the heat transport system in the event of a leak in excess of the D 2 O makeup system capability; makeup to the moderator in the event of a moderator leak when the moderator heat sink is required; makeup to the emergency core cooling (ECC) system to assure NPSH to the ECC pumps during a loss of coolant accident (LOCA), and provision of a passive heat sink for the shield cooling system. Other passive designs are now being developed by AECL. These will be incorporated in future CANDU plants when their performance has been fully proven. This paper reviews the passive heat removal systems and features of current CANDU plants and the CANDU 9, and briefly reviews some of the passive heat removal concepts now being developed. (author)

  1. Key issues for passive safety

    Hayns, M.R.


    The paper represents a summary of the introductory presentation made at this Advisory Group Meeting on the Technical Feasibility and Reliability of Passive Safety Systems. It was intended as an overview of our views on what are the key issues and what are the technical problems which might dominate any future developments of passive safety systems. It is, therefore, not a ''review paper'' as such and only record the highlights. (author)

  2. Key issues for passive safety

    Hayns, M R [AEA Technology, Harwell, Didcot (United Kingdom). European Institutions; Hicken, E F [Forschungszentrum Juelich GmbH (Germany)


    The paper represents a summary of the introductory presentation made at this Advisory Group Meeting on the Technical Feasibility and Reliability of Passive Safety Systems. It was intended as an overview of our views on what are the key issues and what are the technical problems which might dominate any future developments of passive safety systems. It is, therefore, not a ``review paper`` as such and only record the highlights. (author).

  3. Passive vapor extraction feasibility study

    Rohay, V.J.


    Demonstration of a passive vapor extraction remediation system is planned for sites in the 200 West Area used in the past for the disposal of waste liquids containing carbon tetrachloride. The passive vapor extraction units will consist of a 4-in.-diameter pipe, a check valve, a canister filled with granular activated carbon, and a wind turbine. The check valve will prevent inflow of air that otherwise would dilute the soil gas and make its subsequent extraction less efficient. The granular activated carbon is used to adsorb the carbon tetrachloride from the air. The wind turbine enhances extraction rates on windy days. Passive vapor extraction units will be designed and operated to meet all applicable or relevant and appropriate requirements. Based on a cost analysis, passive vapor extraction was found to be a cost-effective method for remediation of soils containing lower concentrations of volatile contaminants. Passive vapor extraction used on wells that average 10-stdft 3 /min air flow rates was found to be more cost effective than active vapor extraction for concentrations below 500 parts per million by volume (ppm) of carbon tetrachloride. For wells that average 5-stdft 3 /min air flow rates, passive vapor extraction is more cost effective below 100 ppm

  4. a Spatio-Spectral Camera for High Resolution Hyperspectral Imaging

    Livens, S.; Pauly, K.; Baeck, P.; Blommaert, J.; Nuyts, D.; Zender, J.; Delauré, B.


    Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS) is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600-900 nm) in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots), horticulture (crop status monitoring to evaluate irrigation management in strawberry fields) and geology (meteorite detection on a grassland field). Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475-925 nm), and we discuss future work.

  5. Automating Hyperspectral Data for Rapid Response in Volcanic Emergencies

    Davies, Ashley G.; Doubleday, Joshua R.; Chien, Steve A.


    In a volcanic emergency, time is of the essence. It is vital to quantify eruption parameters (thermal emission, effusion rate, location of activity) and distribute this information as quickly as possible to decision-makers in order to enable effective evaluation of eruption-related risk and hazard. The goal of this work was to automate and streamline processing of spacecraft hyperspectral data, automate product generation, and automate distribution of products. Visible and Short-Wave Infrared Images of volcanic eruption in Iceland in May 2010." class="caption" align="right">The software rapidly processes hyperspectral data, correcting for incident sunlight where necessary, and atmospheric transmission; detects thermally anomalous pixels; fits data with model black-body thermal emission spectra to determine radiant flux; calculates atmospheric convection thermal removal; and then calculates total heat loss. From these results, an estimation of effusion rate is made. Maps are generated of thermal emission and location (see figure). Products are posted online, and relevant parties notified. Effusion rate data are added to historical record and plotted to identify spikes in activity for persistently active eruptions. The entire process from start to end is autonomous. Future spacecraft, especially those in deep space, can react to detection of transient processes without the need to communicate with Earth, thus increasing science return. Terrestrially, this removes the need for human intervention.

  6. Classification of Grassland Successional Stages Using Airborne Hyperspectral Imagery

    Thomas Möckel


    Full Text Available Plant communities differ in their species composition, and, thus, also in their functional trait composition, at different stages in the succession from arable fields to grazed grassland. We examine whether aerial hyperspectral (414–2501 nm remote sensing can be used to discriminate between grazed vegetation belonging to different grassland successional stages. Vascular plant species were recorded in 104.1 m2 plots on the island of Öland (Sweden and the functional properties of the plant species recorded in the plots were characterized in terms of the ground-cover of grasses, specific leaf area and Ellenberg indicator values. Plots were assigned to three different grassland age-classes, representing 5–15, 16–50 and >50 years of grazing management. Partial least squares discriminant analysis models were used to compare classifications based on aerial hyperspectral data with the age-class classification. The remote sensing data successfully classified the plots into age-classes: the overall classification accuracy was higher for a model based on a pre-selected set of wavebands (85%, Kappa statistic value = 0.77 than one using the full set of wavebands (77%, Kappa statistic value = 0.65. Our results show that nutrient availability and grass cover differences between grassland age-classes are detectable by spectral imaging. These techniques may potentially be used for mapping the spatial distribution of grassland habitats at different successional stages.

  7. Accurate reconstruction of hyperspectral images from compressive sensing measurements

    Greer, John B.; Flake, J. C.


    The emerging field of Compressive Sensing (CS) provides a new way to capture data by shifting the heaviest burden of data collection from the sensor to the computer on the user-end. This new means of sensing requires fewer measurements for a given amount of information than traditional sensors. We investigate the efficacy of CS for capturing HyperSpectral Imagery (HSI) remotely. We also introduce a new family of algorithms for constructing HSI from CS measurements with Split Bregman Iteration [Goldstein and Osher,2009]. These algorithms combine spatial Total Variation (TV) with smoothing in the spectral dimension. We examine models for three different CS sensors: the Coded Aperture Snapshot Spectral Imager-Single Disperser (CASSI-SD) [Wagadarikar et al.,2008] and Dual Disperser (CASSI-DD) [Gehm et al.,2007] cameras, and a hypothetical random sensing model closer to CS theory, but not necessarily implementable with existing technology. We simulate the capture of remotely sensed images by applying the sensor forward models to well-known HSI scenes - an AVIRIS image of Cuprite, Nevada and the HYMAP Urban image. To measure accuracy of the CS models, we compare the scenes constructed with our new algorithm to the original AVIRIS and HYMAP cubes. The results demonstrate the possibility of accurately sensing HSI remotely with significantly fewer measurements than standard hyperspectral cameras.


    S. Livens


    Full Text Available Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600–900 nm in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots, horticulture (crop status monitoring to evaluate irrigation management in strawberry fields and geology (meteorite detection on a grassland field. Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475–925 nm, and we discuss future work.

  9. Hyperspectral estimation of corn fraction of photosynthetically active radiation

    Yang Fei; Zhang Bai; Song Kaishan


    Fraction of absorbed photosynthetically active radiation (FPAR) is one of the important variables in many productivity and biomass estimation models, this analyzed the effect of FPAR estimation with hyperspectral information, which could provide the scientific support on the improvement of FPAR estimation, remote sensing data validation, and the other ecological models. Based on the field experiment of corn, this paper analyzed the correlations between FPAR and spectral reflectance or the differential coefficient, and discussed the mechanism of FPAR estimation, studied corn FPAR estimation with reflectance, first differential coefficient, NDVI and RVI. The reflectance of visible bands showed much better correlations with FPAR than near-infrared bands. The correlation curve between FPAR and differential coefficient varied more frequently and greatly than the curve of FPAR and reflectance. Reflectance and differential coefficient both had good regressions with FPAR of the typical single band, with the maximum R2 of 0.791 and 0.882. In a word, differential coefficient and vegetation index were much effective than reflectance for corn FPAR estimating, and the stepwised regression of multibands differential coefficient showed the best regression with R2 of 0.944. 375 nm purpled band and 950 nm near-infraed band absorbed by water showed prodigious potential for FPAR estimating precision. On the whole, vegetation index and differential coefficient have good relationships with FPAR, and could be used for FAPR estimation. It would be effective of choosing right bands and excavating the hyperspectral data to improve FPAR estimating precision

  10. A novel highly parallel algorithm for linearly unmixing hyperspectral images

    Guerra, Raúl; López, Sebastián.; Callico, Gustavo M.; López, Jose F.; Sarmiento, Roberto


    Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.

  11. Hyperspectral microscopy and cluster analysis for oral cancer diagnosis

    Jarman, Anneliese; Manickavasagam, Arunthathi; Hosny, Neveen; Festy, Frederic


    Oral cancer incidences have been increasing in recent years and late detection often leads to poor prognosis. Raman spectroscopy has been identified has a valuable diagnostic tool for cancer but its time consuming nature has prevented its clinical use. For Raman to become a realistic aid to histopathology, a rapid pre-screening technique is required to find small regions of interest on tissue sections [1]. The aim of this work is to investigate the feasibility of hyperspectral imaging in the visible spectral range as a fast imaging technique before Raman is performed. We have built a hyperspectral microscope which captures 300 focused and intensity corrected images with wavelength ranging from 450- 750 nm in around 30 minutes with sub-micron spatial resolution and around 10 nm spectral resolution. Hyperstacks of known absorbing samples, including fluorescent dyes and dried blood droplets, show excellent results with spectrally accurate transmission spectra and concentration-dependent intensity variations. We successfully showed the presence of different components from a non-absorbent saliva droplet sample. Data analysis is the greatest hurdle to the interpretation of more complex data such as unstained tissue sections.

  12. Joint Group Sparse PCA for Compressed Hyperspectral Imaging.

    Khan, Zohaib; Shafait, Faisal; Mian, Ajmal


    A sparse principal component analysis (PCA) seeks a sparse linear combination of input features (variables), so that the derived features still explain most of the variations in the data. A group sparse PCA introduces structural constraints on the features in seeking such a linear combination. Collectively, the derived principal components may still require measuring all the input features. We present a joint group sparse PCA (JGSPCA) algorithm, which forces the basic coefficients corresponding to a group of features to be jointly sparse. Joint sparsity ensures that the complete basis involves only a sparse set of input features, whereas the group sparsity ensures that the structural integrity of the features is maximally preserved. We evaluate the JGSPCA algorithm on the problems of compressed hyperspectral imaging and face recognition. Compressed sensing results show that the proposed method consistently outperforms sparse PCA and group sparse PCA in reconstructing the hyperspectral scenes of natural and man-made objects. The efficacy of the proposed compressed sensing method is further demonstrated in band selection for face recognition.

  13. Extended SWIR imaging sensors for hyperspectral imaging applications

    Weber, A.; Benecke, M.; Wendler, J.; Sieck, A.; Hübner, D.; Figgemeier, H.; Breiter, R.


    AIM has developed SWIR modules including FPAs based on liquid phase epitaxy (LPE) grown MCT usable in a wide range of hyperspectral imaging applications. Silicon read-out integrated circuits (ROIC) provide various integration and readout modes including specific functions for spectral imaging applications. An important advantage of MCT based detectors is the tunable band gap. The spectral sensitivity of MCT detectors can be engineered to cover the extended SWIR spectral region up to 2.5μm without compromising in performance. AIM developed the technology to extend the spectral sensitivity of its SWIR modules also into the VIS. This has been successfully demonstrated for 384x288 and 1024x256 FPAs with 24μm pitch. Results are presented in this paper. The FPAs are integrated into compact dewar cooler configurations using different types of coolers, like rotary coolers, AIM's long life split linear cooler MCC030 or extreme long life SF100 Pulse Tube cooler. The SWIR modules include command and control electronics (CCE) which allow easy interfacing using a digital standard interface. The development status and performance results of AIM's latest MCT SWIR modules suitable for hyperspectral systems and applications will be presented.

  14. Hyperspectral image classifier based on beach spectral feature

    Liang, Zhang; Lianru, Gao; Bing, Zhang


    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

  15. ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery

    Na Li


    Full Text Available The diverse density (DD algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels. However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS sensor and the Push-broom Hyperspectral Imager (PHI are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively.

  16. Detecting pits in tart cherries by hyperspectral transmission imaging

    Qin, Jianwei; Lu, Renfu


    The presence of pits in processed cherry products causes safety concerns for consumers and imposes potential liability for the food industry. The objective of this research was to investigate a hyperspectral transmission imaging technique for detecting the pit in tart cherries. A hyperspectral imaging system was used to acquire transmission images from individual cherry fruit for four orientations before and after pits were removed over the spectral region between 450 nm and 1,000 nm. Cherries of three size groups (small, intermediate, and large), each with two color classes (light red and dark red) were used for determining the effect of fruit orientation, size, and color on the pit detection accuracy. Additional cherries were studied for the effect of defect (i.e., bruises) on the pit detection. Computer algorithms were developed using the neural network (NN) method to classify the cherries with and without the pit. Two types of data inputs, i.e., single spectra and selected regions of interest (ROIs), were compared. The spectral region between 690 nm and 850 nm was most appropriate for cherry pit detection. The NN with inputs of ROIs achieved higher pit detection rates ranging from 90.6% to 100%, with the average correct rate of 98.4%. Fruit orientation and color had a small effect (less than 1%) on pit detection. Fruit size and defect affected pit detection and their effect could be minimized by training the NN with properly selected cherry samples.

  17. Assessing diabetic foot ulcer development risk with hyperspectral tissue oximetry

    Yudovsky, Dmitry; Nouvong, Aksone; Schomacker, Kevin; Pilon, Laurent


    Foot ulceration remains a serious health concern for diabetic patients and has a major impact on the cost of diabetes treatment. Early detection and preventive care, such as offloading or improved hygiene, can greatly reduce the risk of further complications. We aim to assess the use of hyperspectral tissue oximetry in predicting the risk of diabetic foot ulcer formation. Tissue oximetry measurements are performed during several visits with hyperspectral imaging of the feet in type 1 and 2 diabetes mellitus subjects that are at risk for foot ulceration. The data are retrospectively analyzed at 21 sites that ulcerated during the course of our study and an ulceration prediction index is developed. Then, an image processing algorithm based on this index is implemented. This algorithm is able to predict tissue at risk of ulceration with a sensitivity and specificity of 95 and 80%, respectively, for images taken, on average, 58 days before tissue damage is apparent to the naked eye. Receiver operating characteristic analysis is also performed to give a range of sensitivity/specificity values resulting in a Q-value of 89%.

  18. Hyperspectral optical tomography of intrinsic signals in the rat cortex

    Konecky, Soren D.; Wilson, Robert H.; Hagen, Nathan; Mazhar, Amaan; Tkaczyk, Tomasz S.; Frostig, Ron D.; Tromberg, Bruce J.


    Abstract. We introduce a tomographic approach for three-dimensional imaging of evoked hemodynamic activity, using broadband illumination and diffuse optical tomography (DOT) image reconstruction. Changes in diffuse reflectance in the rat somatosensory cortex due to stimulation of a single whisker were imaged at a frame rate of 5 Hz using a hyperspectral image mapping spectrometer. In each frame, images in 38 wavelength bands from 484 to 652 nm were acquired simultaneously. For data analysis, we developed a hyperspectral DOT algorithm that used the Rytov approximation to quantify changes in tissue concentration of oxyhemoglobin (ctHbO2) and deoxyhemoglobin (ctHb) in three dimensions. Using this algorithm, the maximum changes in ctHbO2 and ctHb were found to occur at 0.29±0.02 and 0.66±0.04  mm beneath the surface of the cortex, respectively. Rytov tomographic reconstructions revealed maximal spatially localized increases and decreases in ctHbO2 and ctHb of 321±53 and 555±96  nM, respectively, with these maximum changes occurring at 4±0.2  s poststimulus. The localized optical signals from the Rytov approximation were greater than those from modified Beer–Lambert, likely due in part to the inability of planar reflectance to account for partial volume effects. PMID:26835483

  19. Hyperspectral image segmentation of the common bile duct

    Samarov, Daniel; Wehner, Eleanor; Schwarz, Roderich; Zuzak, Karel; Livingston, Edward


    Over the course of the last several years hyperspectral imaging (HSI) has seen increased usage in biomedicine. Within the medical field in particular HSI has been recognized as having the potential to make an immediate impact by reducing the risks and complications associated with laparotomies (surgical procedures involving large incisions into the abdominal wall) and related procedures. There are several ongoing studies focused on such applications. Hyperspectral images were acquired during pancreatoduodenectomies (commonly referred to as Whipple procedures), a surgical procedure done to remove cancerous tumors involving the pancreas and gallbladder. As a result of the complexity of the local anatomy, identifying where the common bile duct (CBD) is can be difficult, resulting in comparatively high incidents of injury to the CBD and associated complications. It is here that HSI has the potential to help reduce the risk of such events from happening. Because the bile contained within the CBD exhibits a unique spectral signature, we are able to utilize HSI segmentation algorithms to help in identifying where the CBD is. In the work presented here we discuss approaches to this segmentation problem and present the results.

  20. Estimations of Nitrogen Concentration in Sugarcane Using Hyperspectral Imagery

    Poonsak Miphokasap


    Full Text Available This study aims to estimate the spatial variation of sugarcane Canopy Nitrogen Concentration (CNC using spectral data, which were measured from a spaceborne hyperspectral image. Stepwise Multiple Linear Regression (SMLR and Support Vector Regression (SVR were applied to calibrate and validate the CNC estimation models. The raw spectral reflectance was transformed into a First-Derivative Spectrum (FDS and absorption features to remove the spectral noise and finally used as input variables. The results indicate that the estimation models developed by non-linear SVR based Radial Basis Function (RBF kernel yield the higher correlation coefficient with CNC compared with the models computed by SMLR. The best model shows the coefficient of determination value of 0.78 and Root Mean Square Error (RMSE value of 0.035% nitrogen. The narrow sensitive spectral wavelengths for quantifying nitrogen content in the combined cultivar environments existed mainly in the electromagnetic spectrum of the visible-red, longer portion of red edge, shortwave infrared regions and far-near infrared. The most important conclusion from this experiment is that spectral signals from the space hyperspectral data contain the meaningful information for quantifying sugarcane CNC across larger geographic areas. The nutrient deficient areas could be corrected by applying suitable farm management.

  1. Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

    Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon


    A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

  2. An optical scanning subsystem for a UAS-enabled hyperspectral radiometer

    National Aeronautics and Space Administration — Hyperspectral radiometers will be integrated with an optical scanning subsystem to measure remote sensing reflectance spectra over the ocean.  The entire scanning...

  3. Physiological interpretation of a hyperspectral time series in a citrus orchard

    Stuckens, J.; Dzikiti, S.; Verstraeten, W.W.; Verreynne, J.S.; Swennen, R.; Coppin, P.


    Hyperspectral remote sensing for monitoring horticultural production systems requires the understanding of how plant physiology, canopy structure, management and solar elevation affect the retrieved canopy reflectance during different stages of the phenological cycle. Hence, the objective of this

  4. [Hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status].

    Tan, Chang-Wei; Zhou, Qing-Bo; Qi, La; Zhuang, Heng-Yang


    The correlations of rice plant nitrogen content with raw hyperspectral reflectance, first derivative hyperspectral reflectance, and hyperspectral characteristic parameters were analyzed, and the hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status with these remote sensing parameters as independent variables were constructed and validated. The results indicated that the nitrogen content in rice plant organs had a variation trend of stem plant nitrogen nutritional status, with the decisive coefficients (R2) being 0.7996 and 0.8606, respectively; while the model with vegetation index (SDr - SDb) / (SDr + SDb) as independent variable, i. e., y = 365.871 + 639.323 ((SDr - SDb) / (SDr + SDb)), was most fit rice plant nitrogen content, with R2 = 0.8755, RMSE = 0.2372 and relative error = 11.36%, being able to quantitatively diagnose the nitrogen nutritional status of rice.

  5. A new technique for extracting the red edge position from hyperspectral data : the linear extrapolation method

    Cho, M.A.; Skidmore, A.K.


    There is increasing interest in using hyperspectral data for quantitative characterization of vegetation in spatial and temporal scopes. Many spectral indices are being developed to improve vegetation sensitivity by minimizing the background influence. The chlorophyll absorption continuum index

  6. Particulate absorption properties in the Red Sea from hyperspectral particulate absorption spectra

    Tiwari, Surya Prakash; Zarokanellos, Nikolaos; Kheireddine, Malika; Shanmugam, Palanisamy; Jones, Burton


    This paper aims to describe the variability of particulate absorption properties using a unique hyperspectral dataset collected in the Red Sea as part of the TARA Oceans expedition. The absorption contributions by phytoplankton (aph) and non

  7. Hyperspectral radiometric observation of the northeast Arabians Sea during April 2006

    Sarangi, R.K.; Singh, S.; Dwivedi, R.M.; Matondkar, S.G.P.

    nm. Detailed analysis with High Performance Liquid Chromatography (HPLC) data and comparison with the water composition of hyperspectral radiometer results show that the marine cyanophyte, Trichodesmium bloom produces high pigment concentrations...


    T. H. Kurz


    Full Text Available Compact and lightweight hyperspectral imagers allow the application of close range hyperspectral imaging with a ground based scanning setup for geological fieldwork. Using such a scanning setup, steep cliff sections and quarry walls can be scanned with a more appropriate viewing direction and a higher image resolution than from airborne and spaceborne platforms. Integration of the hyperspectral imagery with terrestrial lidar scanning provides the hyperspectral information in a georeferenced framework and enables measurement at centimetre scale. In this paper, three geological case studies are used to demonstrate the potential of this method for rock characterisation. Two case studies are applied to carbonate quarries where mapping of different limestone and dolomite types was required, as well as measurements of faults and layer thicknesses from inaccessible parts of the quarries. The third case study demonstrates the method using artificial lighting, applied in a subsurface scanning scenario where solar radiation cannot be utilised.

  9. Improved discrete swarm intelligence algorithms for endmember extraction from hyperspectral remote sensing images

    Su, Yuanchao; Sun, Xu; Gao, Lianru; Li, Jun; Zhang, Bing


    Endmember extraction is a key step in hyperspectral unmixing. A new endmember extraction framework is proposed for hyperspectral endmember extraction. The proposed approach is based on the swarm intelligence (SI) algorithm, where discretization is used to solve the SI algorithm because pixels in a hyperspectral image are naturally defined within a discrete space. Moreover, a "distance" factor is introduced into the objective function to limit the endmember numbers which is generally limited in real scenarios, while traditional SI algorithms likely produce superabundant spectral signatures, which generally belong to the same classes. Three endmember extraction methods are proposed based on the artificial bee colony, ant colony optimization, and particle swarm optimization algorithms. Experiments with both simulated and real hyperspectral images indicate that the proposed framework can improve the accuracy of endmember extraction.


    In this study, hyperspectral fluorescence imaging techniques were investigated for detection of microbial biofilm on stainless steel plates typically used to manufacture food processing equipment. Stainless steel coupons were immersed in bacterium cultures consisting of nonpathogenic E. coli, Pseudo...

  11. GPU implementation of discrete particle swarm optimization algorithm for endmember extraction from hyperspectral image

    Yu, Chaoyin; Yuan, Zhengwu; Wu, Yuanfeng


    Hyperspectral image unmixing is an important part of hyperspectral data analysis. The mixed pixel decomposition consists of two steps, endmember (the unique signatures of pure ground components) extraction and abundance (the proportion of each endmember in each pixel) estimation. Recently, a Discrete Particle Swarm Optimization algorithm (DPSO) was proposed for accurately extract endmembers with high optimal performance. However, the DPSO algorithm shows very high computational complexity, which makes the endmember extraction procedure very time consuming for hyperspectral image unmixing. Thus, in this paper, the DPSO endmember extraction algorithm was parallelized, implemented on the CUDA (GPU K20) platform, and evaluated by real hyperspectral remote sensing data. The experimental results show that with increasing the number of particles the parallelized version obtained much higher computing efficiency while maintain the same endmember exaction accuracy.


    O. Brovkina


    Full Text Available Satellite-based hyperspectral sensors provide spectroscopic information in relatively narrow contiguous spectral bands over a large area which can be useful in forestry applications. This study evaluates the potential of satellite hyperspectral Resurs-P data for forest species mapping. Firstly, a comparative study between top of canopy reflectance obtained from the Resurs-P, from the airborne hyperspectral scanner CASI and from field measurement (FieldSpec ASD 4 on selected vegetation cover types is conducted. Secondly, Resurs-P data is tested in classification and verification of different forest species compartments. The results demonstrate that satellite hyperspectral Resurs-P sensor can produce useful informational and show good performance for forest species classification comparable both with forestry map and classification from airborne CASI data, but also indicate that developments in pre-processing steps are still required to improve the mapping level.

  13. The use of hyperspectral remote sensing for mapping the age composition of forest stands

    Skoupý, O.; Zejdová, L.; Hanuš, Jan


    Roč. 58, č. 6 (2012), s. 287-297 ISSN 1212-4834 Institutional support: RVO:67179843 Keywords : age classification * forestry * hyperspectral * object oriented * segmentation * spruce Subject RIV: EH - Ecology, Behaviour

  14. Near-infrared hyperspectral imaging for quality analysis of agricultural and food products

    Singh, C. B.; Jayas, D. S.; Paliwal, J.; White, N. D. G.


    Agricultural and food processing industries are always looking to implement real-time quality monitoring techniques as a part of good manufacturing practices (GMPs) to ensure high-quality and safety of their products. Near-infrared (NIR) hyperspectral imaging is gaining popularity as a powerful non-destructive tool for quality analysis of several agricultural and food products. This technique has the ability to analyse spectral data in a spatially resolved manner (i.e., each pixel in the image has its own spectrum) by applying both conventional image processing and chemometric tools used in spectral analyses. Hyperspectral imaging technique has demonstrated potential in detecting defects and contaminants in meats, fruits, cereals, and processed food products. This paper discusses the methodology of hyperspectral imaging in terms of hardware, software, calibration, data acquisition and compression, and development of prediction and classification algorithms and it presents a thorough review of the current applications of hyperspectral imaging in the analyses of agricultural and food products.

  15. Recent progress of push-broom infrared hyper-spectral imager in SITP

    Wang, Yueming; Hu, Weida; Shu, Rong; Li, Chunlai; Yuan, Liyin; Wang, Jianyu


    In the past decades, hyper-spectral imaging technologies were well developed in SITP, CAS. Many innovations for system design and key parts of hyper-spectral imager were finished. First airborne hyper-spectral imager operating from VNIR to TIR in the world was emerged in SITP. It is well known as OMIS(Operational Modular Imaging Spectrometer). Some new technologies were introduced to improve the performance of hyper-spectral imaging system in these years. A high spatial space-borne hyper-spectral imager aboard Tiangong-1 spacecraft was launched on Sep.29, 2011. Thanks for ground motion compensation and high optical efficiency prismatic spectrometer, a large amount of hyper-spectral imagery with high sensitivity and good quality were acquired in the past years. Some important phenomena were observed. To diminish spectral distortion and expand field of view, new type of prismatic imaging spectrometer based curved prism were proposed by SITP. A prototype of hyper-spectral imager based spherical fused silica prism were manufactured, which can operate from 400nm 2500nm. We also made progress in the development of LWIR hyper-spectral imaging technology. Compact and low F number LWIR imaging spectrometer was designed, manufactured and integrated. The spectrometer operated in a cryogenically-cooled vacuum box for background radiation restraint. The system performed well during flight experiment in an airborne platform. Thanks high sensitivity FPA and high performance optics, spatial resolution and spectral resolution and SNR of system are improved enormously. However, more work should be done for high radiometric accuracy in the future.

  16. Building of the system for managing and analyzing the hyperspectral data of drilling core

    Huang Yanju; Zhang Jielin; Wang Junhu


    Drilling core logging is very important for geological exploration, hyperspectral detection provides a totally new method for drilling core logging. To use and analyze the drilling core data more easily, and especially store them permanently, a system is built for analyzing and managing the hyperspectral data. The system provides a convenient way to sort the core data, and extract the spectral characteristics, which is the basis for the following mineral identification. (authors)


    Aasen, Helge


    Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. This study investigates th...

  18. Hyper-spectral frequency selection for the classification of vegetation diseases

    Dijkstra, Klaas; van de Loosdrecht, Jaap; Schomaker, Lambert; Wiering, Marco


    Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the...

  19. Hyperspectral imaging in medicine: image pre-processing problems and solutions in Matlab.

    Koprowski, Robert


    The paper presents problems and solutions related to hyperspectral image pre-processing. New methods of preliminary image analysis are proposed. The paper shows problems occurring in Matlab when trying to analyse this type of images. Moreover, new methods are discussed which provide the source code in Matlab that can be used in practice without any licensing restrictions. The proposed application and sample result of hyperspectral image analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Bridging research with innovative products: a compact hyperspectral camera for investigating artworks: a feasibility study

    Cucci, Costanza; Casini, Andrea; Stefani, Lorenzo; Picollo, Marcello; Jussila, Jouni


    For more than a decade, a number of studies and research projects have been devoted to customize hyperspectral imaging techniques to the specific needs of conservation and applications in museum context. A growing scientific literature definitely demonstrated the effectiveness of reflectance hyperspectral imaging for non-invasive diagnostics and highquality documentation of 2D artworks. Additional published studies tackle the problems of data-processing, with a focus on the development of algorithms and software platforms optimised for visualisation and exploitation of hyperspectral bigdata sets acquired on paintings. This scenario proves that, also in the field of Cultural Heritage (CH), reflectance hyperspectral imaging has nowadays reached the stage of mature technology, and is ready for the transition from the R&D phase to the large-scale applications. In view of that, a novel concept of hyperspectral camera - featuring compactness, lightness and good usability - has been developed by SPECIM, Spectral Imaging Ltd. (Oulu, Finland), a company in manufacturing products for hyperspectral imaging. The camera is proposed as new tool for novel applications in the field of Cultural Heritage. The novelty of this device relies in its reduced dimensions and weight and in its user-friendly interface, which make this camera much more manageable and affordable than conventional hyperspectral instrumentation. The camera operates in the 400-1000nm spectral range and can be mounted on a tripod. It can operate from short-distance (tens of cm) to long distances (tens of meters) with different spatial resolutions. The first release of the prototype underwent a preliminary in-depth experimentation at the IFAC-CNR laboratories. This paper illustrates the feasibility study carried out on the new SPECIM hyperspectral camera, tested under different conditions on laboratory targets and artworks with the specific aim of defining its potentialities and weaknesses in its use in the

  1. Excitation-scanning hyperspectral imaging system for microscopic and endoscopic applications

    Mayes, Sam A.; Leavesley, Silas J.; Rich, Thomas C.


    Current microscopic and endoscopic technologies for cancer screening utilize white-light illumination sources. Hyper-spectral imaging has been shown to improve sensitivity while retaining specificity when compared to white-light imaging in both microscopy and in vivo imaging. However, hyperspectral imaging methods have historically suffered from slow acquisition times due to the narrow bandwidth of spectral filters. Often minutes are required to gather a full image stack. We have developed a novel approach called excitation-scanning hyperspectral imaging that provides 2-3 orders of magnitude increased signal strength. This reduces acquisition times significantly, allowing for live video acquisition. Here, we describe a preliminary prototype excitation-scanning hyperspectral imaging system that can be coupled with endoscopes or microscopes for hyperspectral imaging of tissues and cells. Our system is comprised of three subsystems: illumination, transmission, and imaging. The illumination subsystem employs light-emitting diode arrays to illuminate at different wavelengths. The transmission subsystem utilizes a unique geometry of optics and a liquid light guide. Software controls allow us to interface with and control the subsystems and components. Digital and analog signals are used to coordinate wavelength intensity, cycling and camera triggering. Testing of the system shows it can cycle 16 wavelengths at as fast as 1 ms per cycle. Additionally, more than 18% of the light transmits through the system. Our setup should allow for hyperspectral imaging of tissue and cells in real time.

  2. Direct Georeferencing of a Pushbroom, Lightweight Hyperspectral System for Mini-UAV Applications

    Marion Jaud


    Full Text Available Hyperspectral imagery has proven its potential in many research applications, especially in the field of environmental sciences. Currently, hyperspectral imaging is generally performed by satellite or aircraft platforms, but mini-UAV (Unmanned Aerial Vehicle platforms (<20 kg are now emerging. On such platforms, payload restrictions are critical, so sensors must be selected according to stringent specifications. This article presents the integration of a light pushbroom hyperspectral sensor onboard a multirotor UAV, which we have called Hyper-DRELIO (Hyperspectral DRone for Environmental and LIttoral Observations. This article depicts the system design: the UAV platform, the imaging module, the navigation module, and the interfacing between the different elements. Pushbroom sensors offer a better combination of spatial and spectral resolution than full-frame cameras. Nevertheless, data georectification has to be performed line by line, the quality of direct georeferencing being limited by mechanical stability, good timing accuracy, and the resolution and accuracy of the proprioceptive sensors. A georegistration procedure is proposed for geometrical pre-processing of hyperspectral data. The specifications of Hyper-DRELIO surveys are described through two examples of surveys above coastal or inland waters, with different flight altitudes. This system can collect hyperspectral data in VNIR (Visible and Near InfraRed domain above small study sites (up to about 4 ha with both high spatial resolution (<10 cm and high spectral resolution (1.85 nm and with georectification accuracy on the order of 1 to 2 m.

  3. Hyperspectral and multispectral data fusion based on linear-quadratic nonnegative matrix factorization

    Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz


    This paper proposes three multisharpening approaches to enhance the spatial resolution of urban hyperspectral remote sensing images. These approaches, related to linear-quadratic spectral unmixing techniques, use a linear-quadratic nonnegative matrix factorization (NMF) multiplicative algorithm. These methods begin by unmixing the observable high-spectral/low-spatial resolution hyperspectral and high-spatial/low-spectral resolution multispectral images. The obtained high-spectral/high-spatial resolution features are then recombined, according to the linear-quadratic mixing model, to obtain an unobservable multisharpened high-spectral/high-spatial resolution hyperspectral image. In the first designed approach, hyperspectral and multispectral variables are independently optimized, once they have been coherently initialized. These variables are alternately updated in the second designed approach. In the third approach, the considered hyperspectral and multispectral variables are jointly updated. Experiments, using synthetic and real data, are conducted to assess the efficiency, in spatial and spectral domains, of the designed approaches and of linear NMF-based approaches from the literature. Experimental results show that the designed methods globally yield very satisfactory spectral and spatial fidelities for the multisharpened hyperspectral data. They also prove that these methods significantly outperform the used literature approaches.

  4. Materials for passively safe reactors

    Simnad, T.


    Future nuclear power capacity will be based on reactor designs that include passive safety features if recent progress in advanced nuclear power developments is realized. There is a high potential for nuclear systems that are smaller and easier to operate than the current generation of reactors, especially when passive or intrinsic characteristics are applied to provide inherent stability of the chain reaction and to minimize the burden on equipment and operating personnel. Taylor, has listed the following common generic technical features as the most important goals for the principal reactor development systems: passive stability, simplification, ruggedness, case of operation, and modularity. Economic competitiveness also depends on standardization and assurance of licensing. The performance of passively safe reactors will be greatly influenced by the successful development of advanced fuels and materials that will provide lower fuel-cycle costs. A dozen new designs of advanced power reactors have been described recently, covering a wide spectrum of reactor types, including pressurized water reactors, boiling water reactors, heavy-water reactors, modular high-temperature gas-cooled reactors (MHTGRs), and fast breeder reactors. These new designs address the need for passive safety features as well as the requirement of economic competitiveness

  5. Miniature infrared hyperspectral imaging sensor for airborne applications

    Hinnrichs, Michele; Hinnrichs, Bradford; McCutchen, Earl


    Pacific Advanced Technology (PAT) has developed an infrared hyperspectral camera, both MWIR and LWIR, small enough to serve as a payload on a miniature unmanned aerial vehicles. The optical system has been integrated into the cold-shield of the sensor enabling the small size and weight of the sensor. This new and innovative approach to infrared hyperspectral imaging spectrometer uses micro-optics and will be explained in this paper. The micro-optics are made up of an area array of diffractive optical elements where each element is tuned to image a different spectral region on a common focal plane array. The lenslet array is embedded in the cold-shield of the sensor and actuated with a miniature piezo-electric motor. This approach enables rapid infrared spectral imaging with multiple spectral images collected and processed simultaneously each frame of the camera. This paper will present our optical mechanical design approach which results in an infrared hyper-spectral imaging system that is small enough for a payload on a mini-UAV or commercial quadcopter. The diffractive optical elements used in the lenslet array are blazed gratings where each lenslet is tuned for a different spectral bandpass. The lenslets are configured in an area array placed a few millimeters above the focal plane and embedded in the cold-shield to reduce the background signal normally associated with the optics. We have developed various systems using a different number of lenslets in the area array. Depending on the size of the focal plane and the diameter of the lenslet array will determine the spatial resolution. A 2 x 2 lenslet array will image four different spectral images of the scene each frame and when coupled with a 512 x 512 focal plane array will give spatial resolution of 256 x 256 pixel each spectral image. Another system that we developed uses a 4 x 4 lenslet array on a 1024 x 1024 pixel element focal plane array which gives 16 spectral images of 256 x 256 pixel resolution each

  6. Passive inhalation of cannabis smoke

    Law, B; Mason, P A; Moffat, A C; King, L J; Marks, V


    Six volunteers each smoked simultaneously, in a small unventilated room (volume 27 950 liter), a cannabis cigarette containing 17.1 mg delta 9-tetrahydrocannabinol (THC). A further four subjects - passive inhalers - remained in the room during smoking and afterwards for a total of 3 h. Blood and urine samples were taken from all ten subjects and analyzed by radioimmunoassay for THC metabolites. The blood samples from the passive subjects taken up to 3 h after the start of exposure to cannabis smoke showed a complete absence of cannabinoids. In contrast, their urine samples taken up to 6 h after exposure showed significant concentrations of cannabinoid metabolites (less than or equal to 6.8 ng ml-1). These data, taken with the results of other workers, show passive inhalation of cannabis smoke to be possible. These results have important implications for forensic toxicologists who are frequently called upon to interpret cannabinoid levels in body fluids.

  7. Active Versus Passive Academic Networking

    Goel, Rajeev K.; Grimpe, Christoph


    This paper examines determinants of networking by academics. Using information from a unique large survey of German researchers, the key contribution focuses on the active versus passive networking distinction. Is active networking by researchers a substitute or a complement to passive networking......? Other contributions include examining the role of geographic factors in networking and whether research bottlenecks affect a researcher's propensity to network. Are the determinants of European conference participation by German researchers different from conferences in rest of the world? Results show...... that some types of passive academic networking are complementary to active networking, while others are substitute. Further, we find differences in factors promoting participation in European conferences versus conferences in rest of the world. Finally, publishing bottlenecks as a group generally do...

  8. Protocol Monitoring Passive Solar Energy

    Van den Ham, E.R.; Bosselaar, L.


    A method has been developed by means of which the contribution of passive solar energy to the Dutch energy balance can be quantified univocally. The contribution was 57 PJ in 1990 and also 57 PJ in 1995. The efficiency of passive solar energy systems increased from -31.5% to -28.1% in the period 1990-1995, mainly as a result of the use of extra insulating glazing. As a result of the reduction of energy consumption for heating in houses it is expected that the extra contribution of 2 PJ will not be realized in the year 2010. It is suggested that the method to determine the absolute contribution of passive solar energy to the energy demand of dwellings is to be included in the protocol monitoring renewable energy. For the method to be included in the energy statistics of Statistics Netherlands (CBS) it can be considered only to take into account the difference compared to 1990. 11 refs

  9. Hyperspectral remote sensing techniques for early detection of plant diseases

    Krezhova, Dora; Maneva, Svetla; Zdravev, Tomas

    Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications in Earth observation. Nowadays spectral remote sensing techniques allow presymptomatic monitoring of changes in the physiological state of plants with high spectral resolution. Hyperspectral leaf reflectance and chlorophyll fluorescence proved to be highly suitable for identification of growth anomalies of cultural plants that result from the environmental changes and different stress factors. Hyperspectral technologies can find place in many scientific areas, as well as for monitoring of plants status and functioning to help in making timely management decisions. This research aimed to detect a presence of viral infection in young pepper plants (Capsicum annuum L.) caused by Cucumber Mosaic Virus (CMV) by using hyperspectral reflectance and fluorescence data and to assess the effect of some growth regulators on the development of the disease. In Bulgaria CMV is one of the widest spread pathogens, causing the biggest economical losses in crop vegetable production. Leaf spectral reflectance and fluorescence data were collected by a portable fibre-optics spectrometer in the spectral ranges 450÷850 nm and 600-900 nm. Greenhouse experiment with pepper plants of two cultivars, Sivria (sensitive to CMV) and Ostrion (resistant to CMV) were used. The plants were divided into six groups. The first group consisted of healthy (control) plants. At growth stage 4-6 expanded leaf, the second group was inoculated with CMV. The other four groups were treated with growth regulators: Spermine, MEIA (beta-monomethyl ester of itaconic acid), BTH (benzo(1,2,3)thiadiazole-7-carbothioic acid-S-methyl ester) and Phytoxin. On the next day, the pepper plants of these four groups were inoculated with CMV. The viral concentrations in the plants were determined by the serological method DAS-ELISA. Statistical, first derivative and cluster analysis were applied and several vegetation indices were

  10. Hyperspectral imaging system for disease scanning on banana plants

    Ochoa, Daniel; Cevallos, Juan; Vargas, German; Criollo, Ronald; Romero, Dennis; Castro, Rodrigo; Bayona, Oswaldo


    Black Sigatoka (BS) is a banana plant disease caused by the fungus Mycosphaerella fijiensis. BS symptoms can be observed at late infection stages. By that time, BS has probably spread to other plants. In this paper, we present our current work on building an hyper-spectral (HS) imaging system aimed at in-vivo detection of BS pre-symptomatic responses in banana leaves. The proposed imaging system comprises a motorized stage, a high-sensitivity VIS-NIR camera and an optical spectrograph. To capture images of the banana leaf, the stage's speed and camera's frame rate must be computed to reduce motion blur and to obtain the same resolution along both spatial dimensions of the resulting HS cube. Our continuous leaf scanning approach allows imaging leaves of arbitrary length with minimum frame loss. Once the images are captured, a denoising step is performed to improve HS image quality and spectral profile extraction.

  11. Development of TMA-based imaging system for hyperspectral application

    Choi, Young-Wan; Yang, Seung-Uk; Kang, Myung-Seok; Kim, Ee-Eul


    Funded by the Ministry of Commerce, Industry, and Energy of Korea, SI initiated the development of the prototype model of TMA-based electro-optical system as part of the national space research and development program. Its optical aperture diameter is 120 mm, the effective focal length is 462 mm, and its full field-of-view is 5.08 degrees. The dimension is of about 600 mm × 400 mm × 400 mm and the weight is less than 15 kg. To demonstrate its performance, hyper-spectral imaging based on linear spectral filter is selected for the application of the prototype. The spectral resolution will be less than 10 nm and the number of channels will be more than 40 in visible and nearinfrared region. In this paper, the progress made so far on the prototype development will be presented

  12. Performance metrics for the evaluation of hyperspectral chemical identification systems

    Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay


    Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

  13. Efficient and compact hyperspectral imager for space-borne applications

    Pisani, Marco; Zucco, Massimo


    In the last decades Hyperspectral Imager (HI) have become irreplaceable space-borne instruments for an increasing number of applications. A number of HIs are now operative onboard (e.g. CHRIS on PROBA), others are going to be launched (e.g. PRISMA, EnMAP, HyspIRI), many others are at the breadboard level. The researchers goal is to realize HI with high spatial and spectral resolution, having low weight and contained dimensions. The most common HI technique is based on the use of a dispersive mean (a grating or a prism) or on the use of band pass filters (tunable or linear variable). These approaches have the advantages of allowing compact devices. Another approach is based on the use of interferometer based spectrometers (Michelson or Sagnac type). The advantage of the latter is a very high efficiency in light collection because of the well-known Felgett and Jaquinot principles.

  14. [Research on hyperspectral remote sensing in monitoring snow contamination concentration].

    Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan


    Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well.

  15. Hyperspectral tomography based on multi-mode absorption spectroscopy (MUMAS)

    Dai, Jinghang; O'Hagan, Seamus; Liu, Hecong; Cai, Weiwei; Ewart, Paul


    This paper demonstrates a hyperspectral tomographic technique that can recover the temperature and concentration field of gas flows based on multi-mode absorption spectroscopy (MUMAS). This method relies on the recently proposed concept of nonlinear tomography, which can take full advantage of the nonlinear dependency of MUMAS signals on temperature and enables 2D spatial resolution of MUMAS which is naturally a line-of-sight technique. The principles of MUMAS and nonlinear tomography, as well as the mathematical formulation of the inversion problem, are introduced. Proof-of-concept numerical demonstrations are presented using representative flame phantoms and assuming typical laser parameters. The results show that faithful reconstruction of temperature distribution is achievable when a signal-to-noise ratio of 20 is assumed. This method can potentially be extended to simultaneously reconstructing distributions of temperature and the concentration of multiple flame species.

  16. Spectral unmixing of hyperspectral data to map bauxite deposits

    Shanmugam, Sanjeevi; Abhishekh, P. V.


    This paper presents a study about the potential of remote sensing in bauxite exploration in the Kolli hills of Tamilnadu state, southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM - DEM in this study. A new approach of spectral unmixing of ASTER image data delineated areas rich in alumina. Various geological and geomorphological parameters that control bauxite formation were also derived from the ASTER image. All these information, when integrated, showed that there are 16 cappings (including the existing mines) that satisfy most of the conditions favouring bauxitization in the Kolli Hills. The study concludes that spectral unmixing of hyperspectral satellite data in the VNIR and SWIR regions may be combined with the terrain parameters to get accurate information about bauxite deposits, including their quality.

  17. Geometric Correction of PHI Hyperspectral Image without Ground Control Points

    Luan, Kuifeng; Tong, Xiaohua; Liu, Xiangfeng; Ma, Yanhua; Shu, Rong; Xu, Weiming


    Geometric correction without ground control points (GCPs) is a very important topic. Conventional airborne photogrammetry is difficult to implement in areas where the installation of GCPs is not available. The technical of integrated GPS/INS systems providing the positioning and attitude of airborne systems is a potential solution in such areas. This paper first states the principle of geometric correction based on a combination of GPS and INS then the error of the geometric correction of Pushbroom Hyperspectral Imager (PHI) without GCP was analysed, then a flight test was carried out in an area of Damxung, Tibet. The experiment result showed that the error at straight track was small, generally less than 1 pixel, while the maximum error at cross track direction, was close to 2 pixels. The results show that geometric correction of PHI without GCP enables a variety of mapping products to be generated from airborne navigation and imagery data


    L. Annala


    Full Text Available Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

  19. Practical Approach for Hyperspectral Image Processing in Python

    Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.


    Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

  20. Passivation of high temperature superconductors

    Vasquez, Richard P. (Inventor)


    The surface of high temperature superconductors such as YBa2Cu3O(7-x) are passivated by reacting the native Y, Ba and Cu metal ions with an anion such as sulfate or oxalate to form a surface film that is impervious to water and has a solubility in water of no more than 10(exp -3) M. The passivating treatment is preferably conducted by immersing the surface in dilute aqueous acid solution since more soluble species dissolve into the solution. The treatment does not degrade the superconducting properties of the bulk material.

  1. Investigations on passive containment cooling

    Knebel, J.U.; Cheng, X.; Neitzel, H.J.; Erbacher, F.J.; Hofmann, F.


    The composite containment design for advanced LWRs that has been examined under the PASCO project is a promising design concept for purely passive decay heat removal after a severe accident. The passive cooling processes applied are natural convection and radiative heat transfer. Heat transfer through the latter process removes at an emission coefficient of 0.9 about 50% of the total heat removed via the steel containment, and thus is an essential factor. The heat transferring surfaces must have a high emission coefficient. The sump cooling concept examined under the SUCO project achieves a steady, natural convection-driven flow from the heat source to the heat sink. (orig./CB) [de

  2. Passive solar offices: integrated design

    Evans, B


    Passive solar design in out-of-town offices can remove the need for air-conditioning by making greater use of daylight and natural ventilation. To promote the use of passive solar energy a series of design studies are being run by the Energy Technology Support Unit on behalf of the Department of Energy. The three reported here are designs for out-of-town business buildings. Each is a hypothetical building designed to a realistic brief for an organisation taking the role of real client. (author).

  3. The Danish Reportive Passive as a Non-Canonical Passive

    Ørsnes, Bjarne


    Danish passive utterance and cognitive verbs allow a construction where the subject of an infinitival complement is raised: Peter siges at være bortrejst (‘Peter is said to be out of town’). Contrary to English, these verbs are not ECM-verbs or subject-to-object raising verbs in the active...

  4. Hyperspectral Remote Sensing of Terrestrial Ecosystem Productivity from ISS

    Huemmrich, K. F.; Campbell, P. K. E.; Gao, B. C.; Flanagan, L. B.; Goulden, M.


    Data from the Hyperspectral Imager for Coastal Ocean (HICO), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. The ISS orbit introduces both limitations and opportunities for observing ecosystem dynamics. Twenty six HICO images were used from four study sites representing different vegetation types: grasslands, shrubland, and forest. Gross ecosystem production (GEP) data from eddy covariance were matched with HICO-derived spectra. Multiple algorithms were successful relating spectral reflectance with GEP, including: Spectral Vegetation Indices (SVI), SVI in a light use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to Multiband Hyperspectral Indices (MHI) from stepwise regressions and Partial Least Squares Regression (PLSR). Algorithms were able to achieve r2 better than 0.7 for both GEP at the overpass time and daily GEP. These algorithms were successful using a diverse set of observations combining data from multiple years, multiple times during growing season, different times of day, with different view angles, and different vegetation types. The demonstrated robustness of the algorithms presented in this study over these conditions provides some confidence in mapping spatial patterns of GEP, describing variability within fields as well as the regional patterns based only on spectral reflectance information. The ISS orbit provides periods with multiple observations collected at different times of the day within a period of a few days. Diurnal GEP patterns were estimated comparing the half-hourly average GEP from the flux tower against HICO estimates of GEP (r2=0.87) if morning, midday, and afternoon observations were available for average fluxes in the time period.

  5. Nonparametric, Coupled ,Bayesian ,Dictionary ,and Classifier Learning for Hyperspectral Classification.

    Akhtar, Naveed; Mian, Ajmal


    We present a principled approach to learn a discriminative dictionary along a linear classifier for hyperspectral classification. Our approach places Gaussian Process priors over the dictionary to account for the relative smoothness of the natural spectra, whereas the classifier parameters are sampled from multivariate Gaussians. We employ two Beta-Bernoulli processes to jointly infer the dictionary and the classifier. These processes are coupled under the same sets of Bernoulli distributions. In our approach, these distributions signify the frequency of the dictionary atom usage in representing class-specific training spectra, which also makes the dictionary discriminative. Due to the coupling between the dictionary and the classifier, the popularity of the atoms for representing different classes gets encoded into the classifier. This helps in predicting the class labels of test spectra that are first represented over the dictionary by solving a simultaneous sparse optimization problem. The labels of the spectra are predicted by feeding the resulting representations to the classifier. Our approach exploits the nonparametric Bayesian framework to automatically infer the dictionary size--the key parameter in discriminative dictionary learning. Moreover, it also has the desirable property of adaptively learning the association between the dictionary atoms and the class labels by itself. We use Gibbs sampling to infer the posterior probability distributions over the dictionary and the classifier under the proposed model, for which, we derive analytical expressions. To establish the effectiveness of our approach, we test it on benchmark hyperspectral images. The classification performance is compared with the state-of-the-art dictionary learning-based classification methods.

  6. Multi- and hyperspectral geologic remote sensing: A review

    van der Meer, Freek D.; van der Werff, Harald M. A.; van Ruitenbeek, Frank J. A.; Hecker, Chris A.; Bakker, Wim H.; Noomen, Marleen F.; van der Meijde, Mark; Carranza, E. John M.; Smeth, J. Boudewijn de; Woldai, Tsehaie


    Geologists have used remote sensing data since the advent of the technology for regional mapping, structural interpretation and to aid in prospecting for ores and hydrocarbons. This paper provides a review of multispectral and hyperspectral remote sensing data, products and applications in geology. During the early days of Landsat Multispectral scanner and Thematic Mapper, geologists developed band ratio techniques and selective principal component analysis to produce iron oxide and hydroxyl images that could be related to hydrothermal alteration. The advent of the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) with six channels in the shortwave infrared and five channels in the thermal region allowed to produce qualitative surface mineral maps of clay minerals (kaolinite, illite), sulfate minerals (alunite), carbonate minerals (calcite, dolomite), iron oxides (hematite, goethite), and silica (quartz) which allowed to map alteration facies (propylitic, argillic etc.). The step toward quantitative and validated (subpixel) surface mineralogic mapping was made with the advent of high spectral resolution hyperspectral remote sensing. This led to a wealth of techniques to match image pixel spectra to library and field spectra and to unravel mixed pixel spectra to pure endmember spectra to derive subpixel surface compositional information. These products have found their way to the mining industry and are to a lesser extent taken up by the oil and gas sector. The main threat for geologic remote sensing lies in the lack of (satellite) data continuity. There is however a unique opportunity to develop standardized protocols leading to validated and reproducible products from satellite remote sensing for the geology community. By focusing on geologic mapping products such as mineral and lithologic maps, geochemistry, P-T paths, fluid pathways etc. the geologic remote sensing community can bridge the gap with the geosciences community. Increasingly

  7. Endoscopic hyperspectral imaging: light guide optimization for spectral light source

    Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.


    Hyperspectral imaging (HSI) is a technology used in remote sensing, food processing and documentation recovery. Recently, this approach has been applied in the medical field to spectrally interrogate regions of interest within respective substrates. In spectral imaging, a two (spatial) dimensional image is collected, at many different (spectral) wavelengths, to sample spectral signatures from different regions and/or components within a sample. Here, we report on the use of hyperspectral imaging for endoscopic applications. Colorectal cancer is the 3rd leading cancer for incidences and deaths in the US. One factor of severity is the miss rate of precancerous/flat lesions ( 65% accuracy). Integrating HSI into colonoscopy procedures could minimize misdiagnosis and unnecessary resections. We have previously reported a working prototype light source with 16 high-powered light emitting diodes (LEDs) capable of high speed cycling and imaging. In recent testing, we have found our current prototype is limited by transmission loss ( 99%) through the multi-furcated solid light guide (lightpipe) and the desired framerate (20-30 fps) could not be achieved. Here, we report on a series of experimental and modeling studies to better optimize the lightpipe and the spectral endoscopy system as a whole. The lightpipe was experimentally evaluated using an integrating sphere and spectrometer (Ocean Optics). Modeling the lightpipe was performed using Monte Carlo optical ray tracing in TracePro (Lambda Research Corp.). Results of these optimization studies will aid in manufacturing a revised prototype with the newly designed light guide and increased sensitivity. Once the desired optical output (5-10 mW) is achieved then the HIS endoscope system will be able to be implemented without adding onto the procedure time.

  8. Detection of hypercholesterolemia using hyperspectral imaging of human skin

    Milanic, Matija; Bjorgan, Asgeir; Larsson, Marcus; Strömberg, Tomas; Randeberg, Lise L.


    Hypercholesterolemia is characterized by high blood levels of cholesterol and is associated with increased risk of atherosclerosis and cardiovascular disease. Xanthelasma is a subcutaneous lesion appearing in the skin around the eyes. Xanthelasma is related to hypercholesterolemia. Identifying micro-xanthelasma can thereforeprovide a mean for early detection of hypercholesterolemia and prevent onset and progress of disease. The goal of this study was to investigate spectral and spatial characteristics of hypercholesterolemia in facial skin. Optical techniques like hyperspectral imaging (HSI) might be a suitable tool for such characterization as it simultaneously provides high resolution spatial and spectral information. In this study a 3D Monte Carlo model of lipid inclusions in human skin was developed to create hyperspectral images in the spectral range 400-1090 nm. Four lesions with diameters 0.12-1.0 mm were simulated for three different skin types. The simulations were analyzed using three algorithms: the Tissue Indices (TI), the two layer Diffusion Approximation (DA), and the Minimum Noise Fraction transform (MNF). The simulated lesions were detected by all methods, but the best performance was obtained by the MNF algorithm. The results were verified using data from 11 volunteers with known cholesterol levels. The face of the volunteers was imaged by a LCTF system (400- 720 nm), and the images were analyzed using the previously mentioned algorithms. The identified features were then compared to the known cholesterol levels of the subjects. Significant correlation was obtained for the MNF algorithm only. This study demonstrates that HSI can be a promising, rapid modality for detection of hypercholesterolemia.

  9. A Functional Approach to Hyperspectral Image Analysis in the Cloud

    Wilson, A.; Lindholm, D. M.; Coddington, O.; Pilewskie, P.


    Hyperspectral image volumes are very large. A hyperspectral image analysis (HIA) may use 100TB of data, a huge barrier to their use. Hylatis is a new NASA project to create a toolset for HIA. Through web notebook and cloud technology, Hylatis will provide a more interactive experience for HIA by defining and implementing concepts and operations for HIA, identified and vetted by subject matter experts, and callable within a general purpose language, particularly Python. Hylatis leverages LaTiS, a data access framework developed at LASP. With an OPeNDAP compliant interface plus additional server side capabilities, the LaTiS API provides a uniform interface to virtually any data source, and has been applied to various storage systems, including: file systems, databases, remote servers, and in various domains including: space science, systems administration and stock quotes. In the LaTiS architecture, data `adapters' read data into a data model, where server-side computations occur. Data `writers' write data from the data model into the desired format. The Hylatis difference is the data model. In LaTiS, data are represented as mathematical functions of independent and dependent variables. Domain semantics are not present at this level, but are instead present in higher software layers. The benefit of a domain agnostic, mathematical representation is having the power of math, particularly functional algebra, unconstrained by domain semantics. This agnosticism supports reusable server side functionality applicable in any domain, such as statistical, filtering, or projection operations. Algorithms to aggregate or fuse data can be simpler because domain semantics are separated from the math. Hylatis will map the functional model onto the Spark relational interface, thereby adding a functional interface to that big data engine.This presentation will discuss Hylatis goals, strategies, and current state.

  10. Progressive sample processing of band selection for hyperspectral imagery

    Liu, Keng-Hao; Chien, Hung-Chang; Chen, Shih-Yu


    Band selection (BS) is one of the most important topics in hyperspectral image (HSI) processing. The objective of BS is to find a set of representative bands that can represent the whole image with lower inter-band redundancy. Many types of BS algorithms were proposed in the past. However, most of them can be carried on in an off-line manner. It means that they can only be implemented on the pre-collected data. Those off-line based methods are sometime useless for those applications that are timeliness, particular in disaster prevention and target detection. To tackle this issue, a new concept, called progressive sample processing (PSP), was proposed recently. The PSP is an "on-line" framework where the specific type of algorithm can process the currently collected data during the data transmission under band-interleavedby-sample/pixel (BIS/BIP) protocol. This paper proposes an online BS method that integrates a sparse-based BS into PSP framework, called PSP-BS. In PSP-BS, the BS can be carried out by updating BS result recursively pixel by pixel in the same way that a Kalman filter does for updating data information in a recursive fashion. The sparse regression is solved by orthogonal matching pursuit (OMP) algorithm, and the recursive equations of PSP-BS are derived by using matrix decomposition. The experiments conducted on a real hyperspectral image show that the PSP-BS can progressively output the BS status with very low computing time. The convergence of BS results during the transmission can be quickly achieved by using a rearranged pixel transmission sequence. This significant advantage allows BS to be implemented in a real time manner when the HSI data is transmitted pixel by pixel.

  11. Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging

    Chaudhari, Abhijit J; Darvas, Felix; Bading, James R; Moats, Rex A; Conti, Peter S; Smith, Desmond J; Cherry, Simon R; Leahy, Richard M


    For bioluminescence imaging studies in small animals, it is important to be able to accurately localize the three-dimensional (3D) distribution of the underlying bioluminescent source. The spectrum of light produced by the source that escapes the subject varies with the depth of the emission source because of the wavelength-dependence of the optical properties of tissue. Consequently, multispectral or hyperspectral data acquisition should help in the 3D localization of deep sources. In this paper, we describe a framework for fully 3D bioluminescence tomographic image acquisition and reconstruction that exploits spectral information. We describe regularized tomographic reconstruction techniques that use semi-infinite slab or FEM-based diffusion approximations of photon transport through turbid media. Singular value decomposition analysis was used for data dimensionality reduction and to illustrate the advantage of using hyperspectral rather than achromatic data. Simulation studies in an atlas-mouse geometry indicated that sub-millimeter resolution may be attainable given accurate knowledge of the optical properties of the animal. A fixed arrangement of mirrors and a single CCD camera were used for simultaneous acquisition of multispectral imaging data over most of the surface of the animal. Phantom studies conducted using this system demonstrated our ability to accurately localize deep point-like sources and show that a resolution of 1.5 to 2.2 mm for depths up to 6 mm can be achieved. We also include an in vivo study of a mouse with a brain tumour expressing firefly luciferase. Co-registration of the reconstructed 3D bioluminescent image with magnetic resonance images indicated good anatomical localization of the tumour

  12. High speed measurement of corn seed viability using hyperspectral imaging

    Ambrose, Ashabahebwa; Kandpal, Lalit Mohan; Kim, Moon S.; Lee, Wang-Hee; Cho, Byoung-Kwan


    Corn is one of the most cultivated crops all over world as food for humans as well as animals. Optimized agronomic practices and improved technological interventions during planting, harvesting and post-harvest handling are critical to improving the quantity and quality of corn production. Seed germination and vigor are the primary determinants of high yield notwithstanding any other factors that may play during the growth period. Seed viability may be lost during storage due to unfavorable conditions e.g. moisture content and temperatures, or physical damage during mechanical processing e.g. shelling, or over heating during drying. It is therefore vital for seed companies and farmers to test and ascertain seed viability to avoid losses of any kind. This study aimed at investigating the possibility of using hyperspectral imaging (HSI) technique to discriminate viable and nonviable corn seeds. A group of corn samples were heat treated by using microwave process while a group of seeds were kept as control group (untreated). The hyperspectral images of corn seeds of both groups were captured between 400 and 2500 nm wave range. Partial least squares discriminant analysis (PLS-DA) was built for the classification of aged (heat treated) and normal (untreated) corn seeds. The model showed highest classification accuracy of 97.6% (calibration) and 95.6% (prediction) in the SWIR region of the HSI. Furthermore, the PLS-DA and binary images were capable to provide the visual information of treated and untreated corn seeds. The overall results suggest that HSI technique is accurate for classification of viable and non-viable seeds with non-destructive manner.

  13. Detection of cracks on concrete surfaces by hyperspectral image processing

    Santos, Bruno O.; Valença, Jonatas; Júlio, Eduardo


    All large infrastructures worldwide must have a suitable monitoring and maintenance plan, aiming to evaluate their behaviour and predict timely interventions. In the particular case of concrete infrastructures, the detection and characterization of crack patterns is a major indicator of their structural response. In this scope, methods based on image processing have been applied and presented. Usually, methods focus on image binarization followed by applications of mathematical morphology to identify cracks on concrete surface. In most cases, publications are focused on restricted areas of concrete surfaces and in a single crack. On-site, the methods and algorithms have to deal with several factors that interfere with the results, namely dirt and biological colonization. Thus, the automation of a procedure for on-site characterization of crack patterns is of great interest. This advance may result in an effective tool to support maintenance strategies and interventions planning. This paper presents a research based on the analysis and processing of hyper-spectral images for detection and classification of cracks on concrete structures. The objective of the study is to evaluate the applicability of several wavelengths of the electromagnetic spectrum for classification of cracks in concrete surfaces. An image survey considering highly discretized wavelengths between 425 nm and 950 nm was performed on concrete specimens, with bandwidths of 25 nm. The concrete specimens were produced with a crack pattern induced by applying a load with displacement control. The tests were conducted to simulate usual on-site drawbacks. In this context, the surface of the specimen was subjected to biological colonization (leaves and moss). To evaluate the results and enhance crack patterns a clustering method, namely k-means algorithm, is being applied. The research conducted allows to define the suitability of using clustering k-means algorithm combined with hyper-spectral images highly

  14. Ningaloo Reef: Shallow Marine Habitats Mapped Using a Hyperspectral Sensor

    Kobryn, Halina T.; Wouters, Kristin; Beckley, Lynnath E.; Heege, Thomas


    Research, monitoring and management of large marine protected areas require detailed and up-to-date habitat maps. Ningaloo Marine Park (including the Muiron Islands) in north-western Australia (stretching across three degrees of latitude) was mapped to 20 m depth using HyMap airborne hyperspectral imagery (125 bands) at 3.5 m resolution across the 762 km2 of reef environment between the shoreline and reef slope. The imagery was corrected for atmospheric, air-water interface and water column influences to retrieve bottom reflectance and bathymetry using the physics-based Modular Inversion and Processing System. Using field-validated, image-derived spectra from a representative range of cover types, the classification combined a semi-automated, pixel-based approach with fuzzy logic and derivative techniques. Five thematic classification levels for benthic cover (with probability maps) were generated with varying degrees of detail, ranging from a basic one with three classes (biotic, abiotic and mixed) to the most detailed with 46 classes. The latter consisted of all abiotic and biotic seabed components and hard coral growth forms in dominant or mixed states. The overall accuracy of mapping for the most detailed maps was 70% for the highest classification level. Macro-algal communities formed most of the benthic cover, while hard and soft corals represented only about 7% of the mapped area (58.6 km2). Dense tabulate coral was the largest coral mosaic type (37% of all corals) and the rest of the corals were a mix of tabulate, digitate, massive and soft corals. Our results show that for this shallow, fringing reef environment situated in the arid tropics, hyperspectral remote sensing techniques can offer an efficient and cost-effective approach to mapping and monitoring reef habitats over large, remote and inaccessible areas. PMID:23922921

  15. Hyperspectral imaging using a color camera and its application for pathogen detection

    Yoon, Seung-Chul; Shin, Tae-Sung; Heitschmidt, Gerald W.; Lawrence, Kurt C.; Park, Bosoon; Gamble, Gary


    This paper reports the results of a feasibility study for the development of a hyperspectral image recovery (reconstruction) technique using a RGB color camera and regression analysis in order to detect and classify colonies of foodborne pathogens. The target bacterial pathogens were the six representative non-O157 Shiga-toxin producing Escherichia coli (STEC) serogroups (O26, O45, O103, O111, O121, and O145) grown in Petri dishes of Rainbow agar. The purpose of the feasibility study was to evaluate whether a DSLR camera (Nikon D700) could be used to predict hyperspectral images in the wavelength range from 400 to 1,000 nm and even to predict the types of pathogens using a hyperspectral STEC classification algorithm that was previously developed. Unlike many other studies using color charts with known and noise-free spectra for training reconstruction models, this work used hyperspectral and color images, separately measured by a hyperspectral imaging spectrometer and the DSLR color camera. The color images were calibrated (i.e. normalized) to relative reflectance, subsampled and spatially registered to match with counterpart pixels in hyperspectral images that were also calibrated to relative reflectance. Polynomial multivariate least-squares regression (PMLR) was previously developed with simulated color images. In this study, partial least squares regression (PLSR) was also evaluated as a spectral recovery technique to minimize multicollinearity and overfitting. The two spectral recovery models (PMLR and PLSR) and their parameters were evaluated by cross-validation. The QR decomposition was used to find a numerically more stable solution of the regression equation. The preliminary results showed that PLSR was more effective especially with higher order polynomial regressions than PMLR. The best classification accuracy measured with an independent test set was about 90%. The results suggest the potential of cost-effective color imaging using hyperspectral image

  16. A FPGA implementation for linearly unmixing a hyperspectral image using OpenCL

    Guerra, Raúl; López, Sebastián.; Sarmiento, Roberto


    Hyperspectral imaging systems provide images in which single pixels have information from across the electromagnetic spectrum of the scene under analysis. These systems divide the spectrum into many contiguos channels, which may be even out of the visible part of the spectra. The main advantage of the hyperspectral imaging technology is that certain objects leave unique fingerprints in the electromagnetic spectrum, known as spectral signatures, which allow to distinguish between different materials that may look like the same in a traditional RGB image. Accordingly, the most important hyperspectral imaging applications are related with distinguishing or identifying materials in a particular scene. In hyperspectral imaging applications under real-time constraints, the huge amount of information provided by the hyperspectral sensors has to be rapidly processed and analysed. For such purpose, parallel hardware devices, such as Field Programmable Gate Arrays (FPGAs) are typically used. However, developing hardware applications typically requires expertise in the specific targeted device, as well as in the tools and methodologies which can be used to perform the implementation of the desired algorithms in the specific device. In this scenario, the Open Computing Language (OpenCL) emerges as a very interesting solution in which a single high-level synthesis design language can be used to efficiently develop applications in multiple and different hardware devices. In this work, the Fast Algorithm for Linearly Unmixing Hyperspectral Images (FUN) has been implemented into a Bitware Stratix V Altera FPGA using OpenCL. The obtained results demonstrate the suitability of OpenCL as a viable design methodology for quickly creating efficient FPGAs designs for real-time hyperspectral imaging applications.

  17. A New Algorithm for the On-Board Compression of Hyperspectral Images

    Raúl Guerra


    Full Text Available Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth’s surface. In this situation, an efficient compression of the hyperspectral images is mandatory in order to save bandwidth and storage space. Lossless compression algorithms have been traditionally preferred, in order to preserve all the information present in the hyperspectral cube for scientific purposes, despite their limited compression ratio. Nevertheless, the increment in the data-rate of the new-generation sensors is making more critical the necessity of obtaining higher compression ratios, making it necessary to use lossy compression techniques. A new transform-based lossy compression algorithm, namely Lossy Compression Algorithm for Hyperspectral Image Systems (HyperLCA, is proposed in this manuscript. This compressor has been developed for achieving high compression ratios with a good compression performance at a reasonable computational burden. An extensive amount of experiments have been performed in order to evaluate the goodness of the proposed HyperLCA compressor using different calibrated and uncalibrated hyperspectral images from the AVIRIS and Hyperion sensors. The results provided by the proposed HyperLCA compressor have been evaluated and compared against those produced by the most relevant state-of-the-art compression solutions. The theoretical and experimental evidence indicates that the proposed algorithm represents an excellent option for lossy compressing hyperspectral images, especially for applications where the available computational resources are limited, such as on-board scenarios.

  18. Antenna for passive RFID tags

    Schiopu, Paul; Manea, Adrian; Cristea, Ionica; Grosu, Neculai; Vladescu, Marian; Craciun, Anca-Ileana; Craciun, Alexandru


    Minuscule devices, called RFID tags are attached to objects and persons and emit information which positioned readers may capture wirelessly. Many methods of identification have been used, but that of most common is to use a unique serial number for identification of person or object. RFID tags can be characterized as either active or passive [1,2]. Traditional passive tags are typically in "sleep" state until awakened by the reader's emitted field. In passive tags, the reader's field acts to charge the capacitor that powers the badge and this can be a combination of antenna and barcodes obtained with SAW( Surface Acoustic Wave) devices [1,2,3] . The antenna in an RFID tag is a conductive element that permits the tag to exchange data with the reader. The paper contribution are targeted to antenna for passive RFID tags. The electromagnetic field generated by the reader is somehow oriented by the reader antenna and power is induced in the tag only if the orientation of the tag antenna is appropriate. A tag placed orthogonal to the reader yield field will not be read. This is the reason that guided manufacturers to build circular polarized antenna capable of propagating a field that is alternatively polarized on all planes passing on the diffusion axis. Passive RFID tags are operated at the UHF frequencies of 868MHz (Europe) and 915MHz (USA) and at the microwave frequencies of 2,45 GHz and 5,8 GHz . Because the tags are small dimensions, in paper, we present the possibility to use circular polarization microstrip antenna with fractal edge [2].

  19. Surface Passivation in Empirical Tight Binding

    He, Yu; Tan, Yaohua; Jiang, Zhengping; Povolotskyi, Michael; Klimeck, Gerhard; Kubis, Tillmann


    Empirical Tight Binding (TB) methods are widely used in atomistic device simulations. Existing TB methods to passivate dangling bonds fall into two categories: 1) Method that explicitly includes passivation atoms is limited to passivation with atoms and small molecules only. 2) Method that implicitly incorporates passivation does not distinguish passivation atom types. This work introduces an implicit passivation method that is applicable to any passivation scenario with appropriate parameters. This method is applied to a Si quantum well and a Si ultra-thin body transistor oxidized with SiO2 in several oxidation configurations. Comparison with ab-initio results and experiments verifies the presented method. Oxidation configurations that severely hamper the transistor performance are identified. It is also shown that the commonly used implicit H atom passivation overestimates the transistor performance.

  20. Data Processing and First Products from the Hyperspectral Imager for the Coastal Ocean (HICO) on the International Space Station


    NRL Stennis Space Center (NRL-SSC) for further processing using the NRL SSC Automated Processing System (APS). APS was developed for processing...have not previously developed automated processing for 73 hyperspectral ocean color data. The hyperspectral processing branch includes several

  1. Non-destructive quality evaluation of pepper (Capsicum annuum L.) seeds using LED-induced hyperspectral reflectance imaging

    In this study, we develop a viability evaluation method for pepper (Capsicum annuum L.) seed based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400–700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumin...

  2. Passivation Of High-Temperature Superconductors

    Vasquez, Richard P.


    Surfaces of high-temperature superconductors passivated with native iodides, sulfides, or sulfates formed by chemical treatments after superconductors grown. Passivating compounds nearly insoluble in and unreactive with water and protect underlying superconductors from effects of moisture. Layers of cuprous iodide and of barium sulfate grown. Other candidate passivating surface films: iodides and sulfides of bismuth, strontium, and thallium. Other proposed techniques for formation of passivating layers include deposition and gas-phase reaction.

  3. Passive Scalar Evolution in Peripheral Region

    Lebedev, V. V.; Turitsyn, K. S.


    We consider evolution of a passive scalar (concentration of pollutants or temperature) in a chaotic (turbulent) flow. A universal asymptotic behavior of the passive scalar decay (homogenization) related to peripheral regions (near walls) is established. The passive scalar moments and its pair correlation function in the peripheral region are analyzed. A special case investigated in our paper is the passive scalar decay along a pipe.

  4. Two or three decades of passive directions

    Cook, J.


    This paper presents an overview of the direction of passive solar architecture. The topics of the paper include design temperatures for buildings, active vs passive, fuel vs philosophy, engineering vs architecture, the thermal scale: heating vs cooling, fuel subsidies, divergent practices, sustainability, lighting, health, the place of passive technology

  5. Active house concept versus passive House

    Zeiler, W.; Boxem, G.; Vehler, R.; Verhoeven, M.; Fremouw, M.


    The passive house concept is the present trend in energy efficient sustainable dwellings. Within the passive house concept every effort is made to minimize the energy use. Substantial savings can be achieved by passive energy systems, especially natural ventilation, summer shading and winter solar

  6. Innovative solutions in passive house details

    Mlecnik, E.; Hilderson, W.


    For the realization of the first passive house demonstration projects in Belgium, passive houses were requested by convinced clients, designed by architects with experience in low energy building, and built by contractors with a feeling for working in building teams. These first passive house

  7. A Lexical Approach to Passive in ESL.

    Marshall, Fred

    Dissatisfaction with the standard transformational grammar approach to teaching passive voice sentences gave rise to the method developed. It is based on the framework of a lexical-functional grammar, which claims that both active and passive sentences are base-generated, and that both active and passive verb forms occur in the lexicon. It would…

  8. Excitation-scanning hyperspectral imaging as a means to discriminate various tissues types

    Deal, Joshua; Favreau, Peter F.; Lopez, Carmen; Lall, Malvika; Weber, David S.; Rich, Thomas C.; Leavesley, Silas J.


    Little is currently known about the fluorescence excitation spectra of disparate tissues and how these spectra change with pathological state. Current imaging diagnostic techniques have limited capacity to investigate fluorescence excitation spectral characteristics. This study utilized excitation-scanning hyperspectral imaging to perform a comprehensive assessment of fluorescence spectral signatures of various tissues. Immediately following tissue harvest, a custom inverted microscope (TE-2000, Nikon Instruments) with Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) were used to acquire hyperspectral image data from each sample. Scans utilized excitation wavelengths from 340 nm to 550 nm in 5 nm increments. Hyperspectral images were analyzed with custom Matlab scripts including linear spectral unmixing (LSU), principal component analysis (PCA), and Gaussian mixture modeling (GMM). Spectra were examined for potential characteristic features such as consistent intensity peaks at specific wavelengths or intensity ratios among significant wavelengths. The resultant spectral features were conserved among tissues of similar molecular composition. Additionally, excitation spectra appear to be a mixture of pure endmembers with commonalities across tissues of varied molecular composition, potentially identifiable through GMM. These results suggest the presence of common autofluorescent molecules in most tissues and that excitationscanning hyperspectral imaging may serve as an approach for characterizing tissue composition as well as pathologic state. Future work will test the feasibility of excitation-scanning hyperspectral imaging as a contrast mode for discriminating normal and pathological tissues.

  9. [Progress in inversion of vegetation nitrogen concentration by hyperspectral remote sensing].

    Wang, Li-Wen; Wei, Ya-Xing


    Nitrogen is the necessary element in life activity of vegetation, which takes important function in biosynthesis of protein, nucleic acid, chlorophyll, and enzyme etc, and plays a key role in vegetation photosynthesis. The technology about inversion of vegetation nitrogen concentration by hyperspectral remote sensing has been the research hotspot since the 70s of last century. With the development of hyperspectral remote sensing technology in recent years, the advantage of spectral bands subdivision in a certain spectral region provides the powerful technology measure for correlative spectral characteristic research on vegetation nitrogen. In the present paper, combined with the newest research production about monitoring vegetation nitrogen concentration by hyperspectral remote sensing published in main geography science literature in recent several years, the principle and correlated problem about monitoring vegetation nitrogen concentration by hyperspectral remote sensing were introduced. From four aspects including vegetation nitrogen spectral index, vegetation nitrogen content inversion based on chlorophyll index, regression model, and eliminating influence factors to inversion of vegetation nitrogen concentration, main technology methods about inversion of vegetation nitrogen concentration by hyperspectral remote sensing were detailedly introduced. Correlative research conclusions were summarized and analyzed, and research development trend was discussed.

  10. Line-Scan Hyperspectral Imaging Techniques for Food Safety and Quality Applications

    Jianwei Qin


    Full Text Available Hyperspectral imaging technologies in the food and agricultural area have been evolving rapidly over the past 15 years owing to tremendous interest from both academic and industrial fields. Line-scan hyperspectral imaging is a major method that has been intensively researched and developed using different physical principles (e.g., reflectance, transmittance, fluorescence, Raman, and spatially resolved spectroscopy and wavelength regions (e.g., visible (VIS, near infrared (NIR, and short-wavelength infrared (SWIR. Line-scan hyperspectral imaging systems are mainly developed and used for surface inspection of food and agricultural products using area or line light sources. Some of these systems can also be configured to conduct spatially resolved spectroscopy measurements for internal or subsurface food inspection using point light sources. This paper reviews line-scan hyperspectral imaging techniques, with introduction, demonstration, and summarization of existing and emerging techniques for food and agricultural applications. The main topics include related spectroscopy techniques, line-scan measurement methods, hardware components and systems, system calibration methods, and spectral and image analysis techniques. Applications in food safety and quality are also presented to reveal current practices and future trends of line-scan hyperspectral imaging techniques.


    S. T. Seydi


    Full Text Available The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.

  12. Intraoperative brain hemodynamic response assessment with real-time hyperspectral optical imaging (Conference Presentation)

    Laurence, Audrey; Pichette, Julien; Angulo-Rodríguez, Leticia M.; Saint Pierre, Catherine; Lesage, Frédéric; Bouthillier, Alain; Nguyen, Dang Khoa; Leblond, Frédéric


    Following normal neuronal activity, there is an increase in cerebral blood flow and cerebral blood volume to provide oxygenated hemoglobin to active neurons. For abnormal activity such as epileptiform discharges, this hemodynamic response may be inadequate to meet the high metabolic demands. To verify this hypothesis, we developed a novel hyperspectral imaging system able to monitor real-time cortical hemodynamic changes during brain surgery. The imaging system is directly integrated into a surgical microscope, using the white-light source for illumination. A snapshot hyperspectral camera is used for detection (4x4 mosaic filter array detecting 16 wavelengths simultaneously). We present calibration experiments where phantoms made of intralipid and food dyes were imaged. Relative concentrations of three dyes were recovered at a video rate of 30 frames per second. We also present hyperspectral recordings during brain surgery of epileptic patients with concurrent electrocorticography recordings. Relative concentration maps of oxygenated and deoxygenated hemoglobin were extracted from the data, allowing real-time studies of hemodynamic changes with a good spatial resolution. Finally, we present preliminary results on phantoms obtained with an integrated spatial frequency domain imaging system to recover tissue optical properties. This additional module, used together with the hyperspectral imaging system, will allow quantification of hemoglobin concentrations maps. Our hyperspectral imaging system offers a new tool to analyze hemodynamic changes, especially in the case of epileptiform discharges. It also offers an opportunity to study brain connectivity by analyzing correlations between hemodynamic responses of different tissue regions.

  13. Platforms for hyperspectral imaging, in-situ optical and acoustical imaging in urbanized regions

    Bostater, Charles R.; Oney, Taylor


    Hyperspectral measurements of the water surface of urban coastal waters are presented. Oblique bidirectional reflectance factor imagery was acquired made in a turbid coastal sub estuary of the Indian River Lagoon, Florida and along coastal surf zone waters of the nearby Atlantic Ocean. Imagery was also collected using a pushbroom hyperspectral imager mounted on a fixed platform with a calibrated circular mechatronic rotation stage. Oblique imagery of the shoreline and subsurface features clearly shows subsurface bottom features and rip current features within the surf zone water column. In-situ hyperspectral optical signatures were acquired from a vessel as a function of depth to determine the attenuation spectrum in Palm Bay. A unique stationary platform methodology to acquire subsurface acoustic images showing the presence of moving bottom boundary nephelometric layers passing through the acoustic fan beam. The acoustic fan beam imagery indicated the presence of oscillatory subsurface waves in the urbanized coastal estuary. Hyperspectral imaging using the fixed platform techniques are being used to collect hyperspectral bidirectional reflectance factor (BRF) measurements from locations at buildings and bridges in order to provide new opportunities to advance our scientific understanding of aquatic environments in urbanized regions.

  14. Classification of Herbaceous Vegetation Using Airborne Hyperspectral Imagery

    Péter Burai


    Full Text Available Alkali landscapes hold an extremely fine-scale mosaic of several vegetation types, thus it seems challenging to separate these classes by remote sensing. Our aim was to test the applicability of different image classification methods of hyperspectral data in this complex situation. To reach the highest classification accuracy, we tested traditional image classifiers (maximum likelihood classifier—MLC, machine learning algorithms (support vector machine—SVM, random forest—RF and feature extraction (minimum noise fraction (MNF-transformation on training datasets of different sizes. Digital images were acquired from an AISA EAGLE II hyperspectral sensor of 128 contiguous bands (400–1000 nm, a spectral sampling of 5 nm bandwidth and a ground pixel size of 1 m. For the classification, we established twenty vegetation classes based on the dominant species, canopy height, and total vegetation cover. Image classification was applied to the original and MNF (minimum noise fraction transformed dataset with various training sample sizes between 10 and 30 pixels. In order to select the optimal number of the transformed features, we applied SVM, RF and MLC classification to 2–15 MNF transformed bands. In the case of the original bands, SVM and RF classifiers provided high accuracy irrespective of the number of the training pixels. We found that SVM and RF produced the best accuracy when using the first nine MNF transformed bands; involving further features did not increase classification accuracy. SVM and RF provided high accuracies with the transformed bands, especially in the case of the aggregated groups. Even MLC provided high accuracy with 30 training pixels (80.78%, but the use of a smaller training dataset (10 training pixels significantly reduced the accuracy of classification (52.56%. Our results suggest that in alkali landscapes, the application of SVM is a feasible solution, as it provided the highest accuracies compared to RF and MLC

  15. Traffic classification with passive measurement

    Pham, Hoang Phong


    Abstract This is a master thesis from a collaboration between Oslo University College and Uninett Research. Uninett have a passive monitoring device on a 2.5 Gbps backbone link between Trondheim and Narvik. They uses measurement with optical splitters and specialized measuring interfaces to trace traffic with Gigabit speed. We would like to investigate the structure and patterns in these data. It is of special interest to classify the traffic belonging to different services and protocols. ...

  16. EP1000 passive plant description

    Saiu, G.


    In 1994, a group of European Utilities, together with Westinghouse and its Industrial Partner GENESI (an Italian consortium including ANSALDO and FIAT), initiated a program designated EPP (European Passive Plant) to evaluate Westinghouse Passive Nuclear Plant Technology for application in Europe. In Phase I of the European Passive Plant Program which was completed in 1996, a 1000 MWe passive plant reference design (EP1000) was established which conforms to the European Utility Requirements (EUR) and is expected to meet the European Safety Authorities requirements. Phase 2 of the program was initiated in 1997 with the objective of developing the Nuclear Island design details and performing supporting analyses to start development of Safety Case Report (SCR) for submittal to European Licensing Authorities. The first part of Phase 2, 'Design Definition' phase (Phase 2A) will be completed at the end of 1998, the main efforts being design definition of key systems and structures, development of the Nuclear Island layout, and performing preliminary safety analyses to support design efforts. The second part, 'Phase 2B', includes both the analyses and evaluations required to demonstrate the adequacy of the design, and to support the preparation of Safety Case Report. The second part of Phase 2 of the program will start at the beginning of 1999 and will be completed in the 2001. Incorporation of the EUR has been a key design requirement for the EP1000 from the beginning of the program. Detailed design solutions to meet the EUR have been defined and the safety approach has also been developed based on the EUR guidelines. This paper integrates and updates the plant description reported in the IAEA TECDOC-968. The most significant developments of the EP1000 plant design during Phase 2A of the EPP program are described and reference is made to the key design requirements set by the EUR Rev. B document. (author)

  17. Active and Passive Hybrid Sensor

    Carswell, James R.


    A hybrid ocean wind sensor (HOWS) can map ocean vector wind in low to hurricane-level winds, and non-precipitating and precipitating conditions. It can acquire active and passive measurements through a single aperture at two wavelengths, two polarizations, and multiple incidence angles. Its low profile, compact geometry, and low power consumption permits installation on air craft platforms, including high-altitude unmanned aerial vehicles (UAVs).

  18. Alternative to Nitric Acid Passivation

    Kessel, Kurt R.


    Corrosion is an extensive problem that affects the National Aeronautics and Space Administration (NASA) and European Space Agency (ESA). The deleterious effects of corrosion result in steep costs, asset downtime affecting mission readiness, and safety risks to personnel. It is vital to reduce corrosion costs and risks in a sustainable manner. The primary objective of this effort is to qualify citric acid as an environmentally-preferable alternative to nitric acid for passivation of stainless steel alloys.

  19. Interior design for passive solar homes

    Breen, J. C.


    The increasing emphasis on refinement of passive solar systems has brought recognition to interior design as an integral part of passive solar architecture. Interior design can be used as a finetuning tool minimizing many of the problems associated with passive solar energy use in residential buildings. In addition, treatment of interior space in solar model homes may be a prime factor in determining sales success. A new style of interior design is evolving in response to changes in building form incorporating passive solar design features. The psychology behind passive solar architecture is reflected in interiors, and selection of interior components increasingly depends on the functional suitability of various interior elements.

  20. Interior design for passive solar homes

    Breen, J. C.


    The increasing emphasis on refinement of passive solar systems brought recognition to interior design as an integral part of passive solar architecture. Interior design can be used as a finetuning tool minimizing many of the problems associated with passive solar energy use in residential buildings. In addition, treatment of interior space in solar model homes may be a prime factor in determining sales success. A new style of interior design is evolving in response to changes in building from incorporating passive solar design features. The psychology behind passive solar architecture is reflected in interiors, and selection of interior components increasingly depends on the functional suitably of various interior elements.

  1. Degradation of materials and passivity

    Meisel, W.


    Demanding for a reduction in materials degradation is a serious problem all over the world. Moessbauer spectroscopy (MS) is, among others, a very valuable tool to follow many degradation processes. Evidently, Fe is the most important Moessbauer element considering the overall presence of iron in everyday life. MS may contribute to our knowledge about nearly all fields of materials degradation, chemical, mechanical, thermal, irradiative, etc. Following some general lines, corrosion is considered in particular. MS is applicable to investigate the bulk of materials as well as their surface layers with an information depth of ca. 250 nm. In general, it has to be applied as a surface sensitive method in combination with other relevant methods in order to get a detailed insight into ongoing processes. Some examples have been selected to elucidate the application of MS in this field. Another class of examples concerns attempts to prevent corrosion, i.e., the application of coatings and transforming chemicals. A very effective and most natural way to reduce corrosion is the passivation of materials. The effect of passive layers and their destruction by environmental influences are discussed using results of MS and related methods. It is outlined that passivity is not restricted to chemically treated metals but can be considered as a general concept for preventing different kinds of materials from degradation. (orig.)

  2. Passive infrared motion sensing technology

    Doctor, A.P.


    In the last 10 years passive IR based (8--12 microns) motion sensing has matured to become the dominant method of volumetric space protection and surveillance. These systems currently cost less than $25 to produce and yet use traditionally expensive IR optics, filters, sensors and electronic circuitry. This IR application is quite interesting in that the volumes of systems produced and the costs and performance level required prove that there is potential for large scale commercial applications of IR technology. This paper will develop the basis and principles of operation of a staring motion sensor system using a technical approach. A model for the motion of the target is developed and compared to the background. The IR power difference between the target and the background as well as the optical requirements are determined from basic principles and used to determine the performance of the system. Low cost reflective and refractive IR optics and bandpass IR filters are discussed. The pyroelectric IR detector commonly used is fully discussed and characterized. Various schemes for ''false alarms'' have been developed and are also explained. This technology is also used in passive IR based motion sensors for other applications such as lighting control. These applications are also discussed. In addition the paper will discuss new developments in IR surveillance technology such as the use of linear motion sensing arrays. This presentation can be considered a ''primer'' on the art of Passive IR Motion Sensing as applied to Surveillance Technology

  3. Mineral mapping in the western Kunlun Mountains using Tiangong-1 hyperspectral imagery

    Ge, W.; Cheng, Q.; Jing, L.; Chen, Y.; Guo, X.; Ding, H.; Liu, Q.


    The unmanned Chinese space module Tiangong-1 was launched in September 2011 with a hyperspectral sensor on board. The sensor combines high spatial and spectral resolution suitable for mineral mapping. In this study, Tiangong-1 hyperspectral data were employed for mineral mapping in the western Kunlun Mountains, an important metallogenic belt in China. A Spectral Hourglass Wizard method was applied to detect common minerals from the Tiangong- 1 shortwave infrared data with reference to a set of spectral libraries. Spectral information on minerals, such as zoisite, mica, quartz, sodalite, dolomite, and actinolite, was extracted from the data. The resulting mineral interpretation maps were highly correlated with the reference geological maps and information from ASTER satellite imagery, suggesting that the hyperspectral data are suitable for mineral mapping.

  4. Locality-preserving sparse representation-based classification in hyperspectral imagery

    Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting


    This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

  5. Hyperspectral Imaging and SPA-LDA Quantitative Analysis for Detection of Colon Cancer Tissue

    Yuan, X.; Zhang, D.; Wang, Ch.; Dai, B.; Zhao, M.; Li, B.


    Hyperspectral imaging (HSI) has been demonstrated to provide a rapid, precise, and noninvasive method for cancer detection. However, because HSI contains many data, quantitative analysis is often necessary to distill information useful for distinguishing cancerous from normal tissue. To demonstrate that HSI with our proposed algorithm can make this distinction, we built a Vis-NIR HSI setup and made many spectral images of colon tissues, and then used a successive projection algorithm (SPA) to analyze the hyperspectral image data of the tissues. This was used to build an identification model based on linear discrimination analysis (LDA) using the relative reflectance values of the effective wavelengths. Other tissues were used as a prediction set to verify the reliability of the identification model. The results suggest that Vis-NIR hyperspectral images, together with the spectroscopic classification method, provide a new approach for reliable and safe diagnosis of colon cancer and could lead to advances in cancer diagnosis generally.

  6. Classification in hyperspectral images by independent component analysis, segmented cross-validation and uncertainty estimates

    Beatriz Galindo-Prieto


    Full Text Available Independent component analysis combined with various strategies for cross-validation, uncertainty estimates by jack-knifing and critical Hotelling’s T2 limits estimation, proposed in this paper, is used for classification purposes in hyperspectral images. To the best of our knowledge, the combined approach of methods used in this paper has not been previously applied to hyperspectral imaging analysis for interpretation and classification in the literature. The data analysis performed here aims to distinguish between four different types of plastics, some of them containing brominated flame retardants, from their near infrared hyperspectral images. The results showed that the method approach used here can be successfully used for unsupervised classification. A comparison of validation approaches, especially leave-one-out cross-validation and regions of interest scheme validation is also evaluated.

  7. Microscopic hyperspectral imaging studies of normal and diabetic retina of rats


    A microscopic hyperspectral imager was developed based on the microscopic technology and the spectral imaging technology. Some microscopic hyperspectral images of retina sections of the normal, the diabetic, and the treated rats were collected by the new imager. Single-band images and pseudo-color images of each group were obtained and the typical transmittance spectrums were ex-tracted. The results showed that the transmittance of outer nuclear layer cells of the diabetic group was generally higher than that of the normal. A small absorption peak appeared near the 180th band in the spectrum of the diabetic group and this peak weakened or disappeared in the spectrum of the treated group. Our findings indicate that the microscopic hyperspectral images include wealthy information of retina sections which is helpful for the ophthalmologist to reveal the pathogenesis of diabetic reti-nopathy and explore the therapeutic effect of drugs.




    Full Text Available We developed a biosensor that is capable for simultaneous surface plasmon resonance (SPR sensing and hyperspectral fluorescence analysis in this paper. A symmetrical metal-dielectric slab scheme is employed for the excitation of coupled plasmon waveguide resonance (CPWR in the present work. Resonance between surface plasmon mode and the guided waveguide mode generates narrower full width half-maximum of the reflective curves which leads to increased precision for the determination of refractive index over conventional SPR sensors. In addition, CPWR also offers longer surface propagation depths and higher surface electric field strengths that enable the excitation of fluorescence with hyperspectral technique to maintain an appreciable signal-to-noise ratio. The refractive index information obtained from SPR sensing and the chemical properties obtained through hyperspectral fluorescence analysis confirm each other to exclude false-positive or false-negative cases. The sensor provides a comprehensive understanding of the biological events on the sensor chips.


    A. Kianisarkaleh


    Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

  10. Bobcat 2013: a hyperspectral data collection supporting the development and evaluation of spatial-spectral algorithms

    Kaufman, Jason; Celenk, Mehmet; White, A. K.; Stocker, Alan D.


    The amount of hyperspectral imagery (HSI) data currently available is relatively small compared to other imaging modalities, and what is suitable for developing, testing, and evaluating spatial-spectral algorithms is virtually nonexistent. In this work, a significant amount of coincident airborne hyperspectral and high spatial resolution panchromatic imagery that supports the advancement of spatial-spectral feature extraction algorithms was collected to address this need. The imagery was collected in April 2013 for Ohio University by the Civil Air Patrol, with their Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor. The target materials, shapes, and movements throughout the collection area were chosen such that evaluation of change detection algorithms, atmospheric compensation techniques, image fusion methods, and material detection and identification algorithms is possible. This paper describes the collection plan, data acquisition, and initial analysis of the collected imagery.

  11. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    YANG Zhaoxia


    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  12. Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

    Yongjian Nian


    Full Text Available A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.

  13. The passive of reflexive verbs in Icelandic

    Hlíf Árnadóttir


    Full Text Available The Reflexive Passive in Icelandic is reminiscent of the so-called New Passive (or New Impersonal in that the oblique case of a passivized object NP is preserved. As is shown by recent surveys, however, speakers who accept the Reflexive Passive do not necessarily accept the New Passive, whereas conversely, speakers who accept the New Passive do also accept the Reflexive Passive. Based on these results we suggest that there is a hierarchy in the acceptance of passive sentences in Icelandic, termed the Passive Acceptability Hierarchy. The validity of this hierarchy is confirmed by our diachronic corpus study of open access digital library texts from Icelandic journals and newspapers dating from the 19th and 20th centuries (tí Finally, we sketch an analysis of the Reflexive Passive, proposing that the different acceptability rates of the Reflexive and New Passives lie in the argument status of the object. Simplex reflexive pronouns are semantically dependent on the verbs which select them, and should therefore be analyzed as syntactic arguments only, and not as semantic arguments of these verbs.

  14. Detection of mechanical injury on pickling cucumbers using near-infrared hyperspectral imaging

    Ariana, D.; Lu, R.; Guyer, D.


    Automated detection of defects on freshly harvested pickling cucumbers will help the pickle industry provide higher quality pickle products and reduce potential economic losses. Research was conducted on using a hyperspectral imaging system for detecting defects on pickling cucumbers caused by mechanical stress. A near-infrared hyperspectral imaging system was used to capture both spatial and spectral information from cucumbers in the spectral region of 900 - 1700 nm. The system consisted of an imaging spectrograph attached to an InGaAs camera with line-light fiber bundles as an illumination source. Cucumber samples were subjected to two forms of mechanical loading, dropping and rolling, to simulate stress caused by mechanical harvesting. Hyperspectral images were acquired from the cucumbers over time periods of 0, 1, 2, 3, and 6 days after mechanical stress. Hyperspectral image processing methods, including principal component analysis and wavelength selection, were developed to separate normal and mechanically injured cucumbers. Results showed that reflectance from normal or non-bruised cucumbers was consistently higher than that from bruised cucumbers. The spectral region between 950 and 1350 nm was found to be most effective for bruise detection. The hyperspectral imaging system detected all mechanically injured cucumbers immediately after they were bruised. The overall detection accuracy was 97% within two hours of bruising and it was lower as time progressed. Lower detection accuracies for the prolonged times after bruising were attributed to the self- healing of the bruised tissue after mechanical injury. This research demonstrated that hyperspectral imaging is useful for detecting mechanical injury on pickling cucumbers.

  15. Lightweight Hyperspectral Mapping System and a Novel Photogrammetric Processing Chain for UAV-based Sensing

    Suomalainen, Juha; Franke, Jappe; Anders, Niels; Iqbal, Shahzad; Wenting, Philip; Becker, Rolf; Kooistra, Lammert


    We have developed a lightweight Hyperspectral Mapping System (HYMSY) and a novel processing chain for UAV based mapping. The HYMSY consists of a custom pushbroom spectrometer (range 450-950nm, FWHM 9nm, ~20 lines/s, 328 pixels/line), a consumer camera (collecting 16MPix raw image every 2 seconds), a GPS-Inertia Navigation System (GPS-INS), and synchronization and data storage units. The weight of the system at take-off is 2.0kg allowing us to mount it on a relatively small octocopter. The novel processing chain exploits photogrammetry in the georectification process of the hyperspectral data. At first stage the photos are processed in a photogrammetric software producing a high-resolution RGB orthomosaic, a Digital Surface Model (DSM), and photogrammetric UAV/camera position and attitude at the moment of each photo. These photogrammetric camera positions are then used to enhance the internal accuracy of GPS-INS data. These enhanced GPS-INS data are then used to project the hyperspectral data over the photogrammetric DSM, producing a georectified end product. The presented photogrammetric processing chain allows fully automated georectification of hyperspectral data using a compact GPS-INS unit while still producingin UAV use higher georeferencing accuracy than would be possible using the traditional processing method. During 2013, we have operated HYMSY on 150+ octocopter flights at 60+ sites or days. On typical flight we have produced for a 2-10ha area: a RGB orthoimagemosaic at 1-5cm resolution, a DSM in 5-10cm resolution, and hyperspectral datacube at 10-50cm resolution. The targets have mostly consisted of vegetated targets including potatoes, wheat, sugar beets, onions, tulips, coral reefs, and heathlands,. In this poster we present the Hyperspectral Mapping System and the photogrammetric processing chain with some of our first mapping results.


    S. J. Buckley


    Full Text Available Close range hyperspectral imaging is a developing method for the analysis and identification of material composition in many applications, such as in within the earth sciences. Using compact imaging devices in the field allows near-vertical topography to be imaged, thus bypassing the key limitations of viewing angle and resolution that preclude the use of airborne and spaceborne platforms. Terrestrial laser scanning allows 3D topography to be captured with high precision and spatial resolution. The combination of 3D geometry from laser scanning, and material properties from hyperspectral imaging allows new fusion products to be created, adding new information for solving application problems. This paper highlights the advantages of terrestrial lidar and hyperspectral integration, focussing on the qualitative and quantitative aspects, with examples from a geological field application. Accurate co-registration of the two data types is required. This allows 2D pixels to be linked to the 3D lidar geometry, giving increased quantitative analysis as classified material vectors are projected to 3D space for calculation of areas and examination of spatial relationships. User interpretation of hyperspectral results in a spatially-meaningful manner is facilitated using visual methods that combine the geometric and mineralogical products in a 3D environment. Point cloud classification and the use of photorealistic modelling enhance qualitative validation and interpretation, and allow image registration accuracy to be checked. A method for texture mapping of lidar meshes with multiple image textures, both conventional digital photos and hyperspectral results, is described. The integration of terrestrial laser scanning and hyperspectral imaging is a valuable means of providing new analysis methods, suitable for many applications requiring linked geometric and chemical information.


    P. Walczykowski


    Full Text Available The purpose of the presented research was to establish a methodology that would allow the registration of hyperspectral images with a defined spatial resolution on a horizontal plane. The results obtained within this research could then be used to establish the optimum sensor and flight parameters for collecting aerial imagery data using an UAV or other aerial system. The methodology is based on an user-selected optimal camera exposure parameters (i.e. time, gain value and flight parameters (i.e. altitude, velocity. A push-broom hyperspectral imager- the Headwall MicroHyperspec A-series VNIR was used to conduct this research. The measurement station consisted of the following equipment: a hyperspectral camera MicroHyperspec A-series VNIR, a personal computer with HyperSpec III software, a slider system which guaranteed the stable motion of the sensor system, a white reference panel and a Siemens star, which was used to evaluate the spatial resolution. Hyperspectral images were recorded at different distances between the sensor and the target- from 5m to 100m. During the registration process of each acquired image, many exposure parameters were changed, such as: the aperture value, exposure time and speed of the camera’s movement on the slider. Based on all of the registered hyperspectral images, some dependencies between chosen parameters had been developed: - the Ground Sampling Distance – GSD and the distance between the sensor and the target, - the speed of the camera and the distance between the sensor and the target, - the exposure time and the gain value, - the Density Number and the gain value. The developed methodology allowed us to determine the speed and the altitude of an unmanned aerial vehicle on which the sensor would be mounted, ensuring that the registered hyperspectral images have the required spatial resolution.

  18. Investigation of grapevine photosynthesis using hyperspectral techniques and development of hyperspectral band ratio indices sensitive to photosynthesis.

    Ozelkan, Emre; Karaman, Muhittin; Candar, Serkan; Coskun, Zafer; Ormeci, Cankut


    The photosynthetic rate of 9 different grapevines were analyzed with simultaneous photosynthesis and spectroradiometric measurements on 08.08.2012 (veraison) and 06.09.2012 (harvest). The wavelengths and spectral regions, which most properly express photosynthetic rate, were determined using correlation and regression analysis. In addition, hyperspectral band ratio (BR) indices sensitive to photosynthesis were developed using optimum band ratio (OBRA) method. The relation of BR results with photosynthesis values are presented with the correlation matrix maps created in this study. The examinations were performed for both specific dates (i.e., veraison and harvest) and also in aggregate (i.e., correlation between total spectra and photosynthesis data). For specific dates wavelength based analysis, the photosynthesis were best determined with -0.929 correlation coefficient (r) 609 nm of yellow region at veraison stage, and -0.870 at 641 nm of red region at harvest stage. For wavelength based aggregate analysis, 640 nm of red region was found to be correlated with 0.921 and -0.867 r values respectively and red edge (RE) (695 nm) was found to be correlated with -0.922 and -0.860 r values, respectively. When BR indices results were analyzed with photosynthetic values for specific dates, -0.987 r with R8../R, at veraison stage and -0.911 r with R696/R944 at harvest stage were found most correlated. For aggregate analysis of BR, common BR presenting great correlation with photosynthesis for both measurements was found to be R632/R971 with -0.974, -0.881 r values, respectively and other R610/R760 with -0.976, -0.879 r values. The final results of this study indicate that the proportion of RE region to a region with direct or indirect correlation with photosynthetic provides information about rate of photosynthesis. With the indices created in this study, the photosynthesis rate of vineyards can be determined using in-situ hyperspectral remote sensing. The findings of this

  19. Implementation of webcam-based hyperspectral imaging system

    Balooch, Ali; Nazeri, Majid; Abbasi, Hamed


    In the present work, a hyperspectral imaging system (imaging spectrometer) using a commercial webcam has been designed and developed. This system was able to capture two-dimensional spectra (in emission, transmission and reflection modes) directly from the scene in the desired wavelengths. Imaging of the object is done directly by linear sweep (pushbroom method). To do so, the spectrometer is equipped with a suitable collecting lens and a linear travel stage. A 1920 x 1080 pixel CMOS webcam was used as a detector. The spectrometer has been calibrated by the reference spectral lines of standard lamps. The spectral resolution of this system was about 2nm and its spatial resolution was about 1 mm for a 10 cm long object. The hardware solution is based on data acquisition working on the USB platform and controlled by a LabVIEW program. In this system, the initial output was a three-dimensional matrix in which two dimensions of the matrix were related to the spatial information of the object and the third dimension was the spectrum of any point of the object. Finally, the images in different wavelengths were created by reforming the data of the matrix. The free spectral range (FSR) of the system was 400 to 1100 nm. The system was successfully tested for some applications, such as plasma diagnosis as well as applications in food and agriculture sciences.

  20. Coastal Seabed Mapping with Hyperspectral and Lidar data

    Taramelli, A.; Valentini, E.; Filipponi, F.; Cappucci, S.


    A synoptic view of the coastal seascape and its dynamics needs a quantitative ability to dissect different components over the complexity of the seafloor where a mixture of geo - biological facies determines geomorphological features and their coverage. The present study uses an analytical approach that takes advantage of a multidimensional model to integrate different data sources from airborne Hyperspectral and LiDAR remote sensing and in situ measurements to detect antropogenic features and ecological `tipping points' in coastal seafloors. The proposed approach has the ability to generate coastal seabed maps using: 1) a multidimensional dataset to account for radiometric and morphological properties of waters and the seafloor; 2) a field spectral library to assimilate the high environmental variability into the multidimensional model; 3) a final classification scheme to represent the spatial gradients in the seafloor. The spatial pattern of the response to anthropogenic forcing may be indistinguishable from patterns of natural variability. It is argued that this novel approach to define tipping points following anthropogenic impacts could be most valuable in the management of natural resources and the economic development of coastal areas worldwide. Examples are reported from different sites of the Mediterranean Sea, both from Marine Protected and un-Protected Areas.


    M. Gu


    Full Text Available There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  2. Distributed Source Coding Techniques for Lossless Compression of Hyperspectral Images

    Barni Mauro


    Full Text Available This paper deals with the application of distributed source coding (DSC theory to remote sensing image compression. Although DSC exhibits a significant potential in many application fields, up till now the results obtained on real signals fall short of the theoretical bounds, and often impose additional system-level constraints. The objective of this paper is to assess the potential of DSC for lossless image compression carried out onboard a remote platform. We first provide a brief overview of DSC of correlated information sources. We then focus on onboard lossless image compression, and apply DSC techniques in order to reduce the complexity of the onboard encoder, at the expense of the decoder's, by exploiting the correlation of different bands of a hyperspectral dataset. Specifically, we propose two different compression schemes, one based on powerful binary error-correcting codes employed as source codes, and one based on simpler multilevel coset codes. The performance of both schemes is evaluated on a few AVIRIS scenes, and is compared with other state-of-the-art 2D and 3D coders. Both schemes turn out to achieve competitive compression performance, and one of them also has reduced complexity. Based on these results, we highlight the main issues that are still to be solved to further improve the performance of DSC-based remote sensing systems.

  3. Hyperspectral imaging of colonic polyps in vivo (Conference Presentation)

    Clancy, Neil T.; Elson, Daniel S.; Teare, Julian


    Standard endoscopic tools restrict clinicians to making subjective visual assessments of lesions detected in the bowel, with classification results depending strongly on experience level and training. Histological examination of resected tissue remains the diagnostic gold standard, meaning that all detected lesions are routinely removed. This subjects the patient to risk of polypectomy-related injury, and places significant workload and economic burdens on the hospital. An objective endoscopic classification method would allow hyperplastic polyps, with no malignant potential, to be left in situ, or low grade adenomas to be resected and discarded without histology. A miniature multimodal flexible endoscope is proposed to obtain hyperspectral reflectance and dual excitation autofluorescence information from polyps in vivo. This is placed inside the working channel of a conventional colonoscope, with the external scanning and detection optics on a bedside trolley. A blue and violet laser diode pair excite endogenous fluorophores in the respiration chain, while the colonoscope's xenon light source provides broadband white light for diffuse reflectance measurements. A push-broom HSI scanner collects the hypercube. System characterisation experiments are presented, defining resolution limits as well as acquisition settings for optimal spectral, spatial and temporal performance. The first in vivo results in human subjects are presented, demonstrating the clinical utility of the device. The optical properties (reflectance and autofluorescence) of imaged polyps are quantified and compared to the histologically-confirmed tissue type as well as the clinician's visual assessment. Further clinical studies will allow construction of a full robust training dataset for development of classification schemes.

  4. Subspace Learning via Local Probability Distribution for Hyperspectral Image Classification

    Huiwu Luo


    Full Text Available The computational procedure of hyperspectral image (HSI is extremely complex, not only due to the high dimensional information, but also due to the highly correlated data structure. The need of effective processing and analyzing of HSI has met many difficulties. It has been evidenced that dimensionality reduction has been found to be a powerful tool for high dimensional data analysis. Local Fisher’s liner discriminant analysis (LFDA is an effective method to treat HSI processing. In this paper, a novel approach, called PD-LFDA, is proposed to overcome the weakness of LFDA. PD-LFDA emphasizes the probability distribution (PD in LFDA, where the maximum distance is replaced with local variance for the construction of weight matrix and the class prior probability is applied to compute the affinity matrix. The proposed approach increases the discriminant ability of the transformed features in low dimensional space. Experimental results on Indian Pines 1992 data indicate that the proposed approach significantly outperforms the traditional alternatives.

  5. Hyperspectral imaging and ankle: brachial indices in peripheral arterial disease.

    Jafari-Saraf, Lida; Gordon, Ian L


    To evaluate the correlation between ankle:brachial indices (ABI) and visible light reflectance spectroscopy hyperspectral imaging (HSI) determinations of oxygenated and deoxygenated hemoglobin (oxyHgb and deoxyHgb) levels in the skin of the distal lower extremity. This is a prospective, open, comparator trial which took place at the Vascular laboratory of a Veterans Administration Hospital in Long Beach, USA. Fifty-eight patients (85 limbs) were referred for routine vascular laboratory studies including ABI had concomitant HSI. Limbs with noncompressible pedal signals were excluded from the analysis. ABI was determined with continuous wave Doppler ultrasound and leg blood pressure cuffs. A commercial HSI system (Oxu-Vu(R), Hypermed, Inc.) was used to measure oxyHgb, deoxyHgb, and percent oxygenated hemoglobin (%oxyHgb) in the dorsum of the foot and ankle. HSI measurements of volar forearm skin were also obtained to normalize the lower extremity HSI measurements in a manner comparable with ABI. For purposes of comparison, data sets were divided into 3 groups: ABI > 0.9 (n = 53), 0.45 failed to show a clinically useful correlation between HSI measurements of oxyHgb levels, further evaluation of this novel technology is warranted. Published by Elsevier Inc.


    B. Rasaiah


    Full Text Available Field spectroscopic metadata is a central component in the quality assurance, reliability, and discoverability of hyperspectral data and the products derived from it. Cataloguing, mining, and interoperability of these datasets rely upon the robustness of metadata protocols for field spectroscopy, and on the software architecture to support the exchange of these datasets. Currently no standard for in situ spectroscopy data or metadata protocols exist. This inhibits the effective sharing of growing volumes of in situ spectroscopy datasets, to exploit the benefits of integrating with the evolving range of data sharing platforms. A core metadataset for field spectroscopy was introduced by Rasaiah et al., (2011-2015 with extended support for specific applications. This paper presents a prototype model for an OGC and ISO compliant platform-independent metadata discovery service aligned to the specific requirements of field spectroscopy. In this study, a proof-of-concept metadata catalogue has been described and deployed in a cloud-based architecture as a demonstration of an operationalized field spectroscopy metadata standard and web-based discovery service.

  7. Can porosity affect the hyperspectral signature of sandy landscapes?

    Baranoski, Gladimir V. G.; Kimmel, Bradley W.


    Porosity is a fundamental property of sand deposits found in a wide range of landscapes, from beaches to dune fields. As a primary determinant of the density and permeability of sediments, it represents a central element in geophysical studies involving basin modeling and coastal erosion as well as geoaccoustics and geochemical investigations aiming at the understanding of sediment transport and water diffusion properties of sandy landscapes. These applications highlight the importance of obtaining reliable porosity estimations, which remains an elusive task, notably through remote sensing. In this work, we aim to contribute to the strengthening of the knowledge basis required for the development of new technologies for the remote monitoring of environmentally-triggered changes in sandy landscapes. Accordingly, we employ an in silico investigation approach to assess the effects of porosity variations on the reflectance of sandy landscapes in the visible and near-infrared spectral domains. More specifically, we perform predictive computer simulations using SPLITS, a hyperspectral light transport model for particulate materials that takes into account actual sand characterization data. To the best of our knowledge, this work represents the first comprehensive investigation relating porosity to the reflectance responses of sandy landscapes. Our findings indicate that the putative dependence of these responses on porosity may be considerably less pronounced than its dependence on other properties such as grain size and shape. Hence, future initiatives for the remote quantification of porosity will likely require reflectance sensors with a high degree of sensitivity.

  8. Hyperspectral Sensors Final Report CRADA No. TC02173.0

    Priest, R. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sauvageau, J. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)


    This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Science Applications International Corporation (SAIC), National Security Space Operations/SRBU, to develop longwave infrared (LWIR) hyperspectral imaging (HSI) sensors for airborne and potentially ground and space, platforms. LLNL has designed and developed LWIR HSI sensors since 1995. The current generation of these sensors has applications to users within the U.S. Department of Defense and the Intelligence Community. User needs are for multiple copies provided by commercial industry. To gain the most benefit from the U.S. Government’s prior investments in LWIR HSI sensors developed at LLNL, transfer of technology and know-how from LLNL HSI experts to commercial industry was needed. The overarching purpose of the CRADA project was to facilitate the transfer of the necessary technology from LLNL to SAIC thereby allowing the U.S. Government to procure LWIR HSI sensors from this company.

  9. Rapid prototyping of biomimetic vascular phantoms for hyperspectral reflectance imaging

    Ghassemi, Pejhman; Wang, Jianting; Melchiorri, Anthony J.; Ramella-Roman, Jessica C.; Mathews, Scott A.; Coburn, James C.; Sorg, Brian S.; Chen, Yu; Joshua Pfefer, T.


    The emerging technique of rapid prototyping with three-dimensional (3-D) printers provides a simple yet revolutionary method for fabricating objects with arbitrary geometry. The use of 3-D printing for generating morphologically biomimetic tissue phantoms based on medical images represents a potentially major advance over existing phantom approaches. Toward the goal of image-defined phantoms, we converted a segmented fundus image of the human retina into a matrix format and edited it to achieve a geometry suitable for printing. Phantoms with vessel-simulating channels were then printed using a photoreactive resin providing biologically relevant turbidity, as determined by spectrophotometry. The morphology of printed vessels was validated by x-ray microcomputed tomography. Channels were filled with hemoglobin (Hb) solutions undergoing desaturation, and phantoms were imaged with a near-infrared hyperspectral reflectance imaging system. Additionally, a phantom was printed incorporating two disjoint vascular networks at different depths, each filled with Hb solutions at different saturation levels. Light propagation effects noted during these measurements-including the influence of vessel density and depth on Hb concentration and saturation estimates, and the effect of wavelength on vessel visualization depth-were evaluated. Overall, our findings indicated that 3-D-printed biomimetic phantoms hold significant potential as realistic and practical tools for elucidating light-tissue interactions and characterizing biophotonic system performance.

  10. Hyperspectral Imaging Using Flexible Endoscopy for Laryngeal Cancer Detection

    Bianca Regeling


    Full Text Available Hyperspectral imaging (HSI is increasingly gaining acceptance in the medical field. Up until now, HSI has been used in conjunction with rigid endoscopy to detect cancer in vivo. The logical next step is to pair HSI with flexible endoscopy, since it improves access to hard-to-reach areas. While the flexible endoscope’s fiber optic cables provide the advantage of flexibility, they also introduce an interfering honeycomb-like pattern onto images. Due to the substantial impact this pattern has on locating cancerous tissue, it must be removed before the HS data can be further processed. Thereby, the loss of information is to minimize avoiding the suppression of small-area variations of pixel values. We have developed a system that uses flexible endoscopy to record HS cubes of the larynx and designed a special filtering technique to remove the honeycomb-like pattern with minimal loss of information. We have confirmed its feasibility by comparing it to conventional filtering techniques using an objective metric and by applying unsupervised and supervised classifications to raw and pre-processed HS cubes. Compared to conventional techniques, our method successfully removes the honeycomb-like pattern and considerably improves classification performance, while preserving image details.

  11. Multi-Color QWIP FPAs for Hyperspectral Thermal Emission Instruments

    Soibel, Alexander; Luong, Ed; Mumolo, Jason M.; Liu, John; Rafol, Sir B.; Keo, Sam A.; Johnson, William; Willson, Dan; Hill, Cory J.; Ting, David Z.-Y.; hide


    Infrared focal plane arrays (FPAs) covering broad mid- and long-IR spectral ranges are the central parts of the spectroscopic and imaging instruments in several Earth and planetary science missions. To be implemented in the space instrument these FPAs need to be large-format, uniform, reproducible, low-cost, low 1/f noise, and radiation hard. Quantum Well Infrared Photodetectors (QWIPs), which possess all needed characteristics, have a great potential for implementation in the space instruments. However a standard QWIP has only a relatively narrow spectral coverage. A multi-color QWIP, which is compromised of two or more detector stacks, can to be used to cover the broad spectral range of interest. We will discuss our recent work on development of multi-color QWIP for Hyperspectral Thermal Emission Spectrometer instruments. We developed QWIP compromising of two stacks centered at 9 and 10.5 ?m, and featuring 9 grating regions optimized to maximize the responsivity in the individual subbands across the 7.5-12 ?m spectral range. The demonstrated 1024x1024 QWIP FPA exhibited excellent performance with operability exceeding 99% and noise equivalent differential temperature of less than 15 mK across the entire 7.5-12 ?m spectral range.

  12. Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

    Yidong Tang


    Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

  13. Rapid prototyping of biomimetic vascular phantoms for hyperspectral reflectance imaging

    Ghassemi, Pejhman; Wang, Jianting; Melchiorri, Anthony J.; Ramella-Roman, Jessica C.; Mathews, Scott A.; Coburn, James C.; Sorg, Brian S.; Chen, Yu; Joshua Pfefer, T.


    Abstract. The emerging technique of rapid prototyping with three-dimensional (3-D) printers provides a simple yet revolutionary method for fabricating objects with arbitrary geometry. The use of 3-D printing for generating morphologically biomimetic tissue phantoms based on medical images represents a potentially major advance over existing phantom approaches. Toward the goal of image-defined phantoms, we converted a segmented fundus image of the human retina into a matrix format and edited it to achieve a geometry suitable for printing. Phantoms with vessel-simulating channels were then printed using a photoreactive resin providing biologically relevant turbidity, as determined by spectrophotometry. The morphology of printed vessels was validated by x-ray microcomputed tomography. Channels were filled with hemoglobin (Hb) solutions undergoing desaturation, and phantoms were imaged with a near-infrared hyperspectral reflectance imaging system. Additionally, a phantom was printed incorporating two disjoint vascular networks at different depths, each filled with Hb solutions at different saturation levels. Light propagation effects noted during these measurements—including the influence of vessel density and depth on Hb concentration and saturation estimates, and the effect of wavelength on vessel visualization depth—were evaluated. Overall, our findings indicated that 3-D-printed biomimetic phantoms hold significant potential as realistic and practical tools for elucidating light–tissue interactions and characterizing biophotonic system performance. PMID:26662064

  14. Pesticide residue quantification analysis by hyperspectral imaging sensors

    Liao, Yuan-Hsun; Lo, Wei-Sheng; Guo, Horng-Yuh; Kao, Ching-Hua; Chou, Tau-Meu; Chen, Junne-Jih; Wen, Chia-Hsien; Lin, Chinsu; Chen, Hsian-Min; Ouyang, Yen-Chieh; Wu, Chao-Cheng; Chen, Shih-Yu; Chang, Chein-I.


    Pesticide residue detection in agriculture crops is a challenging issue and is even more difficult to quantify pesticide residue resident in agriculture produces and fruits. This paper conducts a series of base-line experiments which are particularly designed for three specific pesticides commonly used in Taiwan. The materials used for experiments are single leaves of vegetable produces which are being contaminated by various amount of concentration of pesticides. Two sensors are used to collected data. One is Fourier Transform Infrared (FTIR) spectroscopy. The other is a hyperspectral sensor, called Geophysical and Environmental Research (GER) 2600 spectroradiometer which is a batteryoperated field portable spectroradiometer with full real-time data acquisition from 350 nm to 2500 nm. In order to quantify data with different levels of pesticide residue concentration, several measures for spectral discrimination are developed. Mores specifically, new measures for calculating relative power between two sensors are particularly designed to be able to evaluate effectiveness of each of sensors in quantifying the used pesticide residues. The experimental results show that the GER is a better sensor than FTIR in the sense of pesticide residue quantification.

  15. [Analysis of influencing factors of snow hyperspectral polarized reflections].

    Sun, Zhong-Qiu; Zhao, Yun-Sheng; Yan, Guo-Qian; Ning, Yan-Ling; Zhong, Gui-Xin


    Due to the need of snow monitoring and the impact of the global change on the snow, on the basis of the traditional research on snow, starting from the perspective of multi-angle polarized reflectance, we analyzed the influencing factors of snow from the incidence zenith angles, the detection zenith angles, the detection azimuth angles, polarized angles, the density of snow, the degree of pollution, and the background of the undersurface. It was found that these factors affected the spectral reflectance values of the snow, and the effect of some factors on the polarization hyperspectral reflectance observation is more evident than in the vertical observation. Among these influencing factors, the pollution of snow leads to an obvious change in the snow reflectance spectrum curve, while other factors have little effect on the shape of the snow reflectance spectrum curve and mainly impact the reflection ratio of the snow. Snow reflectance polarization information has not only important theoretical significance, but also wide application prospect, and provides new ideas and methods for the quantitative research on snow using the remote sensing technology.


    J. Avbelj


    Full Text Available Data fusion techniques require a good registration of all the used datasets. In remote sensing, images are usually geo-referenced using the GPS and IMU data. However, if more precise registration is required, image processing techniques can be employed. We propose a method for multi-modal image coregistration between hyperspectral images (HSI and digital surface models (DSM. The method is divided in three parts: object and line detection of the same object in HSI and DSM, line matching and determination of transformation parameters. Homogeneous coordinates are used to implement matching and adjustment of transformation parameters. The common object in HSI and DSM are building boundaries. They have apparent change in height and material, that can be detected in DSM and HSI, respectively. Thus, before the matching and transformation parameter computation, building outlines are detected and adjusted in HSI and DSM. We test the method on a HSI and two DSM, using extracted building outbounds and for comparison also extracted lines with a line detector. The results show that estimated building boundaries provide more line assignments, than using line detector.

  17. [Estimation of vegetation canopy water content using Hyperion hyperspectral data].

    Song, Xiao-Ning; Ma, Jian-Wei; Li, Xiao-Tao; Leng, Pei; Zhou, Fang-Cheng; Li, Shuang


    Vegetation canopy water content (VCWC) has widespread utility in agriculture, ecology and hydrology. Based on the PROSAIL model, a novel model for quantitative inversion of vegetation canopy water content using Hyperion hyperspectral data was explored. Firstly, characteristics of vegetation canopy reflection were investigated with the PROSAIL radiative transfer model, and it was showed that the first derivative at the right slope (980 - 1 070 nm) of the 970 nm water absorption feature (D98-1 070) was closely related to VCWC, and determination coefficient reached to 0.96. Then, bands 983, 993, 1 003, 1 013, 1 023, 1 033, 1 043, 1 053 and 1 063 nm of Hyperion data were selected to calculate D980-1 070, and VCWC was estimated using the proposed method. Finally, the retrieval result was verified using field measured data in Yingke oasis of the Heihe basin. It indicated that the mean relative error was 12.5%, RMSE was within 0.1 kg x m(-2) and the proposed model was practical and reliable. This study provides a more efficient way for obtaining VCWC of large area.

  18. Classification and Recognition of Tomb Information in Hyperspectral Image

    Gu, M.; Lyu, S.; Hou, M.; Ma, S.; Gao, Z.; Bai, S.; Zhou, P.


    There are a large number of materials with important historical information in ancient tombs. However, in many cases, these substances could become obscure and indistinguishable by human naked eye or true colour camera. In order to classify and identify materials in ancient tomb effectively, this paper applied hyperspectral imaging technology to archaeological research of ancient tomb in Shanxi province. Firstly, the feature bands including the main information at the bottom of the ancient tomb are selected by the Principal Component Analysis (PCA) transformation to realize the data dimension. Then, the image classification was performed using Support Vector Machine (SVM) based on feature bands. Finally, the material at the bottom of ancient tomb is identified by spectral analysis and spectral matching. The results show that SVM based on feature bands can not only ensure the classification accuracy, but also shorten the data processing time and improve the classification efficiency. In the material identification, it is found that the same matter identified in the visible light is actually two different substances. This research result provides a new reference and research idea for archaeological work.

  19. Hyperspectral imaging simulation of object under sea-sky background

    Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui


    Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

  20. Spectral Distortion in Lossy Compression of Hyperspectral Data

    Bruno Aiazzi


    Full Text Available Distortion allocation varying with wavelength in lossy compression of hyperspectral imagery is investigated, with the aim of minimizing the spectral distortion between original and decompressed data. The absolute angular error, or spectral angle mapper (SAM, is used to quantify spectral distortion, while radiometric distortions are measured by maximum absolute deviation (MAD for near-lossless methods, for example, differential pulse code modulation (DPCM, or mean-squared error (MSE for lossy methods, for example, spectral decorrelation followed by JPEG 2000. Two strategies of interband distortion allocation are compared: given a target average bit rate, distortion may be set to be constant with wavelength. Otherwise, it may be allocated proportionally to the noise level of each band, according to the virtually lossless protocol. Comparisons with the uncompressed originals show that the average SAM of radiance spectra is minimized by constant distortion allocation to radiance data. However, variable distortion allocation according to the virtually lossless protocol yields significantly lower SAM in case of reflectance spectra obtained from compressed radiance data, if compared with the constant distortion allocation at the same compression ratio.

  1. Multiangular hyperspectral investigation of polarized light in case 2 waters

    Tonizzo, A.; Zhou, J.; Gilerson, A.; Chowdhary, J.; Gross, B.; Moshary, F.; Ahmed, S.


    The focus of this work is on the dependence of in situ hyperspectral and multiangular polarized data on the size distribution and refractive index of the suspended particles. Underwater polarization measurements were obtained using a polarimeter developed at the Optical Remote Sensing Laboratory of the City College of New York, NY. The degree of polarization (DOP) of the underwater light field in coastal environments was measured and the water-leaving polarized radiance was derived. In-water optical properties were also measured with an ac-9 (WET Labs). Absorption and attenuation spectra are then used to derive information on the dissolved and suspend components in the water medium which are used in a vector radiative transfer code which provides the upwelling radiance. The model was run for various values of the refractive index of mineral particles until the modeled DOP matched the measured one. The relationship between the intensity of the maximum of the DOP and both the refractive index of the mineral particles and the shapes of their size distributions is analyzed in detail.

  2. Hyperspectral imaging applied to complex particulate solids systems

    Bonifazi, Giuseppe; Serranti, Silvia


    HyperSpectral Imaging (HSI) is based on the utilization of an integrated hardware and software (HW&SW) platform embedding conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Although HSI was originally developed for remote sensing, it has recently emerged as a powerful process analytical tool, for non-destructive analysis, in many research and industrial sectors. The possibility to apply on-line HSI based techniques in order to identify and quantify specific particulate solid systems characteristics is presented and critically evaluated. The originally developed HSI based logics can be profitably applied in order to develop fast, reliable and lowcost strategies for: i) quality control of particulate products that must comply with specific chemical, physical and biological constraints, ii) performance evaluation of manufacturing strategies related to processing chains and/or realtime tuning of operative variables and iii) classification-sorting actions addressed to recognize and separate different particulate solid products. Case studies, related to recent advances in the application of HSI to different industrial sectors, as agriculture, food, pharmaceuticals, solid waste handling and recycling, etc. and addressed to specific goals as contaminant detection, defect identification, constituent analysis and quality evaluation are described, according to authors' originally developed application.

  3. Rapid calibrated high-resolution hyperspectral imaging using tunable laser source

    Nguyen, Lam K.; Margalith, Eli


    We present a novel hyperspectral imaging technique based on tunable laser technology. By replacing the broadband source and tunable filters of a typical NIR imaging instrument, several advantages are realized, including: high spectral resolution, highly variable field-of-views, fast scan-rates, high signal-to-noise ratio, and the ability to use optical fiber for efficient and flexible sample illumination. With this technique, high-resolution, calibrated hyperspectral images over the NIR range can be acquired in seconds. The performance of system features will be demonstrated on two example applications: detecting melamine contamination in wheat gluten and separating bovine protein from wheat protein in cattle feed.

  4. Calibration, characterization, and first results with the Ocean PHILLS hyperspectral imager

    Davis, Curtiss O.; Kappus, Mary E.; Bowles, Jeffrey H.; Fisher, John; Antoniades, John A.; Carney, Megan


    The Ocean Portable Hyperspectral Imager for Low-Light spectroscopy (Ocean PHILLS), is a new hyperspectral imager specifically designed for imaging the coastal ocean. It uses a thinned, backside illuminated CCD for high sensitivity, and an all-reflective spectrograph with a convex grating in an Offner configuration to produce a distortion free image. Here we describe the instrument design and present the results of laboratory calibration and characterization and example results from a two week field experiment imaging the coastal waters off Lee Stocking, Island, Bahamas.

  5. Monitoring of biofilm formation on different material surfaces of medical devices using hyperspectral imaging method

    Kim, Do-Hyun; Kim, Moon S.; Hwang, Jeeseong


    Contamination of the inner surface of indwelling (implanted) medical devices by microbial biofilm is a serious problem. Some microbial bacteria such as Escherichia coli form biofilms that lead to potentially lifethreatening infections. Other types of medical devices such as bronchoscopes and duodenoscopes account for the highest number of reported endoscopic infections where microbial biofilm is one of the major causes for these infections. We applied a hyperspectral imaging method to detect biofilm contamination on the surface of several common materials used for medical devices. Such materials include stainless steel, titanium, and stainless-steeltitanium alloy. Potential uses of hyperspectral imaging technique to monitor biofilm attachment to different material surfaces are discussed.

  6. Classification of large-sized hyperspectral imagery using fast machine learning algorithms

    Xia, Junshi; Yokoya, Naoto; Iwasaki, Akira


    We present a framework of fast machine learning algorithms in the context of large-sized hyperspectral images classification from the theoretical to a practical viewpoint. In particular, we assess the performance of random forest (RF), rotation forest (RoF), and extreme learning machine (ELM) and the ensembles of RF and ELM. These classifiers are applied to two large-sized hyperspectral images and compared to the support vector machines. To give the quantitative analysis, we pay attention to comparing these methods when working with high input dimensions and a limited/sufficient training set. Moreover, other important issues such as the computational cost and robustness against the noise are also discussed.

  7. Passive film growth on carbon steel and its nanoscale features at various passivating potentials

    Li, Yuan; Cheng, Y. Frank


    Highlights: • Imaged the topography of passivated steel at various film-forming potentials. • Characterized the nanoscale features of passive films. • Determined the composition of passive films formed at various potentials. - Abstract: In this work, the passivation and topographic sub-structure of passive films on a carbon steel in a carbonate/bicarbonate solution was characterized by electrochemical measurements, atomic force microscopy and X-ray photoelectron spectroscopy. When passivating at a potential near the active-passive transition, the film contains the mixture of Fe_3O_4, Fe_2O_3 and FeOOH, with numerous nanoscale features. As the film-forming potential shifts positively, the passive film becomes more compact and the nanoscale features disappear. When the film is formed at a passive potential where the oxygen evolution is enabled, the content of FeOOH in the film increases, resulting in an amorphous topography and reduced corrosion resistance.

  8. Continued development of a portable widefield hyperspectral imaging (HSI) sensor for standoff detection of explosive, chemical, and narcotic residues

    Nelson, Matthew P.; Gardner, Charles W.; Klueva, Oksana; Tomas, David


    Passive, standoff detection of chemical, explosive and narcotic threats employing widefield, shortwave infrared (SWIR) hyperspectral imaging (HSI) continues to gain acceptance in defense and security fields. A robust and user-friendly portable platform with such capabilities increases the effectiveness of locating and identifying threats while reducing risks to personnel. In 2013 ChemImage Sensor Systems (CISS) introduced Aperio, a handheld sensor, using real-time SWIR HSI for wide area surveillance and standoff detection of explosives, chemical threats, and narcotics. That SWIR HSI system employed a liquid-crystal tunable filter for real-time automated detection and display of threats. In these proceedings, we report on a next generation device called VeroVision™, which incorporates an improved optical design that enhances detection performance at greater standoff distances with increased sensitivity and detection speed. A tripod mounted sensor head unit (SHU) with an optional motorized pan-tilt unit (PTU) is available for precision pointing and sensor stabilization. This option supports longer standoff range applications which are often seen at checkpoint vehicle inspection where speed and precision is necessary. Basic software has been extended to include advanced algorithms providing multi-target display functionality, automatic threshold determination, and an automated detection recipe capability for expanding the library as new threats emerge. In these proceedings, we report on the improvements associated with the next generation portable widefield SWIR HSI sensor, VeroVision™. Test data collected during development are presented in this report which supports the targeted applications for use of VeroVision™ for screening residue and bulk levels of explosive and drugs on vehicles and personnel at checkpoints as well as various applications for other secure areas. Additionally, we highlight a forensic application of the technology for assisting forensic

  9. An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles

    Youkyung Han


    Full Text Available Multitemporal hyperspectral remote sensing data have the potential to detect altered areas on the earth’s surface. However, dissimilar radiometric and geometric properties between the multitemporal data due to the acquisition time or position of the sensors should be resolved to enable hyperspectral imagery for detecting changes in natural and human-impacted areas. In addition, data noise in the hyperspectral imagery spectrum decreases the change-detection accuracy when general change-detection algorithms are applied to hyperspectral images. To address these problems, we present an unsupervised change-detection algorithm based on statistical analyses of spectral profiles; the profiles are generated from a synthetic image fusion method for multitemporal hyperspectral images. This method aims to minimize the noise between the spectra corresponding to the locations of identical positions by increasing the change-detection rate and decreasing the false-alarm rate without reducing the dimensionality of the original hyperspectral data. Using a quantitative comparison of an actual dataset acquired by airborne hyperspectral sensors, we demonstrate that the proposed method provides superb change-detection results relative to the state-of-the-art unsupervised change-detection algorithms.

  10. Point-and-stare operation and high-speed image acquisition in real-time hyperspectral imaging

    Driver, Richard D.; Bannon, David P.; Ciccone, Domenic; Hill, Sam L.


    The design and optical performance of a small-footprint, low-power, turnkey, Point-And-Stare hyperspectral analyzer, capable of fully automated field deployment in remote and harsh environments, is described. The unit is packaged for outdoor operation in an IP56 protected air-conditioned enclosure and includes a mechanically ruggedized fully reflective, aberration-corrected hyperspectral VNIR (400-1000 nm) spectrometer with a board-level detector optimized for point and stare operation, an on-board computer capable of full system data-acquisition and control, and a fully functioning internal hyperspectral calibration system for in-situ system spectral calibration and verification. Performance data on the unit under extremes of real-time survey operation and high spatial and high spectral resolution will be discussed. Hyperspectral acquisition including full parameter tracking is achieved by the addition of a fiber-optic based downwelling spectral channel for solar illumination tracking during hyperspectral acquisition and the use of other sensors for spatial and directional tracking to pinpoint view location. The system is mounted on a Pan-And-Tilt device, automatically controlled from the analyzer's on-board computer, making the HyperspecTM particularly adaptable for base security, border protection and remote deployments. A hyperspectral macro library has been developed to control hyperspectral image acquisition, system calibration and scene location control. The software allows the system to be operated in a fully automatic mode or under direct operator control through a GigE interface.

  11. The passive-aggressive organization.

    Kaplan, Robert S; Norton, David P


    Passive-aggressive organizations are friendly places to work: People are congenial, conflict is rare, and consensus is easy to reach. But, at the end of the day, even the best proposals fail to gain traction, and a company can go nowhere so imperturbably that it's easy to pretend everything is fine. Such companies are not necessarily saddled with mulishly passive-aggressive employees. Rather, they are filled with mostly well-intentioned people who are the victirms of flawed processes and policies. Commonly, a growing company's halfhearted or poorly thought-out attempts to decentralize give rise to multiple layers of managers, whose authority for making decisions becomes increasingly unclear. Some managers, as a result, hang back, while others won't own up to the calls they've made, inviting colleagues to second-guess or overturn the decisions. In such organizations, information does not circulate freely, and that makes it difficult for workers to understand the impact of their actions on company performance and for managers to correctly appraise employees' value to the organization. A failure to accurately match incentives to performance stifles initiative, and people do just enough to get by. Breaking free from this pattern is hard; a long history of seeing corporate initiatives ignored and then fade away tends to make people cynical. Often it's best to bring in an outsider to signal that this time things will be different. He or she will need to address every obstacle all at once: clarify decision rights; see to it that decisions stick; and reward people for sharing information and adding value, not for successfully negotiating corporate politics. If those steps are not taken, it's only a matter of time before the diseased elements of a passive-aggressive organization overwhelm the remaining healthy ones and drive the company into financial distress.

  12. Architectural Qualities in Passive Houses

    Brunsgaard, Camilla


    that it is possible to build this type of houses, but the knowledge and discussion about the architectural quality in the buildings is hardly present. The question is if the strategies for optimising energy use and indoor environment collide with the architectural qualities of buildings. This paper brings forth...... this discussion based in literature and four case studies. The paper highlights cases on how passive strategies for optimising energy use and indoor environment affect, restrict, inspire or create possibilities for the architectural expression and there through the architectural quality of the building....

  13. Passive Containment DataSet

    This data is for Figures 6 and 7 in the journal article. The data also includes the two EPANET input files used for the analysis described in the paper, one for the looped system and one for the block system.This dataset is associated with the following publication:Grayman, W., R. Murray , and D. Savic. Redesign of Water Distribution Systems for Passive Containment of Contamination. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(7): 381-391, (2016).

  14. Passive longitudinal phase space linearizer

    P. Craievich


    Full Text Available We report on the possibility to passively linearize the bunch compression process in electron linacs for the next generation x-ray free electron lasers. This can be done by using the monopole wakefields in a dielectric-lined waveguide. The optimum longitudinal voltage loss over the length of the bunch is calculated in order to compensate both the second-order rf time curvature and the second-order momentum compaction terms. Thus, the longitudinal phase space after the compression process is linearized up to a fourth-order term introduced by the convolution between the bunch and the monopole wake function.

  15. Measurement and Treatment of Passive Muscle Stiffness

    Kirk, Henrik

    , which aimed to investigate: 1) The development of a clinical method to evaluate and distinguish neural (reflex mediated stiffness) and non-neural (passive muscle stiffness) components of muscle stiffness in adults with CP by objective and reliable measurements. 2) The association between increased...... and reliability of the method, and argue for the use of the method in the clinical practice. The device is able to distinguish between passive muscle stiffness and reflex-mediated stiffness in subjects with CP. It shows good high intrarater and interrater reliability in evaluation of passive muscle stiffness...... to measure muscle stiffness, and distinguish between passive muscle stiffness and reflex-mediated stiffness. Furthermore, it is a reliable device to measure changes in passive ROM. Treatment of passive muscle stiffness should be directed towards intense training, comprising many repetitions with a functional...

  16. Forekomsten af passiv rygning i Danmark

    Kristensen, T S; Møller, L; Holstein, B E


    The occurrence of passive smoking in the adult population in Denmark has not been described previously. This article publishes data from three investigations all of which were carried out in 1987. One was an interview investigation of a random section of the Danish population carried out by the D...... inconvenienced by passive smoking at work and a corresponding fraction had taken steps to reduce the extent of passive smoking in their daily life. Udgivelsesdato: 1990-Aug-27...... showed consistent results as regards the occurrence of passive smoking among adult Danes. About 12% of non-smokers were exposed to passive smoking for at least eight hours and 40% for at least one hour daily. Altogether 73% were exposed to passive smoking daily. About one third of the non-smokers were...

  17. Columbia County Habitat for Humanity Passive Townhomes

    None, None


    Columbia County Habitat for Humanity (CCHH) (New York, Climate Zone 5A) built a pair of townhomes to Passive House Institute U.S. (PHIUS+ 2015) criteria to explore approaches for achieving Passive House performance (specifically with respect to exterior wall, space-conditioning, and ventilation strategies) within the labor and budget context inherent in a Habitat for Humanity project. CCHH’s goal is to eventually develop a cost-justified Passive House prototype design for future projects.

  18. Passive Nuclear Plants Program (UPDATE)

    Chimeno, M. A.


    The light water passive plants program (PCNP), today Advanced Nuclear Power Plants Program (PCNA), was constituted in order to reach the goals of the Spanish Electrical Sector in the field of advanced nuclear power plants, optimize the efforts of all Spanish initiatives, and increase joint presence in international projects. The last update of this program, featured in revision 5th of the Program Report, reflects the consolidation of the Spanish sector's presence in International programs of the advanced power plants on the basis of the practically concluded American ALWR program. Since the beginning of the program , the PCNP relies on financing from the Electrical sector, Ocide, SEPI-Endesa, Westinghouse, General Electric, as well as from the industrial cooperators, Initec, UTE (Initec- Empresarios Agrupados), Ciemat, Enusa, Ensa and Tecnatom. The program is made up of the following projects, already concluded: - EPRI's Advanced Light Water Plants Certification Project - Westinghouse's AP600 Project - General Electric's SBWR Project (presently paralyzed) and ABWR project Currently, the following project are under development, at different degrees of advance: - EPP project (European Passive Plant) - EBWR project (European Advanced Boiling Water Reactor)

  19. A Portable Passive Physiotherapeutic Exoskeleton

    Dasheek Naidu


    Full Text Available The public healthcare system in South Africa is in need of urgent attention in no small part because there has been an escalation in the number of stroke victims which could be due to the increase in hypertension in this urbanizing society. There is a growing need for physiotherapists and occupational therapists in the country, which is further hindered by the division between urban and rural areas. A possible solution is a portable passive physiotherapeutic exoskeleton device. The exoskeleton device has been formulated to encapsulate methodologies that enable the anthropomorphic integration between a biological and mechatronic limb. A physiotherapeutic mechanism was designed to be portable and adjustable, without limiting the spherical motion and workspace of the human arm. The exoskeleton was designed to be portable in the sense that it could be transported geographically. It is a complete device allowing for motion in the shoulder, elbow, wrist and hand joints. The inverse kinematics was solved iteratively via the Damped Least Squares (DLS method. The electronic and computer system allowed for professional personnel to either change an individual joint or a combination of joints angles via the kinematic models. A ramp PI controller was established to provide a smooth response to simulate the passive therapy motion.

  20. Liberal theory of passive citizenship

    Salatić Stevan


    Full Text Available In this seminar paper I will focus on the analysis of liberal theory of citizenship. The focus of the study will be on the liberal-communitarian dispute in the theory of citizenship, with main ideas of the most important representatives of liberal discourse in the field of citizenship also being discussed. I will look more closely at the ideas of T.H. Marshall, as the most significant writer of liberal orthodoxy in the second half of the twentieth century, his contribution to liberal theory of passive citizenship, but I will also deal with the ideas of his biggest critics, both from the aspect of liberalism and from the aspect of communitarianism, including Anthony Giddens, Claus Offe, Michael Mann, Barrington Moore and Brian Turner. The emphasis will be on Marshall's term 'conquest of citizenship', as well as on the derivation of various theories of state from the obtained rights achieved through the expansion of the concept of citizenship. Finally, I will say something about modern obstacles to theories of passive citizenship derived from the communitarian school.

  1. Passive propulsion in vortex wakes

    Beal, D. N.; Hover, F. S.; Triantafyllou, M. S.; Liao, J. C.; Lauder, G. V.

    A dead fish is propelled upstream when its flexible body resonates with oncoming vortices formed in the wake of a bluff cylinder, despite being well outside the suction region of the cylinder. Within this passive propulsion mode, the body of the fish extracts sufficient energy from the oncoming vortices to develop thrust to overcome its own drag. In a similar turbulent wake and at roughly the same distance behind a bluff cylinder, a passively mounted high-aspect-ratio foil is also shown to propel itself upstream employing a similar flow energy extraction mechanism. In this case, mechanical energy is extracted from the flow at the same time that thrust is produced. These results prove experimentally that, under proper conditions, a body can follow at a distance or even catch up to another upstream body without expending any energy of its own. This observation is also significant in the development of low-drag energy harvesting devices, and in the energetics of fish dwelling in flowing water and swimming behind wake-forming obstacles.

  2. Crop stress detection and classification using hyperspectral remote sensing

    Irby, Jon Trenton

    crop stresses utilizing hyperspectral remote sensing. Key words: crop stress, herbicide drift, remote sensing

  3. Assessment of spatial information for hyperspectral imaging of lesion

    Yang, Xue; Li, Gang; Lin, Ling


    Multiple diseases such as breast tumor poses a great threat to women's health and life, while the traditional detection method is complex, costly and unsuitable for frequently self-examination, therefore, an inexpensive, convenient and efficient method for tumor self-inspection is needed urgently, and lesion localization is an important step. This paper proposes an self-examination method for positioning of a lesion. The method adopts transillumination to acquire the hyperspectral images and to assess the spatial information of lesion. Firstly, multi-wavelength sources are modulated with frequency division, which is advantageous to separate images of different wavelength, meanwhile, the source serves as fill light to each other to improve the sensitivity in the low-lightlevel imaging. Secondly, the signal-to-noise ratio of transmitted images after demodulation are improved by frame accumulation technology. Next, gray distributions of transmitted images are analyzed. The gray-level differences is constituted by the actual transmitted images and fitting transmitted images of tissue without lesion, which is to rule out individual differences. Due to scattering effect, there will be transition zones between tissue and lesion, and the zone changes with wavelength change, which will help to identify the structure details of lesion. Finally, image segmentation is adopted to extract the lesion and the transition zones, and the spatial features of lesion are confirmed according to the transition zones and the differences of transmitted light intensity distributions. Experiment using flat-shaped tissue as an example shows that the proposed method can extract the space information of lesion.

  4. Soybean varieties discrimination using non-imaging hyperspectral sensor

    da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo


    Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.

  5. Hyperspectral observation of anthropogenic and biogenic pollution in coastal zone

    Lavrova, Olga; Loupian, Evgeny; Mityagina, Marina; Uvarov, Ivan

    The work presents results of anthropogenic and biogenic pollution detection in coastal zones of the Black and Caspian Seas based on satellite hyperspetral data provided by the Hyperion and HICO instruments. Techniques developed on the basis of the analysis of spectral characteristics calculated in special points were employed to address the following problems: (a) assessment of the blooming intensity of cyanobacteria and their distribution in bays of western Crimea and discrimination between anthropogenic pollutant discharge events and algae bloom; (b) detection of anthropogenic pollution in Crimean lakes utilized as industrial liquid discharge reservoirs; (c) detection of oil pollution in areas of shelf oil production in the Caspian Sea. Information values of different spectral bands and their composites were estimated in connection with the retrieval of the main sea water components: phytoplankton, suspended matter and colored organic matter, and also various anthropogenic pollutants, including oil. Software tools for thematic hyperspectral data processing in application to the investigation of sea coastal zones and internal water bodies were developed on the basis of the See the Sea geoportal created by the Space Research Institute RAS. The geoportal is focused on the study of processes in the world ocean with the emphasis on the advantages of satellite systems of observation. The tools that were introduced into the portal allow joint analysis of quasi-simultaneous satellite data, in particular data from the Hyperion, HICO, OLI Landsat-8, ETM Landsat-7 and TM Landsat-5 instruments. Results of analysis attempts combining data from different sensors are discussed. Their strong and weak points are highlighted. The study was completed with partial financial support from The Russian Foundation for Basic Research grants # 14-05-00520-a and 13-07-12017.

  6. Hyperspectral small animal fluorescence imaging: spectral selection imaging

    Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul


    Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

  7. Rapid and early detection of salmonella serotypes with hyperspectral microscope and multivariate data analysis

    This study was designed to evaluate hyperspectral microscope images for early and rapid detection of Salmonella serotypes: S. Enteritidis, S. Heidelberg, S. Infantis, S. Kentucky, and S. Typhimurium at incubation times of 6, 8, 10, 12, and 24 hours. Images were collected by an acousto-optical tunab...

  8. Hyperspectral analysis of mangrove foliar chemistry using PLSR and support vector regression

    Axelsson, C.; Skidmore, A.K.; Schlerf, M.; Fauzi, A.; Verhoef, W.


    Hyperspectral remote sensing enables the large-scale mapping of canopy biochemical properties. This study explored the possibility of retrieving the concentration of nitrogen, phosphorus, potassium, calcium, magnesium, and sodium from mangroves in the Berau Delta, Indonesia. The objectives of the

  9. Hyper-Spectral Imager in visible and near-infrared band for lunar ...

    India's first lunar mission, Chandrayaan-1, will have a Hyper-Spectral Imager in the visible and near-infrared spectral ... mapping of the Moon's crust in a large number of spectral channels. The planned .... In-flight verification may be done.

  10. The practical utility of hyperspectral remote sensing for early detection of emerald ash borer

    Richard Hallett; Jennifer Pontius; Mary Martin; Lucie Plourde


    Hyperspectral remote sensing technology has been used in forest ecology research for the last decade to examine landscape scale patterns of foliar chemistry (nitrogen, cellulose, and lignin) (Martin and Aber 1997), stand productivity (Smith et al. 2002), and soil nitrogen dynamics (Ollinger et al. 2002). More recently, techniques have been developed to map the location...

  11. Hyperspectral predictors for monitoring biomass production in Mediterranean mountain grasslands: Majella National Park, Italy

    Cho, M.A.; Skidmore, A.K.


    The research objective was to determine robust hyperspectral predictors for monitoring grass/herb biomass production on a yearly basis in the Majella National Park, Italy. HyMap images were acquired over the study area on 15 July 2004 and 4 July 2005. The robustness of vegetation indices and

  12. Linking rainforest ecophysiology and microclimate through fusion of airborne LiDAR and hyperspectral imagery

    Eben N. Broadbent; Angélica M. Almeyda Zambrano; Gregory P. Asner; Christopher B. Field; Brad E. Rosenheim; Ty Kennedy-Bowdoin; David E. Knapp; David Burke; Christian Giardina; Susan Cordell


    We develop and validate a high-resolution three-dimensional model of light and air temperature for a tropical forest interior in Hawaii along an elevation gradient varying greatly in structure but maintaining a consistent species composition. Our microclimate models integrate high-resolution airborne waveform light detection and ranging data (LiDAR) and hyperspectral...

  13. Assessment of plant species diversity based on hyperspectral indices at a fine scale.

    Peng, Yu; Fan, Min; Song, Jingyi; Cui, Tiantian; Li, Rui


    Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R 2  = 0.83), Pielou (R 2  = 0.87) and Shannon-Wiener index (R 2  = 0.88). Stepwise linear regression of FD (R 2  = 0.81, R 2  = 0.82) and spectral vegetation indices (R 2  = 0.51, R 2  = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.


    Visible to near-infrared, airborne hyperspectral data were successfully used to estimate water quality parameters such as chlorophyll a, turbidity and total phosphorus from the Great Miami River, Ohio. During the summer of 1999, spectral data were collected with a hand-held fiel...

  15. Nondestructive measurement of tomato postharvest quality using a multichannel hyperspectral imaging probe

    A multichannel hyperspectral imaging probe with 30 optic fibers covering the wavelength range of 550-1,650 nm and the light source-detector distances of 1.5-36 mm was recently developed for optical property measurement and quality evaluation of food products with flat or curved surface. This paper r...

  16. Concept for a hyperspectral remote sensing algorithm for floating marine macro plastics

    Goddijn-Murphy, Lonneke; Peters, Steef; van Sebille, Erik; James, Neil A.; Gibb, Stuart


    There is growing global concern over the chemical, biological and ecological impact of plastics in the ocean. Remote sensing has the potential to provide long-term, global monitoring but for marine plastics it is still in its early stages. Some progress has been made in hyperspectral remote sensing

  17. Fluorescence hyperspectral imaging technique for the foreign substance detection on fresh-cut lettuce

    Nondestructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed in order to detect worms on fresh-cut lettuce. The optimal wavebands for detecting worms on fresh-cut lettuce were investigated using the one-way ANOVA analysis and correlation analysis. The worm detec...

  18. On-line fresh-cut lettuce quality measurement system using hyperspectral imaging

    Lettuce, which is a main type of fresh-cut vegetable, has been used in various fresh-cut products. In this study, an online quality measurement system for detecting foreign substances on the fresh-cut lettuce was developed using hyperspectral reflectance imaging. The online detection system with a s...

  19. A coarse-to-fine approach for medical hyperspectral image classification with sparse representation

    Chang, Lan; Zhang, Mengmeng; Li, Wei


    A coarse-to-fine approach with sparse representation is proposed for medical hyperspectral image classification in this work. Segmentation technique with different scales is employed to exploit edges of the input image, where coarse super-pixel patches provide global classification information while fine ones further provide detail information. Different from common RGB image, hyperspectral image has multi bands to adjust the cluster center with more high precision. After segmentation, each super pixel is classified by recently-developed sparse representation-based classification (SRC), which assigns label for testing samples in one local patch by means of sparse linear combination of all the training samples. Furthermore, segmentation with multiple scales is employed because single scale is not suitable for complicate distribution of medical hyperspectral imagery. Finally, classification results for different sizes of super pixel are fused by some fusion strategy, offering at least two benefits: (1) the final result is obviously superior to that of segmentation with single scale, and (2) the fusion process significantly simplifies the choice of scales. Experimental results using real medical hyperspectral images demonstrate that the proposed method outperforms the state-of-the-art SRC.

  20. Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging

    Visible and near-infrared (VNIR) hyperspectral imaging (400–900 nm) was used to evaluate pH of fresh chicken breast fillets (pectoralis major muscle) from the bone (dorsal) side of individual fillets. After the principal component analysis (PCA), a band threshold method was applied to the first prin...

  1. Estimating and mapping grass phosphorus concentration in an African savanna using hyperspectral image data

    Mutanga, O.; Kumar, L.


    We tested the utility of imaging spectroscopy and neural networks to map phosphorus concentration in savanna grass using airborne HyMAP image data. We also sought to ascertain the key wavelengths for phosphorus prediction using hyperspectral remote sensing. The remote sensing of foliar phosphorus


    H. Aasen


    Full Text Available Hyperspectral data has great potential for vegetation parameter retrieval. However, due to angular effects resulting from different sun-surface-sensor geometries, objects might appear differently depending on the position of an object within the field of view of a sensor. Recently, lightweight snapshot cameras have been introduced, which capture hyperspectral information in two spatial and one spectral dimension and can be mounted on unmanned aerial vehicles. This study investigates the influence of the different viewing geometries within an image on the apparent hyperspectral reflection retrieved by these sensors. Additionally, it is evaluated how hyperspectral vegetation indices like the NDVI are effected by the angular effects within a single image and if the viewing geometry influences the apparent heterogeneity with an area of interest. The study is carried out for a barley canopy at booting stage. The results show significant influences of the position of the area of interest within the image. The red region of the spectrum is more influenced by the position than the near infrared. The ability of the NDVI to compensate these effects was limited to the capturing positions close to nadir. The apparent heterogeneity of the area of interest is the highest close to a nadir.

  3. Innovative Hyperspectral Imaging-Based Techniques for Quality Evaluation of Fruits and Vegetables: A Review

    Yuzhen Lu


    Full Text Available New, non-destructive sensing techniques for fast and more effective quality assessment of fruits and vegetables are needed to meet the ever-increasing consumer demand for better, more consistent and safer food products. Over the past 15 years, hyperspectral imaging has emerged as a new generation of sensing technology for non-destructive food quality and safety evaluation, because it integrates the major features of imaging and spectroscopy, thus enabling the acquisition of both spectral and spatial information from an object simultaneously. This paper first provides a brief overview of hyperspectral imaging configurations and common sensing modes used for food quality and safety evaluation. The paper is, however, focused on the three innovative hyperspectral imaging-based techniques or sensing platforms, i.e., spectral scattering, integrated reflectance and transmittance, and spatially-resolved spectroscopy, which have been developed in our laboratory for property and quality evaluation of fruits, vegetables and other food products. The basic principle and instrumentation of each technique are described, followed by the mathematical methods for processing and extracting critical information from the acquired data. Applications of these techniques for property and quality evaluation of fruits and vegetables are then presented. Finally, concluding remarks are given on future research needs to move forward these hyperspectral imaging techniques.

  4. Algorithm-Eigenvalue Estimation of Hyperspectral Wishart Covariance Matrices from a Limited Number of Samples


    biometrics for physiological characteristics, hyperspectral remote sensing for detecting signals buried in noise and clutter, and medical genetics for...s); %approximate bounds on the eigenvalues used in Eq. (8) that are derived %from the Marcenko- Pastur law k=p./n; %band

  5. Detection of Glycoalkaloids and Chlorophyll in Potatoes (Solanum tuberosum L.) by Hyperspectral Imaging

    Kjær, Anders; Nielsen, Glenn; Stærke, Søren


    The purpose of the study was to investigate the use of hyperspectral imaging (HSI) to detect and quantify chlorophyll (Chl) and total glycoalkaloid concentrations (TGA) in potatoes. To create a set of tubers with different concentrations of Chl and TGA, potatoes of four varieties were wounded...

  6. Detection of wheat powdery mildew by differentiating background factors using hyperspectral imaging

    Accurate assessment of crop disease severities is the key for precision application of pesticides to prevent disease infestation. In-situ hyperspectral imaging technology can provide high-resolution imagery with spectra for rapid identification of crop disease and determining disease infestation pat...

  7. Hyperspectral diffuse reflectance for determination of the optical properties of milk and fruit and vegetable juices

    Qin, Jianwei; Lu, Renfu


    Absorption and reduced scattering coefficients are two fundamental optical properties for turbid biological materials. This paper presents the technique and method of using hyperspectral diffuse reflectance for fast determination of the optical properties of fruit and vegetable juices and milks. A hyperspectral imaging system was used to acquire spatially resolved steady-state diffuse reflectance over the spectral region between 530 and 900 nm from a variety of fruit and vegetable juices (citrus, grapefruit, orange, and vegetable) and milks with different fat levels (full, skim and mixed). The system collected diffuse reflectance in the source-detector separation range from 1.1 to 10.0 mm. The hyperspectral reflectance data were analyzed by using a diffusion theory model for semi-infinite homogeneous media. The absorption and reduced scattering coefficients of the fruit and vegetable juices and milks were extracted by inverse algorithms from the scattering profiles for wavelengths of 530-900 nm. Values of the absorption and reduced scattering coefficient at 650 nm were highly correlated to the fat content of the milk samples with the correlation coefficient of 0.990 and 0.989, respectively. The hyperspectral imaging technique can be extended to the measurement of other liquid and solid foods in which light scattering is dominant.

  8. Evaluation of hyperspectral reflectance for estimating dry matter and sugar concentration in processing potatoes

    The measurement of sugar concentration and dry matter in processing potatoes is a time and resource intensive activity, cannot be performed in the field, and does not easily measure within tuber variation. A proposed method to improve the phenotyping of processing potatoes is to employ hyperspectral...

  9. An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation

    Himar Fabelo


    Full Text Available Hyperspectral imaging (HSI allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400–1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min, making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes.

  10. Detecting Sulfuric and Nitric Acid Rain Stresses on Quercus glauca through Hyperspectral Responses.

    Wang, Shanqian; Zhang, Xiuying; Ma, Yuandan; Li, Xinhui; Cheng, Min; Zhang, Xiaomin; Liu, Lei


    Acid rain, which has become one of the most severe global environmental issues, is detrimental to plant growth. However, effective methods for monitoring plant responses to acid rain stress are currently lacking. The hyperspectral technique provides a cost-effective and nondestructive way to diagnose acid rain stresses. Taking a widely distributed species ( Quercus glauca ) in Southern China as an example, this study aims to monitor the hyperspectral responses of Q. glauca to simulated sulfuric acid rain (SAR) and nitric acid rain (NAR). A total of 15 periods of leaf hyperspectral data under four pH levels of SAR and NAR were obtained during the experiment. The results showed that hyperspectral information could be used to distinguish plant responses under acid rain stress. An index (green peak area index, GPAI) was proposed to indicate acid rain stresses, based on the significantly variations in the region of 500-660 nm. Light acid rain (pH 4.5 SAR and NAR) promoted Q. glauca growth relative to the control groups (pH 5.6 SAR and NAR); moderate acid rain (pH 3.0 SAR) firstly promoted and then inhibited plant growth, while pH 3.0 NAR showed mild inhibitory effects during the experiment; and heavy acid rain (pH 2.0) significantly inhibited plant growth. Compared with NAR, SAR induced more serious damages to Q. glauca . These results could help monitor acid rain stress on plants on a regional scale using remote sensing techniques.

  11. Minimum volume simplicial enclosure for spectral unmixing of remotely sensed hyperspectral data

    Hendrix, E.M.T.; García, I.; Plaza, J.; Plaza, A.


    Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. Linear spectral unmixing relies on two main steps: 1) identification of pure spectral constituents (endmembers), and 2) end member abundance estimation in mixed pixels. One of the main problems concerning the

  12. Detection of microbial biofilms on food processing surfaces: Hyperspectral fluorescence imaging study

    We used a portable hyperspectral fluorescence imaging system to evaluate biofilm formations on four types of food processing surface materials including stainless steel, polypropylene used for cutting boards, and household counter top materials such as formica and granite. The objective of this inve...

  13. A comparison of hyperspectral reflectance and fluorescence imaging techniques for detection of contaminants on leafy greens

    Ensuring the supply of safe, contaminant free fresh fruit and vegetables is of importance to consumers, suppliers and governments worldwide. In this study, three hyperspectral imaging (HSI) configurations coupled with two multivariate image analysis techniques are compared for detection of fecal con...

  14. Assessment of bacterial biofilm on stainless steel by hyperspectral fluorescence imaging

    Hyperspectral fluorescence imaging techniques were investigated for detection of two genera of microbial biofilms on stainless steel material which is commonly used to manufacture food processing equipment. Stainless steel coupons were deposited in nonpathogenic E. coli O157:H7 and Salmonella cultu...

  15. Automated cart with VIS/NIR hyperspectral reflectance and fluorescence imaging capabilities

    A system to take high-resolution VIS/NIR hyperspectral reflectance and fluorescence images in outdoor fields using ambient lighting or a pulsed laser (355 nm), respectively, for illumination was designed, built, and tested. Components of the system include a semi-autonomous cart, a gated-intensified...

  16. Classification of gram-positive and gram-negative foodborne pathogenic bacteria with hyperspectral microscope imaging

    Optical method with hyperspectral microscope imaging (HMI) has potential for identification of foodborne pathogenic bacteria from microcolonies rapidly with a cell level. A HMI system that provides both spatial and spectral information could be an effective tool for analyzing spectral characteristic...

  17. Rapid identification of salmonella serotypes with stereo and hyperspectral microscope imaging Methods

    The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

  18. Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma In Situ

    Yasser Khouj


    Full Text Available Hyperspectral imaging (HSI is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues. Tissue samples mounted on slides were identified from 10 different patients. Samples from each patient included both normal and ductal carcinoma tissue, both stained with hematoxylin and eosin stain and unstained. Slides were imaged using a snapshot HSI system, and the spectral reflectance differences were evaluated. Analysis of the spectral reflectance values indicated that wavelengths near 550 nm showed the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. The K-means method was applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with true negative rate of 95.8%, and false positive rate of 4.2%. These results were verified by ground-truth marking of the tissue samples by a pathologist. In the hyperspectral image analysis, the image processing algorithm, K-means, shows the greatest potential for building a semi-automated system that could identify and sort between normal and ductal carcinoma in situ tissues.

  19. Mapping beech (Fagus sylvatica L.) forest structure with airborne hyperspectral imagery

    Cho, Moses A


    Full Text Available The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast-height (DBH), mean tree height and tree density of a closed canopy beech forest...

  20. Hyperspectral imaging and multivariate analysis in the dried blood spots investigations

    Majda, Alicja; Wietecha-Posłuszny, Renata; Mendys, Agata; Wójtowicz, Anna; Łydżba-Kopczyńska, Barbara


    The aim of this study was to apply a new methodology using the combination of the hyperspectral imaging and the dry blood spot (DBS) collecting. Application of the hyperspectral imaging is fast and non-destructive. DBS method offers the advantage also on the micro-invasive blood collecting and low volume of required sample. During experimental step, the reflected light was recorded by two hyperspectral systems. The collection of 776 spectral bands in the VIS-NIR range (400-1000 nm) and 256 spectral bands in the SWIR range (970-2500 nm) was applied. Pixel has the size of 8 × 8 and 30 × 30 µm for VIS-NIR and SWIR camera, respectively. The obtained data in the form of hyperspectral cubes were treated with chemometric methods, i.e., minimum noise fraction and principal component analysis. It has been shown that the application of these methods on this type of data, by analyzing the scatter plots, allows a rapid analysis of the homogeneity of DBS, and the selection of representative areas for further analysis. It also gives the possibility of tracking the dynamics of changes occurring in biological traces applied on the surface. For the analyzed 28 blood samples, described method allowed to distinguish those blood stains because of time of apply.

  1. Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer

    Goto, Atsushi; Nishikawa, Jun; Kiyotoki, Shu; Nakamura, Munetaka; Nishimura, Junichi; Okamoto, Takeshi; Ogihara, Hiroyuki; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao


    Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa.

  2. Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

    Antonio Plaza


    Full Text Available Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS system over theWorld Trade Center (WTC in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.

  3. Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

    Paz Abel


    Full Text Available Abstract Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS system over theWorld Trade Center (WTC in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.

  4. Hyperspectral Imaging and K-Means Classification for Histologic Evaluation of Ductal Carcinoma In Situ.

    Khouj, Yasser; Dawson, Jeremy; Coad, James; Vona-Davis, Linda


    Hyperspectral imaging (HSI) is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues. Tissue samples mounted on slides were identified from 10 different patients. Samples from each patient included both normal and ductal carcinoma tissue, both stained with hematoxylin and eosin stain and unstained. Slides were imaged using a snapshot HSI system, and the spectral reflectance differences were evaluated. Analysis of the spectral reflectance values indicated that wavelengths near 550 nm showed the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. The K-means method was applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with true negative rate of 95.8%, and false positive rate of 4.2%. These results were verified by ground-truth marking of the tissue samples by a pathologist. In the hyperspectral image analysis, the image processing algorithm, K-means, shows the greatest potential for building a semi-automated system that could identify and sort between normal and ductal carcinoma in situ tissues.

  5. Modelling Water Stress in a Shiraz Vineyard Using Hyperspectral Imaging and Machine Learning

    Kyle Loggenberg


    Full Text Available The detection of water stress in vineyards plays an integral role in the sustainability of high-quality grapes and prevention of devastating crop loses. Hyperspectral remote sensing technologies combined with machine learning provides a practical means for modelling vineyard water stress. In this study, we applied two ensemble learners, i.e., random forest (RF and extreme gradient boosting (XGBoost, for discriminating stressed and non-stressed Shiraz vines using terrestrial hyperspectral imaging. Additionally, we evaluated the utility of a spectral subset of wavebands, derived using RF mean decrease accuracy (MDA and XGBoost gain. Our results show that both ensemble learners can effectively analyse the hyperspectral data. When using all wavebands (p = 176, RF produced a test accuracy of 83.3% (KHAT (kappa analysis = 0.67, and XGBoost a test accuracy of 80.0% (KHAT = 0.6. Using the subset of wavebands (p = 18 produced slight increases in accuracy ranging from 1.7% to 5.5% for both RF and XGBoost. We further investigated the effect of smoothing the spectral data using the Savitzky-Golay filter. The results indicated that the Savitzky-Golay filter reduced model accuracies (ranging from 0.7% to 3.3%. The results demonstrate the feasibility of terrestrial hyperspectral imagery and machine learning to create a semi-automated framework for vineyard water stress modelling.

  6. Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

    Di Napoli, Claudia; Pope, Iestyn; Masia, Francesco; Watson, Peter; Langbein, Wolfgang; Borri, Paola


    In this work, we demonstrate the applicability of coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy for quantitative chemical imaging of saturated and unsaturated lipids in human stem-cell derived adipocytes. We compare dual-frequency/differential CARS (D-CARS), which enables rapid imaging and simple data analysis, with broadband hyperspectral CARS microscopy analyzed using an unsupervised phase-retrieval and factorization method recently developed by us for quantitative chemical image analysis. Measurements were taken in the vibrational fingerprint region (1200–2000/cm) and in the CH stretch region (2600–3300/cm) using a home-built CARS set-up which enables hyperspectral imaging with 10/cm resolution via spectral focussing from a single broadband 5 fs Ti:Sa laser source. Through a ratiometric analysis, both D-CARS and phase-retrieved hyperspectral CARS determine the concentration of unsaturated lipids with comparable accuracy in the fingerprint region, while in the CH stretch region D-CARS provides only a qualitative contrast owing to its non-linear behavior. When analyzing hyperspectral CARS images using the blind factorization into susceptibilities and concentrations of chemical components recently demonstrated by us, we are able to determine vol:vol concentrations of different lipid components and spatially resolve inhomogeneities in lipid composition with superior accuracy compared to state-of-the art ratiometric methods. PMID:24877002

  7. Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

    Varga, Timothy A; Asner, Gregory P


    Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.

  8. Quantitative coating thickness determination using a coefficient-independent hyperspectral scattering model

    Dingemans, LM; Papadakis, V.; Liu, P.; Adam, A.J.L.; Groves, R.M.


    Hyperspectral imaging is a technique that enables the mapping of spectral signatures across a surface. It is most commonly used for surface chemical mapping in fields as diverse as satellite remote sensing, biomedical imaging and heritage science. Existing models, such as the

  9. Assimilation of SAPHIR radiance: impact on hyperspectral radiances in 4D-VAR

    Indira Rani, S.; Doherty, Amy; Atkinson, Nigel; Bell, William; Newman, Stuart; Renshaw, Richard; George, John P.; Rajagopal, E. N.


    Assimilation of a new observation dataset in an NWP system may affect the quality of an existing observation data set against the model background (short forecast), which in-turn influence the use of an existing observation in the NWP system. Effect of the use of one data set on the use of another data set can be quantified as positive, negative or neutral. Impact of the addition of new dataset is defined as positive if the number of assimilated observations of an existing type of observation increases, and bias and standard deviation decreases compared to the control (without the new dataset) experiment. Recently a new dataset, Megha Tropiques SAPHIR radiances, which provides atmospheric humidity information, is added in the Unified Model 4D-VAR assimilation system. In this paper we discuss the impact of SAPHIR on the assimilation of hyper-spectral radiances like AIRS, IASI and CrIS. Though SAPHIR is a Microwave instrument, its impact can be clearly seen in the use of hyper-spectral radiances in the 4D-VAR data assimilation systems in addition to other Microwave and InfraRed observation. SAPHIR assimilation decreased the standard deviation of the spectral channels of wave number from 650 -1600 cm-1 in all the three hyperspectral radiances. Similar impact on the hyperspectral radiances can be seen due to the assimilation of other Microwave radiances like from AMSR2 and SSMIS Imager.

  10. Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

    Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

  11. Orientational imaging of a single plasmonic nanoparticle using dark-field hyperspectral imaging

    Mehta, Nishir; Mahigir, Amirreza; Veronis, Georgios; Gartia, Manas Ranjan


    Orientation of plasmonic nanostructures is an important feature in many nanoscale applications such as catalyst, biosensors DNA interactions, protein detections, hotspot of surface enhanced Raman spectroscopy (SERS), and fluorescence resonant energy transfer (FRET) experiments. However, due to diffraction limit, it is challenging to obtain the exact orientation of the nanostructure using standard optical microscope. Hyperspectral Imaging Microscopy is a state-of-the-art visualization technology that combines modern optics with hyperspectral imaging and computer system to provide the identification and quantitative spectral analysis of nano- and microscale structures. In this work, initially we use transmitted dark field imaging technique to locate single nanoparticle on a glass substrate. Then we employ hyperspectral imaging technique at the same spot to investigate orientation of single nanoparticle. No special tagging or staining of nanoparticle has been done, as more likely required in traditional microscopy techniques. Different orientations have been identified by carefully understanding and calibrating shift in spectral response from each different orientations of similar sized nanoparticles. Wavelengths recorded are between 300 nm to 900 nm. The orientations measured by hyperspectral microscopy was validated using finite difference time domain (FDTD) electrodynamics calculations and scanning electron microscopy (SEM) analysis. The combination of high resolution nanometer-scale imaging techniques and the modern numerical modeling capacities thus enables a meaningful advance in our knowledge of manipulating and fabricating shaped nanostructures. This work will advance our understanding of the behavior of small nanoparticle clusters useful for sensing, nanomedicine, and surface sciences.

  12. Utility requirements for advanced LWR passive plants

    Yedidia, J.M.; Sugnet, W.R.


    LWR Passive Plants are becoming an increasingly attractive and prominent option for future electric generating capacity for U.S. utilities. Conceptual designs for ALWR Passive Plants are currently being developed by U.S. suppliers. EPRI-sponsored work beginning in 1985 developed preliminary conceptual designs for a passive BWR and PWR. DOE-sponsored work from 1986 to the present in conjunction with further EPRI-sponsored studies has continued this development to the point of mature conceptual designs. The success to date in developing the ALWR Passive Plant concepts has substantially increased utility interest. The EPRI ALWR Program has responded by augmenting its initial scope to develop a Utility Requirements Document for ALWR Passive Plants. These requirements will be largely based on the ALWR Utility Requirements Document for Evolutionary Plants, but with significant changes in areas related to the passive safety functions and system configurations. This work was begun in late 1988, and the thirteen-chapter Passive Plant Utility Requirements Document will be completed in 1990. This paper discusses the progress to date in developing the Passive Plant requirements, reviews the top-level requirements, and discusses key issues related to adaptation of the utility requirements to passive safety functions and system configurations. (orig.)

  13. Multiple mechanisms quench passive spiral galaxies

    Fraser-McKelvie, Amelia; Brown, Michael J. I.; Pimbblet, Kevin; Dolley, Tim; Bonne, Nicolas J.


    We examine the properties of a sample of 35 nearby passive spiral galaxies in order to determine their dominant quenching mechanism(s). All five low-mass (M⋆ environments. We postulate that cluster-scale gas stripping and heating mechanisms operating only in rich clusters are required to quench low-mass passive spirals, and ram-pressure stripping and strangulation are obvious candidates. For higher mass passive spirals, while trends are present, the story is less clear. The passive spiral bar fraction is high: 74 ± 15 per cent, compared with 36 ± 5 per cent for a mass, redshift and T-type matched comparison sample of star-forming spiral galaxies. The high mass passive spirals occur mostly, but not exclusively, in groups, and can be central or satellite galaxies. The passive spiral group fraction of 74 ± 15 per cent is similar to that of the comparison sample of star-forming galaxies at 61 ± 7 per cent. We find evidence for both quenching via internal structure and environment in our passive spiral sample, though some galaxies have evidence of neither. From this, we conclude no one mechanism is responsible for quenching star formation in passive spiral galaxies - rather, a mixture of mechanisms is required to produce the passive spiral distribution we see today.

  14. Inherent/passive safety for fusion

    Piet, S.J.


    The concept of inherent or passive passive safety for fusion energy is explored, defined, and partially quantified. Four levels of safety assurance are defined, which range from true inherent safety to passive safety to protection via active engineered safeguard systems. Fusion has the clear potential for achieving inherent or passive safety, which should be an objective of fusion research and design. Proper material choice might lead to both inherent safety and high mass power density, improving both safety and economics. When inherent safety is accomplished, fusion will be well on the way to achieving its ultimate potential and to be truly different and superior

  15. Passive Wireless SAW Humidity Sensors, Phase I

    National Aeronautics and Space Administration — This proposal describes the preliminary development of passive wireless surface acoustic wave (SAW) based humidity sensors for NASA application to distributed...

  16. Passive cavitation imaging with ultrasound arrays.

    Salgaonkar, Vasant A; Datta, Saurabh; Holland, Christy K; Mast, T Douglas


    A method is presented for passive imaging of cavitational acoustic emissions using an ultrasound array, with potential application in real-time monitoring of ultrasound ablation. To create such images, microbubble emissions were passively sensed by an imaging array and dynamically focused at multiple depths. In this paper, an analytic expression for a passive image is obtained by solving the Rayleigh-Sommerfield integral, under the Fresnel approximation, and passive images were simulated. A 192-element array was used to create passive images, in real time, from 520-kHz ultrasound scattered by a 1-mm steel wire. Azimuthal positions of this target were accurately estimated from the passive images. Next, stable and inertial cavitation was passively imaged in saline solution sonicated at 520 kHz. Bubble clusters formed in the saline samples were consistently located on both passive images and B-scans. Passive images were also created using broadband emissions from bovine liver sonicated at 2.2 MHz. Agreement was found between the images and source beam shape, indicating an ability to map therapeutic ultrasound beams in situ. The relation between these broadband emissions, sonication amplitude, and exposure conditions are discussed.

  17. Hybrid Active-Passive Radiation Shielding System

    National Aeronautics and Space Administration — A radiation shielding system is proposed that integrates active magnetic fields with passive shielding materials. The objective is to increase the shielding...

  18. Universality in passively advected hydrodynamic fields : the case of a passive vector with pressure

    Benzi, R.; Biferale, L.; Toschi, F.


    Universality of statistical properties of passive quantities advected by turbulent velocity fields at changing the passive forcing mechanism is discussed. In particular, we concentrate on the statistical properties of an hydrodynamic system with pressure. We present theoretical arguments and

  19. Band registration of tuneable frame format hyperspectral UAV imagers in complex scenes

    Honkavaara, Eija; Rosnell, Tomi; Oliveira, Raquel; Tommaselli, Antonio


    A recent revolution in miniaturised sensor technology has provided markets with novel hyperspectral imagers operating in the frame format principle. In the case of unmanned aerial vehicle (UAV) based remote sensing, the frame format technology is highly attractive in comparison to the commonly utilised pushbroom scanning technology, because it offers better stability and the possibility to capture stereoscopic data sets, bringing an opportunity for 3D hyperspectral object reconstruction. Tuneable filters are one of the approaches for capturing multi- or hyperspectral frame images. The individual bands are not aligned when operating a sensor based on tuneable filters from a mobile platform, such as UAV, because the full spectrum recording is carried out in the time-sequential principle. The objective of this investigation was to study the aspects of band registration of an imager based on tuneable filters and to develop a rigorous and efficient approach for band registration in complex 3D scenes, such as forests. The method first determines the orientations of selected reference bands and reconstructs the 3D scene using structure-from-motion and dense image matching technologies. The bands, without orientation, are then matched to the oriented bands accounting the 3D scene to provide exterior orientations, and afterwards, hyperspectral orthomosaics, or hyperspectral point clouds, are calculated. The uncertainty aspects of the novel approach were studied. An empirical assessment was carried out in a forested environment using hyperspectral images captured with a hyperspectral 2D frame format camera, based on a tuneable Fabry-Pérot interferometer (FPI) on board a multicopter and supported by a high spatial resolution consumer colour camera. A theoretical assessment showed that the method was capable of providing band registration accuracy better than 0.5-pixel size. The empirical assessment proved the performance and showed that, with the novel method, most parts of

  20. Contrast based band selection for optimized weathered oil detection in hyperspectral images

    Levaux, Florian; Bostater, Charles R., Jr.; Neyt, Xavier


    Hyperspectral imagery offers unique benefits for detection of land and water features due to the information contained in reflectance signatures such as the bi-directional reflectance distribution function or BRDF. The reflectance signature directly shows the relative absorption and backscattering features of targets. These features can be very useful in shoreline monitoring or surveillance applications, for example to detect weathered oil. In real-time detection applications, processing of hyperspectral data can be an important tool and Optimal band selection is thus important in real time applications in order to select the essential bands using the absorption and backscatter information. In the present paper, band selection is based upon the optimization of target detection using contrast algorithms. The common definition of the contrast (using only one band out of all possible combinations available within a hyperspectral image) is generalized in order to consider all the possible combinations of wavelength dependent contrasts using hyperspectral images. The inflection (defined here as an approximation of the second derivative) is also used in order to enhance the variations in the reflectance spectra as well as in the contrast spectrua in order to assist in optimal band selection. The results of the selection in term of target detection (false alarms and missed detection) are also compared with a previous method to perform feature detection, namely the matched filter. In this paper, imagery is acquired using a pushbroom hyperspectral sensor mounted at the bow of a small vessel. The sensor is mechanically rotated using an optical rotation stage. This opto-mechanical scanning system produces hyperspectral images with pixel sizes on the order of mm to cm scales, depending upon the distance between the sensor and the shoreline being monitored. The motion of the platform during the acquisition induces distortions in the collected HSI imagery. It is therefore