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1

Hyperspectral Imaging Sensors and the Marine Coastal Zone  

NASA Technical Reports Server (NTRS)

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.

Richardson, Laurie L.

2000-01-01

2

The Hyperspectral Imager for the Coastal Ocean (HICO): Sensor and data processing overview  

Microsoft Academic Search

The Hyperspectral Imager for the Coastal Ocean (HICO) is a new hyperspectral sensor that will be housed on the International Space Station (ISS). The low-cost, rapid-development sensor was built by the Naval Research Laboratory (NRL). NRL is also responsible for mission planning and operational data processing for this new sensor. HICO is sponsored and funded by the Office of Naval

M. D. Lewis; R. W. Gould; R. A. Arnone; P. E. Lyon; P. M. Martinolich; R. Vaughan; A. Lawson; T. Scardino; W. Hou; W. Snyder; R. Lucke; M. Corson; M. Montes; C. Davis

2009-01-01

3

Hyperspectral Image Projector for Advanced Sensor Characterization  

Microsoft Academic Search

In this work, we describe radiometric platforms able to produce realistic spectral distributions and spatial scenes for the development of application-specific metrics to quantify the performance of sensors and systems. Using these platforms, sensor and system performance may be quantified in terms of the accuracy of measurements of standardized sets of complex source distributions. The same platforms can also serve

S. W. Brown; J. P. Rice; J. E. Neira; R. Bousquet; B. C. Johnson

2006-01-01

4

Methods for gas detection using stationary hyperspectral imaging sensors  

DOEpatents

According to one embodiment, a method comprises producing a first hyperspectral imaging (HSI) data cube of a location at a first time using data from a HSI sensor; producing a second HSI data cube of the same location at a second time using data from the HSI sensor; subtracting on a pixel-by-pixel basis the second HSI data cube from the first HSI data cube to produce a raw difference cube; calibrating the raw difference cube to produce a calibrated raw difference cube; selecting at least one desired spectral band based on a gas of interest; producing a detection image based on the at least one selected spectral band and the calibrated raw difference cube; examining the detection image to determine presence of the gas of interest; and outputting a result of the examination. Other methods, systems, and computer program products for detecting the presence of a gas are also described.

Conger, James L. (San Ramon, CA); Henderson, John R. (Castro Valley, CA)

2012-04-24

5

BAYESIAN FUSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES WITH UNKNOWN SENSOR SPECTRAL RESPONSE  

E-print Network

BAYESIAN FUSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES WITH UNKNOWN SENSOR SPECTRAL RESPONSE Qi-of-the-art fusion techniques. Index Terms-- Fusion, multispectral and hyperspectral images, spectral response, Bayesian estimation, Hamiltonian Monte Carlo. 1. INTRODUCTION Multi-resolution image fusion, also known

Dobigeon, Nicolas

6

Characterization and reduction of stochastic and periodic anomalies in a hyperspectral imaging sensor system  

Microsoft Academic Search

HYDICE, the HYperspectral Digital Imagery Collection Experiment, is an airborne hyperspectral imaging sensor operating in a pushbroom mode. HYDICE collects data simultaneously in 210 wavelength bands from 0.4 to 2.5 micrometers using a prism as the dispersing element. While the overall quality of HYDICE data is excellent, certain data stream anomalies have been identified, among which are a periodic offset

Bruce V. Shetler; Hugh H. Kieffer

1996-01-01

7

Performance modeling of hyperspectral imaging sensors for atmospheric studies  

Microsoft Academic Search

In this research project, we have developed a sensor model for the Navy's HYDICE system, using current engineering specifications and data from Hughes Danbury Optical Systems, the manufacturer. This sensor imaging model has been integrated into an end-to-end simulation system, Multispectral Image Simulator (MIS). Using MIS with the HYDICE model we have investigated Signal to Noise Ratios (SNR's) that might

Yudi Adityawarman; R. A. Schowengerdt

1994-01-01

8

Miniaturized handheld hyperspectral imager  

NASA Astrophysics Data System (ADS)

A miniaturized hyperspectral imager is enabled with image sensor integrated with dispersing elements in a very compact form factor, removing the need for expensive, moving, bulky and complex optics that have been used in conventional hyperspectral imagers for decades. The result is a handheld spectral imager that can be installed on miniature UAV drones or conveyor belts in production lines. Eventually, small handhelds can be adapted for use in outpatient medical clinics for point-of-care diagnostics and other in-field applications.

Wu, Huawen; Haibach, Frederick G.; Bergles, Eric; Qian, Jack; Zhang, Charlie; Yang, William

2014-05-01

9

Evaluation of onboard hyperspectral-image compression techniques for a parallel push-broom sensor  

SciTech Connect

A single hyperspectral imaging sensor can produce frames with spatially-continuous rows of differing, but adjacent, spectral wavelength. If the frame sample-rate of the sensor is such that subsequent hyperspectral frames are spatially shifted by one row, then the sensor can be thought of as a parallel (in wavelength) push-broom sensor. An examination of data compression techniques for such a sensor is presented. The compression techniques are intended to be implemented onboard a space-based platform and to have implementation speeds that match the date rate of the sensor. Data partitions examined extend from individually operating on a single hyperspectral frame to operating on a data cube comprising the two spatial axes and the spectral axis. Compression algorithms investigated utilize JPEG-based image compression, wavelet-based compression and differential pulse code modulation. Algorithm performance is quantitatively presented in terms of root-mean-squared error and root-mean-squared correlation coefficient error. Implementation issues are considered in algorithm development.

Briles, S.

1996-04-01

10

Performance modeling of hyperspectral imaging sensors for atmospheric studies  

NASA Astrophysics Data System (ADS)

In this research project, we have developed a sensor model for the Navy's HYDICE system, using current engineering specifications and data from Hughes Danbury Optical Systems, the manufacturer. This sensor imaging model has been integrated into an end-to-end simulation system, Multispectral Image Simulator (MIS). Using MIS with the HYDICE model we have investigated Signal to Noise Ratios (SNR's) that might be expected from HYDICE under low radiance conditions, such as images of coastal water areas. The results are presented in Section 4.1. We also used the Cuprite, Nevada, AVIRIS database developed earlier, for simulation of natural HYDICE imagery. This is presented in Section 4.2. Finally, we have also initiated investigation of large view angle effects on image contrast, using the Advanced Very High Resolution Radiometer (AVHRR) module in MIS since it allows a range of +55 deg in view angle cross-track. These simulation results are presented in Section 4.3.

Adityawarman, Yudi; Schowengerdt, R. A.

1994-09-01

11

MAP estimation for hyperspectral image resolution enhancement using an auxiliary sensor.  

PubMed

This paper presents a novel maximum a posteriori estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here, we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the "true" scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the airborne visible-infrared imaging spectrometer are presented to demonstrate the efficacy of the proposed estimator. PMID:15449580

Hardie, Russell C; Eismann, Michael T; Wilson, Gregory L

2004-09-01

12

Invariant Recognition in Hyperspectral Images  

Microsoft Academic Search

The spectral radiance measured for a material by an airborne hyperspectral sensor depends strongly on. The illumination environment and the atmospheric conditions. This dependence has limited the success of material identification algorithms that rely exclusively on the information contained in hyperspectral image data. In this paper we use a comprehensive physical model to show that the set of observed 0.4-2.5

Glenn Healey; David Slater

1999-01-01

13

Characterization and reduction of stochastic and periodic anomalies in a hyperspectral imaging sensor system  

NASA Astrophysics Data System (ADS)

HYDICE, the HYperspectral Digital Imagery Collection Experiment, is an airborne hyperspectral imaging sensor operating in a pushbroom mode. HYDICE collects data simultaneously in 210 wavelength bands from 0.4 to 2.5 micrometers using a prism as the dispersing element. While the overall quality of HYDICE data is excellent, certain data stream anomalies have been identified, among which are a periodic offset in DN level related to the operation of the system cryocooler and a quasi-random variation in the spectral alignment between the dispersed image and the focal plane. In this paper we report on an investigation into the above two effects and the development of algorithms and software to correct or minimize their impact in a production data processing system. We find the periodic variation to have unexpected time and band-dependent characteristics which argues against the possibility of correction in post- processing, but to be relatively insensitive to signal and consequently of low impact on the operation of the system. We investigate spectral jitter through an algorithm which performs a least squares fit to several atmospheric spectral features to characterize both the time-dependent jitter motion and systematic spectral mis-registration. This method is also implemented to correct the anomalies in the production data stream. A comprehensive set of hyperspectral sensor calibration and correction algorithm is also presented.

Shetler, Bruce V.; Kieffer, Hugh H.

1996-11-01

14

Hyperspectral Systems Increase Imaging Capabilities  

NASA Technical Reports Server (NTRS)

In 1983, NASA started developing hyperspectral systems to image in the ultraviolet and infrared wavelengths. In 2001, the first on-orbit hyperspectral imager, Hyperion, was launched aboard the Earth Observing-1 spacecraft. Based on the hyperspectral imaging sensors used in Earth observation satellites, Stennis Space Center engineers and Institute for Technology Development researchers collaborated on a new design that was smaller and used an improved scanner. Featured in Spinoff 2007, the technology is now exclusively licensed by Themis Vision Systems LLC, of Richmond, Virginia, and is widely used in medical and life sciences, defense and security, forensics, and microscopy.

2010-01-01

15

Hyperspectral imaging sensor array based on diffractively driving infrared beams with chosen wavelength into designated subsensors  

NASA Astrophysics Data System (ADS)

In this paper, an integrated hyperspectral imaging sensor array technology by using arrayed diffractive micro-optics elements for driving infrared beams with chosen wavelength into designated subsensors is proposed. The diffractive optical element, which can be treated as a functioned microlens here, collect the incident Gaussian beam or other types of infrared beams out-from targets and then concentrate the incident light into desired monochromatic point pattern or arbitrary distinct hyperspectral image at the imaging plane based on phase transformation and diffraction propagation process. For the incident infrared beams with different wavelengths, the arrayed diffractive micro-optics elements is designed based on the diffractive integral theory, and the weighted iterative phase retrieval algorithm is modeled so as to obtain the needed phase distribution, and therefore the frequency spectrum of the incident beams can be separated locally in different locations over the focal plane according to designated wavelength. We can then achieve beam-splitting imaging by placing sensor array (4×4 pixels per subsensor) on the focal plane at locations that correspond to different wavelengths. Simulation results demonstrate that the designed elements can successfully implement both the functions of demultiplexing different wavelength beams and focusing each component at a pre-designated position simultaneously.

Qu, Yong; Zhang, Xinyu; Sang, Hongshi; Zhang, Tianxu; Xie, Changsheng

2013-10-01

16

Hyperspectral Imager Characterization and Calibration  

Microsoft Academic Search

Current radiometric calibration standards, specifically blackbody and lamp-based optical radiation sources, produce spatially, spectrally, and temporally simple scenes. Hyperspectral imaging instruments, which in-practice view spatially, spectrally, and temporally complex scenes, would benefit from advanced radiometric artifacts that more closely resemble scenes the sensor will ultimately view. Techniques and artifacts that advance sensor characterization and algorithms that reduce the impact of

John T. Woodward; Steven W. Brown; Allan W. Smith; Keith R. Lykke

2009-01-01

17

Hyperspectral Image Compression  

Microsoft Academic Search

Hyperspectral images gathered by satellites or aerial means provide a vast amount of data for geophysicists. A few applications include the exploration of minerals, research of land pollution, and military surveillance. NASA and other agencies are producing gigabytes of hyperspectral images which need to be transmitted and stored daily. As these images require high compression rates and preservation of data

Stephanie Wright; Jason Ashbach

2008-01-01

18

Dual-coded compressive hyperspectral imaging.  

PubMed

This Letter presents a new snapshot approach to hyperspectral imaging via dual-optical coding and compressive computational reconstruction. We demonstrate that two high-speed spatial light modulators, located conjugate to the image and spectral plane, respectively, can code the hyperspectral datacube into a single sensor image such that the high-resolution signal can be recovered in postprocessing. We show various applications by designing different optical modulation functions, including programmable spatially varying color filtering, multiplexed hyperspectral imaging, and high-resolution compressive hyperspectral imaging. PMID:24686670

Lin, Xing; Wetzstein, Gordon; Liu, Yebin; Dai, Qionghai

2014-04-01

19

Satellite Hyperspectral Imaging Simulation  

NASA Technical Reports Server (NTRS)

Simulation of generic pushbroom satellite hyperspectral sensors have been performed to evaluate the potential performance and validation techniques for satellite systems such as COIS(NEMO), Warfighter-1(OrbView-4) and Hyperion(EO-1). The simulations start with a generation of synthetic scenes from material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response using MODTRAN 4 radiance and transmissions calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and etectorr/electronics noise are added to the simulated images, which are also finally quantized to the sensor bit resolution. Studied scenes include bridges and straight roads used for evaluation of sensor spatial resolution, as well as fields of minerals, vegetation and manmade materials used for evaluation of sensor radiometric response and sensitivity. The scenes are simulated with various seasons and weather conditions. Signal-to-noise ratios and expected performance are estimated for typical satellite system specifications and are discussed for all the scenes.

Zanoni, Vicki; Stanley, Tom; Blonski, Slawomir; Cao, Changyong; Gasser, Jerry; Ryan, Robert

1999-01-01

20

Imaging Solar-Induced Chlorophyll Fluorescence with Hyperspectral Sensor in Situ  

NASA Astrophysics Data System (ADS)

Chlorophyll fluorescence is related to photosynthesis and it has become common practice to use chlorophyll fluorescence in plant ecophysiology studies in recent years. Active fluorescence method, which needs to generate laser to induce chlorophyll fluorescence, seems unsafe and is impossible to use on a satellite platform over 400 kilometers away in space. Therefore, solar-induced chlorophyll fluorescence (SIF) is an ideal substitution and a potential way to study vegetation condition. Imaging SIF can be a complement to the traditional SIF study with non-imaging spectrometer in the field experiments. With the fluorescence images, soil and leaves in different conditions can be distinguished easily and appropriate pixels can be selected in calculating SIF. The goal of this study is to use an imaging hyperspectral sensor companioned with a multi-angle observe platform to acquire vegetation apparent reflectance in order to image vegetation SIF in situ. The hyperspectral sensor has a 3.3 nm spectral resolution and less than 1 nm spectral sampling interval. SIF is extracted using Fraunhofer Line Depth (FLD) principle. Three FLD methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD) are used in both two major Fraunhofer bands, 687 nm and 760 nm. The results of this study show that, although radiance and reflectance of leaf varies, the peak of reflectance in 760 nm is obvious and stable. Around 687 nm, a peak of reflectance also occurs, but it is not obvious and the position varies. Furthermore, all of the three FLD methods get clear SIF images of wheat in 760 nm, while images calculated around 687 nm are comparatively vague. It seems that the depth and width of Fraunhofer line in 687 nm are so small that a sensor with higher spectral resolution should be used. In addition, using sFLD in 760 nm can get the clearest SIF images among all the methods. This is perhaps because of the overestimated SIF of sFLD method and, as a consequence, the contrast caused by SIF is amplified. Because more light was absorbed by upper leaves under light, SIF of upper leaves is bigger than fluorescence of lower leaves. Several new leaves and old leaves under light were selected and analyzed with statistical methods. The result shows that standard deviations in 760 nm of the three FLD methods are less than those in 687 nm and the results in 760 nm are more reasonable. Additionally, different compositions of the bands selected for the FLDs can also affect the results. When selecting the bands located out of the Fraunhofer line (?out), two principles should be considered. On one hand, the band selected should be kept in a relative long distance to the closest Fraunhofer line to prevent its effect. On the other hand, the presumptions of FLD methods would be correct only if the selected ?out is close enough to the band existed within the Fraunhofer line. In this study, for each FLD methods, the same composition of bands was selected for all the pixels and the differences among pixels were ignored. However, the shapes of reflectance spectrum of different pixels are actually different in details. It is impossible to guarantee that appropriate band composition was applied to each pixel. This can also affect the final SIF images. The way to select the optimal band composition should be studied in the future.

Wang, R.; Liu, Z.

2012-12-01

21

Hyperspectral imaging using rotational spectrotomography  

Microsoft Academic Search

Hyperspectral imaging can be a powerful tool for remote sensing of geologic, biologic, and ocean surfaces of atmospheres, and of rocket plumes. A hyperspectral imager provides a 3D (two spatial and one spectral) description from a sequence of 2D images. Common hyperspectral approaches using narrow band filters or imaging spectrometers are inefficient because photons outside the filter passband or the

Paul A. Bernhardt; John A. Antoniades

1995-01-01

22

Unsupervised hyperspectral image classification  

NASA Astrophysics Data System (ADS)

Two major issues encountered in unsupervised hyperspectral image classification are (1) how to determine the number of spectral classes in the image and (2) how to find training samples that well represent each of spectral classes without prior knowledge. A recently developed concept, Virtual dimensionality (VD) is used to estimate the number of spectral classes of interest in the image data. This paper proposes an effective algorithm to generate an appropriate training set via a recently developed Prioritized Independent Component Analysis (PICA). Two sets of hyperspectral data, Airborne Visible Infrared Imaging Spectrometer (AVIRIS) Cuprite data and HYperspectral Digital Image Collection Experiment (HYDICE) data are used for experiments and performance analysis for the proposed method.

Jiao, Xiaoli; Chang, Chein-I.

2007-09-01

23

Uncooled long-wave infrared hyperspectral imaging  

NASA Technical Reports Server (NTRS)

A long-wave infrared hyperspectral sensor device employs a combination of an interferometer with an uncooled microbolometer array camera to produce hyperspectral images without the use of bulky, power-hungry motorized components, making it suitable for UAV vehicles, small mobile platforms, or in extraterrestrial environments. The sensor device can provide signal-to-noise ratios near 200 for ambient temperature scenes with 33 wavenumber resolution at a frame rate of 50 Hz, with higher results indicated by ongoing component improvements.

Lucey, Paul G. (Inventor)

2006-01-01

24

Quantitative Hyperspectral Reflectance Imaging  

Microsoft Academic Search

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultura l heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of enviro nmental

Marvin E. Klein; Bernard J. Aalderink; Roberto Padoan; Gerrit de Bruin; A. G. Steemers

2008-01-01

25

Quantitative Hyperspectral Reflectance Imaging  

PubMed Central

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms.

Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

2008-01-01

26

Planetary Hyperspectral Imager (PHI)  

NASA Technical Reports Server (NTRS)

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.

Silvergate, Peter

1996-01-01

27

Hyperspectral imaging applied to forensic medicine  

Microsoft Academic Search

Remote sensing techniques now include the use of hyperspectral infrared imaging sensors covering the mid-and- long wave regions of the spectrum. They have found use in military surveillance applications due to their capability for detection and classification of a large variety of both naturally occurring and man-made substances. The images they produce reveal the spatial distributions of spectral patterns that

Donald B. Malkoff; William R. Oliver

2000-01-01

28

Simulation of Hyperspectral Images  

NASA Technical Reports Server (NTRS)

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.

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

2004-01-01

29

Novel hyperspectral imager for lightweight UAVs  

NASA Astrophysics Data System (ADS)

VTT Technical Research Centre of Finland has developed a new miniaturized staring hyperspectral imager with a weight of 350 g making the system compatible with lightweight UAS platforms. The instrument is able to record 2D spatial images at the selected wavelength bands simultaneously. The concept of the hyperspectral imager has been published in the SPIE Proc. 74741. The operational wavelength range of the imager can be tuned in the range 400 - 1100 nm and spectral resolution is in the range 5 - 10 nm @ FWHM. Presently the spatial resolution is 480 × 750 pixels but it can be increased simply by changing the image sensor. The field of view of the system is 20 × 30 degrees and ground pixel size at 100 m flying altitude is around 7.5 cm. The system contains batteries, image acquisition control system and memory for the image data. It can operate autonomously recording hyperspectral data cubes continuously or controlled by the autopilot system of the UAS. The new hyperspectral imager prototype was first tried in co-operation with the Flemish Institute for Technological Research (VITO) on their UAS helicopter. The instrument was configured for the spectral range 500 - 900 nm selected for the vegetation and natural water monitoring applications. The design of the UAS hyperspectral imager and its characterization results together with the analysis of the spectral data from first test flights will be presented.

Saari, Heikki; Aallos, Ville-Veikko; Holmlund, Christer; Mäkynen, Jussi; Delauré, Bavo; Nackaerts, Kris; Michiels, Bart

2010-04-01

30

Remote Sensing of Selected Water-Quality Indicators with the Hyperspectral Imager for the Coastal Ocean (HICO) Sensor  

EPA Science Inventory

The Hyperspectral Imager for the Coastal Ocean (HICO) offers the coastal environmental monitoring community an unprecedented opportunity to observe changes in coastal and estuarine water quality across a range of spatial scales not feasible with traditional field-based monitoring...

31

Aerospace wetland monitoring by hyperspectral imaging sensors: a case study in the coastal zone of San Rossore Natural Park.  

PubMed

The San Rossore Natural Park, located on the Tuscany (Italy) coast, has been utilized over the last 10 years for many remote sensing campaigns devoted to coastal zone monitoring. A wet area is located in the south-west part of the Natural Park and it is characterized by a system of ponds and dunes formed by sediment deposition occurring at the Arno River estuary. The considerable amount of collected data has permitted us to investigate the evolution of wetland spreading and land coverage as well as to retrieve relevant biogeochemical parameters, e.g. green biomass, from remote sensing images and products. This analysis has proved that the monitoring of coastal wetlands, characterized by shallow waters, moor and dunes, demands dedicated aerospace sensors with high spatial and spectral resolution. The outcomes of the processing of images gathered during several remote sensing campaigns by airborne and spaceborne hyperspectral sensors are presented and discussed. A particular effort has been devoted to sensor response calibration and data validation due to the complex heterogeneity of the observed natural surfaces. PMID:18423842

Barducci, Alessandro; Guzzi, Donatella; Marcoionni, Paolo; Pippi, Ivan

2009-05-01

32

Hyperspectral Imager-Tracker  

NASA Technical Reports Server (NTRS)

The Hyperspectral Imager-Tracker (HIT) is a technique for visualization and tracking of low-contrast, fast-moving objects. The HIT architecture is based on an innovative and only recently developed concept in imaging optics. This innovative architecture will give the Light Prescriptions Innovators (LPI) HIT the possibility of simultaneously collecting the spectral band images (hyperspectral cube), IR images, and to operate with high-light-gathering power and high magnification for multiple fast- moving objects. Adaptive Spectral Filtering algorithms will efficiently increase the contrast of low-contrast scenes. The most hazardous parts of a space mission are the first stage of a launch and the last 10 kilometers of the landing trajectory. In general, a close watch on spacecraft operation is required at distances up to 70 km. Tracking at such distances is usually associated with the use of radar, but its milliradian angular resolution translates to 100- m spatial resolution at 70-km distance. With sufficient power, radar can track a spacecraft as a whole object, but will not provide detail in the case of an accident, particularly for small debris in the onemeter range, which can only be achieved optically. It will be important to track the debris, which could disintegrate further into more debris, all the way to the ground. Such fragmentation could cause ballistic predictions, based on observations using high-resolution but narrow-field optics for only the first few seconds of the event, to be inaccurate. No optical imager architecture exists to satisfy NASA requirements. The HIT was developed for space vehicle tracking, in-flight inspection, and in the case of an accident, a detailed recording of the event. The system is a combination of five subsystems: (1) a roving fovea telescope with a wide 30 field of regard; (2) narrow, high-resolution fovea field optics; (3) a Coude optics system for telescope output beam stabilization; (4) a hyperspectral-mutispectral imaging assembly; and (5) image analysis software with effective adaptive spectral filtering algorithm for real-time contrast enhancement.

Agurok, Llya

2013-01-01

33

Continued development of a portable widefield hyperspectral imaging (HSI) sensor for standoff detection of explosive, chemical, and narcotic residues  

NASA Astrophysics Data System (ADS)

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 investigators in locating bone remains in a cluttered background environment.

Nelson, Matthew P.; Gardner, Charles W.; Klueva, Oksana; Tomas, David

2014-05-01

34

Super-resolution reconstruction of hyperspectral images.  

PubMed

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions. PMID:16279185

Akgun, Toygar; Altunbasak, Yucel; Mersereau, Russell M

2005-11-01

35

Perceptual-based image fusion for hyperspectral data  

Microsoft Academic Search

Three hierarchical multiresolution image fusion techniques are implemented and tested using image data from the Airborne Visual\\/Infrared Imaging Spectrometer (AVIRIS) hyperspectral sensor. The methods presented focus on combining multiple images from the AVIRIS sensor into a smaller subset of images white maintaining the visual information necessary for human analysis. Two of the techniques are published algorithms that were originally designed

Terry A. Wilson; Steven K. Rogers; Matthew Kabrisky

1997-01-01

36

Parametric adaptive signal detection for hyperspectral imaging  

Microsoft Academic Search

Hyperspectral imaging (HSI) sensors can provide very fine spectral resolution that allows remote identification of ground objects smaller than a full pixel in an HSI image. Traditional approaches to the so-called subpixel target signal detection problem are training inefficient due to the need for an estimate of a large-size covariance matrix of the background from target-free training pixels. This imposes

Hongbin Li; James H. Michels

2006-01-01

37

SPARSITY AND STRUCTURE IN HYPERSPECTRAL IMAGING: SENSING, RECONSTRUCTION, AND TARGET DETECTION  

E-print Network

of in- terest. Hyperspectral images consist of spatial maps of light intensity variation across a large sparse (low- dimensional) image models are enabling sensor designers to tackle many of the above a hyperspectral datacube f Rdx�dy�d , where fi,j, is the intensity of light in the hyperspectral image

38

Hyperspectral Image Analysis for Skin Tumor Detection  

NASA Astrophysics Data System (ADS)

This chapter presents hyperspectral imaging of fluorescence for nonin-vasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect two-dimensional (2D) image data of an object in a number of narrow, adjacent spectral bands. This high-resolution measurement of spectral information reveals a continuous emission spectrum for each image pixel useful for skin tumor detection. The hyperspectral image data used in this study are fluorescence intensities of a mouse sample consisting of 21 spectral bands in the visible spectrum of wavelengths ranging from 440 to 640 nm. Fluorescence signals are measured using a laser excitation source with the center wavelength of 337 nm. An acousto-optic tunable filter is used to capture individual spectral band images at a 10-nm resolution. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the offsets caused during the image capture procedure. The support vector machines with polynomial kernel functions provide decision boundaries with a maximum separation margin to classify malignant tumor and normal tissue from the observed fluorescence spectral signatures for skin tumor detection.

Kong, Seong G.; Park, Lae-Jeong

39

Vicarious calibration of airborne hyperspectral sensors in operational environments  

Microsoft Academic Search

A reflectance-based vicarious calibration (RBVC) method has been used to correct the radiometric coefficients for hyperspectral data obtained with the Probe 1 sensor over the Raglan region of northern Quebec, and to perform a radiance renormalisation for compact airborne spectrographic imager (casi) data obtained over Goose Bay, Labrador. It relies on the simultaneous acquisition of ground-based reflectance spectra for at

Jeff Secker; Karl Staenz; Robert P Gauthier; Paul Budkewitsch

2001-01-01

40

Hyperspectral monitoring of chemically sensitive plant sensors  

NASA Astrophysics Data System (ADS)

Current events clearly demonstrate that chemical and biological threats against the public are very real. Automated detection of chemical threats is a necessary component of a system that provides early warning of an attack. Plant biologists are currently developing genetically engineered plants that de-green in the presence of explosives (i.e. TNT) in their environment. The objectives of this thesis are to study the spectral reflectance phenomenology of the plant sensors and to propose requirements for an operational monitoring system using spectral imaging technology. Hyperspectral data were collected under laboratory conditions to determine the key spectral regions in the reflectance spectra associated with the de-greening phenomenon. The collected reflectance spectra were then entered into simulated imagery created using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. System performance was studied as a function of pixel size, radiometric noise, spectral waveband dependence and spectral resolution. It was found that a framing array sensor with 40nm wide bands centered at 645 nm, 690 nm, 875 nm, a ground sample distance of 11cm or smaller, and an signal to noise ratio of 250 or better would be sufficient for monitoring bio-sensors deployed under conditions similar to those simulated for this work.

Simmons, Danielle A.

41

Combined hyperspatial and hyperspectral imaging spectrometer concept  

NASA Technical Reports Server (NTRS)

There is a user need for increasing spatial and spectral resolution in Earth Observation (EO) optical instrumentation. Higher spectral resolution will be achieved by the introduction of spaceborne imaging spectrometers. Higher spatial resolutions of 1 - 3m will be achieved also, but at the expense of sensor redesign, higher communications bandwidth, high data processing volumes, and therefore, at the risk of time delays due to large volume data-handling bottlenecks. This paper discusses a design concept whereby the hyperspectral properties of a spaceborne imaging spectrometer can be used to increase the image spatial resolution, without such adverse cost impact.

Burke, Ian; Zwick, Harold

1995-01-01

42

Curvelet based hyperspectral image fusion  

NASA Astrophysics Data System (ADS)

Hyperspectral imagery typically possesses high spectral resolution but low spatial resolution. One way to enhance the spatial resolution of a hyperspectral image is to fuse its spectral information and the spatial information of another high resolution image. In this paper, we propose a novel image fusion strategy for hyperspectral image and high spatial resolution panchromatic image, which is based on the curvelet transform. Firstly, determine a synthesized image with the specified RGB bands of the original hyperspectral images according to the optimal index factor (OIF) model. Then use the IHS transform to extract the intensity component of the synthesized image. After that, the histogram matching is performed between the intensity component and the panchromatic image. Thirdly, the curvelet transform is applied to decompose the two source images (the intensity component and the panchromatic image) in different scales and directions. Different fusion strategies are applied to coefficients in various scales and directions. Finally, the fused image is achieved by the inverse IHS transform. The experimental result shows that the proposed method has a superior performance. Comparing with the traditional methods such as the PCA transform, wavelet-based or pyramid-based methods and the multi-resolution fusion methods (shearlet or contourlet decomposition), the fused image achieves the highest entropy index and average gradient value. While providing a better human visual quality, a good correlation coefficient index indicates that the fused image keeps good spectral information. Both visual quality and objective evaluation criteria demonstrate that this method can well preserve the spatial quality and the spectral characteristics.

Wang, Sha; Feng, Hua-jun; Xu, Zhi-hai; Li, Qi; Chen, Yue-ting

2013-08-01

43

Hyperspectral sensor HSC3000 for nano-satellite TAIKI  

NASA Astrophysics Data System (ADS)

Hokkaido Satellite Project was kicked off at April in 2003 by the volunteer group that consists of students, researchers and engineers in order to demonstrate the space business models using nanosatellites of 15kg/50kg in Japan. The Hokkaido satellite named "TAIKI" is characterized by a hyperspectral sensor with a VNIR (visible and near infrared range) and a laser communication instrument for data downlink communication. At the beginning of 2008 we started to develop a space qualified hyperspectral sensor HSC3000 based on the optical design of HSC1700. Last year we developed the hyperspectral camera HSC-3000 BBM funded by New Energy Development Organization (NEDO) as the position of the breadboard model of HSC3000. HSC-3000 BBM is specified by the spectral range from 400nm to 1000nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 10 bits and data transfer rate of 200 f/s. By averaging outputs of several adjacent pixels to increase S/N, HSC3000 of the spaceborne is targeted at the specification of 30 m spatial resolution, 61 spectral bands, 10 nm spectral resolution and S/N300. Spin-off technology of the hyperspectral imager is also introduced. We have succeeded to develop a hyperspectral camera as the spin-off product named HSC1700 which installs both the hyperspectral sensor unit and a scanning mechanism inside. The HSC1700 is specified by the spectral range from 400nm to 800nm, 81 spectral bands, image size of 640 x 480 pixels, radiometric resolution of 8 bits and data transfer rate of 30 f/s.

Satori, S.; Aoyanagi, Y.; Hara, U.; Mitsuhashi, R.; Takeuchi, Y.

2008-12-01

44

Residual striping reduction in hyperspectral images  

Microsoft Academic Search

In this paper a new algorithm for striping noise reduction in hyperspectral images is proposed. Signal dependent striping noise is reduced by exploiting the high degree of spectral correlation of the useful signal in hyperspectral data. The algorithm does not require the human intervention nor introduces significant radiometric distortions on the useful signal. Results obtained on simulated and real hyperspectral

N. Acito; M. Diani; G. Corsini

2011-01-01

45

The civil air patrol ARCHER hyperspectral sensor system  

NASA Astrophysics Data System (ADS)

The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a fleet of Gippsland GA-8 aircraft, and will position CAP to gain realworld mission experience with the application of hyperspectral sensor and processing technology to search and rescue. The ARCHER system design, data processing, and operational concept leverage several years of investment in hyperspectral technology research and airborne system demonstration programs by the Naval Research Laboratory (NRL) and Air Force Research Laboratory (AFRL). Each ARCHER system consists of a NovaSol-designed, pushbroom, visible/near-infrared (VNIR) hyperspectral imaging (HSI) sensor, a co-boresighted visible panchromatic high-resolution imaging (HRI) sensor, and a CMIGITS-III GPS/INS unit in an integrated sensor assembly mounted inside the GA-8 cabin. ARCHER incorporates an on-board data processing system developed by Space Computer Corporation (SCC) to perform numerous real-time processing functions including data acquisition and recording, raw data correction, target detection, cueing and chipping, precision image geo-registration, and display and dissemination of image products and target cue information. A ground processing station is provided for post-flight data playback and analysis. This paper describes the requirements and architecture of the ARCHER system, including design, components, software, interfaces, and displays. Key sensor performance characteristics and real-time data processing features are discussed in detail. The use of the system for detecting and geo-locating ground targets in real-time is demonstrated using test data collected in Southern California in the fall of 2004.

Stevenson, Brian; O'Connor, Rory; Kendall, William; Stocker, Alan; Schaff, William; Holasek, Rick; Even, Detlev; Alexa, Drew; Salvador, John; Eismann, Michael; Mack, Robert; Kee, Pat; Harris, Steve; Karch, Barry; Kershenstein, John

2005-05-01

46

Hyperspectral imaging of bruised skin  

NASA Astrophysics Data System (ADS)

Bruises can be important evidence in legal medicine, for example in cases of child abuse. Optical techniques can be used to discriminate and quantify the chromophores present in bruised skin, and thereby aid dating of an injury. However, spectroscopic techniques provide only average chromophore concentrations for the sampled volume, and contain little information about the spatial chromophore distribution in the bruise. Hyperspectral imaging combines the power of imaging and spectroscopy, and can provide both spectroscopic and spatial information. In this study a hyperspectral imaging system developed by Norsk Elektro Optikk AS was used to measure the temporal development of bruised skin in a human volunteer. The bruises were inflicted by paintball bullets. The wavelength ranges used were 400 - 1000 nm (VNIR) and 900 - 1700 nm (SWIR), and the spectral sampling intervals were 3.7 and 5 nm, respectively. Preliminary results show good spatial discrimination of the bruised areas compared to normal skin. Development of a white spot can be seen in the central zone of the bruises. This central white zone was found to resemble the shape of the object hitting the skin, and is believed to develop in areas where the impact caused vessel damage. These results show that hyperspectral imaging is a promising technique to evaluate the temporal and spatial development of bruises on human skin.

Randeberg, Lise L.; Baarstad, Ivar; Løke, Trond; Kaspersen, Peter; Svaasand, Lars O.

2006-02-01

47

HYPERSPECTRAL IMAGING PHENOMENOLOGY OF GENETICALLY ENGINEERED PLANT SENTINELS  

E-print Network

HYPERSPECTRAL IMAGING PHENOMENOLOGY OF GENETICALLY ENGINEERED PLANT SENTINELS D. Simmonsa , J engineered plant sentinels as measured by spectral imaging remote sensors is investigated. Plant sentinels of a chemical inducer such as hazardous chemicals or environmental pollutants. This work investigates the use

Kerekes, John

48

Data characterization for hyperspectral image compression  

Microsoft Academic Search

By their very nature, hyperspectral imagers collect much more data per pixel than more traditional imaging systems. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and\\/or data compression will be very important. In two recent government-funded studies (completed in Dec. 1996), Kodak developed two preliminary compression options for hyperspectral imaging. As part of

Rulon E. Simmons; Bernard V. Brower; John R. Schott

1997-01-01

49

Hyperspectral imaging applied to forensic medicine  

NASA Astrophysics Data System (ADS)

Remote sensing techniques now include the use of hyperspectral infrared imaging sensors covering the mid-and- long wave regions of the spectrum. They have found use in military surveillance applications due to their capability for detection and classification of a large variety of both naturally occurring and man-made substances. The images they produce reveal the spatial distributions of spectral patterns that reflect differences in material temperature, texture, and composition. A program is proposed for demonstrating proof-of-concept in using a portable sensor of this type for crime scene investigations. It is anticipated to be useful in discovering and documenting the affects of trauma and/or naturally occurring illnesses, as well as detecting blood spills, tire patterns, toxic chemicals, skin injection sites, blunt traumas to the body, fluid accumulations, congenital biochemical defects, and a host of other conditions and diseases. This approach can significantly enhance capabilities for determining the circumstances of death. Potential users include law enforcement organizations (police, FBI, CIA), medical examiners, hospitals/emergency rooms, and medical laboratories. Many of the image analysis algorithms already in place for hyperspectral remote sensing and crime scene investigations can be applied to the interpretation of data obtained in this program.

Malkoff, Donald B.; Oliver, William R.

2000-03-01

50

Hyperspectral Image Classification using a Self-Organizing Map  

NASA Technical Reports Server (NTRS)

The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Martinez, P.; Gualtieri, J. A.; Aguilar, P. L.; Perez, R. M.; Linaje, M.; Preciado, J. C.; Plaza, A.

2001-01-01

51

Hyperspectral imaging of an intercoastal waterway  

Microsoft Academic Search

This paper demonstrates the characterization of the water properties, bathymetry, and bottom type of the Indian River Lagoon (IRL) on the eastern coast of Florida using hyperspectral imagery. Images of this region were collected from an aircraft in July 2004 using the Portable Hyperspectral Imager for Low Light Spectroscopy (PHILLS). PHILLS is a Visible Near InfraRed (VNIR) spectrometer that was

Jeffrey H. Bowles; Shelia J. Maness; Wei Chen; Curtiss O. Davis; Tim F. Donato; David B. Gillis; Daniel Korwan; Gia Lamela; Marcos J. Montes; W. Joseph Rhea; William A. Snyder

2005-01-01

52

Hyperspectral Imaging of human arm  

NASA Technical Reports Server (NTRS)

ProVision Technologies, a NASA research partnership center at Sternis Space Center in Mississippi, has developed a new hyperspectral imaging (HSI) system that is much smaller than the original large units used aboard remote sensing aircraft and satellites. The new apparatus is about the size of a breadbox. Health-related applications of HSI include non-invasive analysis of human skin to characterize wounds and wound healing rates (especially important for space travelers who heal more slowly), determining if burns are first-, second-, or third degree (rather than painful punch biopsies). The work is sponsored under NASA's Space Product Development (SPD) program.

2003-01-01

53

Common hyperspectral image database design  

NASA Astrophysics Data System (ADS)

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.

Tian, Lixun; Liao, Ningfang; Chai, Ali

2009-11-01

54

Image analysis of hyperspectral and multispectral data using projection pursuit  

Microsoft Academic Search

Given recent advancements of modern hyperspectral (HS) sensors, the potential for information extraction has increased drastically given the continual improvements in spatial and spectral resolution. As a result, more sophisticated feature extraction and target detection (TD) algorithms are needed to improve the performance of the image analyst, whether computer-based or human. In this paper, a novel TD algorithm based on

Nilofar Azizi; Julian Meng

2008-01-01

55

Parametric adaptive modeling and detection for hyperspectral imaging  

Microsoft Academic Search

Hyperspectral imaging (HSI) sensors can provide very fine spectral resolution that allows remote identification of ground objects smaller than a full pixel. Traditional approaches to the so-called subpixel target signal detection problem involve the estimation of the sample covariance matrix of the background from target-free training pixels. This entails a large training requirement and high complexity. In this paper, we

Hongbin Li; James H. Michels

2004-01-01

56

Hyperspectral Imaging or Victim Detection with Rescue Robots  

Microsoft Academic Search

The main task of rescue robots is to locate victims after a disaster such as an earthquake. For this task sensor data is used to localize the robots in their environment, build maps, and mark the victims in the maps. Usually, thermal and color cameras, monitored by a human operator, are used for the detection. Hyperspectral imaging techniques are today

Marina Trierscheid; Johannes Pellenz; Dietrich Paulus; D. Balthasar

2008-01-01

57

Data characterization for hyperspectral image compression  

NASA Astrophysics Data System (ADS)

By their very nature, hyperspectral imagers collect much more data per pixel than more traditional imaging systems. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very important. In two recent government-funded studies (completed in Dec. 1996), Kodak developed two preliminary compression options for hyperspectral imaging. As part of these studies, the band-to- band data correlation structures for both AVIRIS and HYDICE hyperspectral imaging systems were evaluated. Some surprising results were noted that have important implications to system designers.

Simmons, Rulon E.; Brower, Bernard V.; Schott, John R.

1997-09-01

58

Advanced Airborne Hyperspectral Imaging System (AAHIS)  

NASA Astrophysics Data System (ADS)

The design, operation, and performance of the fourth generation of Science and Technology International's Advanced Airborne Hyperspectral Imaging Sensors (AAHIS) are described. These imaging spectrometers have a variable bandwidth ranging from 390-840 nm. A three-axis image stabilization provides spatially and spectrally coherent imagery by damping most of the airborne platform's random motion. A wide 40-degree field of view coupled with sub-pixel detection allows for a large area coverage rate. A software controlled variable aperture, spectral shaping filters, and high quantum efficiency, back-illuminated CCD's contribute to the excellent sensitivity of the sensors. AAHIS sensors have been operated on a variety of fixed and rotary wing platforms, achieving ground-sampling distances ranging from 6.5 cm to 2 m. While these sensors have been primarily designed for use over littoral zones, they are able to operate over both land and water. AAHIS has been used for detecting and locating submarines, mines, tanks, divers, camouflage and disturbed earth. Civilian applications include search and rescue on land and at sea, agricultural analysis, environmental time-series, coral reef assessment, effluent plume detection, coastal mapping, damage assessment, and seasonal whale population monitoring

Topping, Miles Q.; Pfeiffer, Joel E.; Sparks, Andrew W.; Jim, Kevin T. C.; Yoon, Dugan

2002-11-01

59

HYDICE: an airborne system for hyperspectral imaging  

Microsoft Academic Search

HYDICE (the Hyperspectral Digital Imagery Collection Experiment) is a program to build and operate an advanced airborne imaging spectrometer. Scheduled to be operating in 1994, it will provide high quality hyperspectral data for use by a number of US civil agencies in determining its utility for a wide range of applications, as well as in support of basic research. The

Lee J. Rickard; Robert W. Basedow; Edward F. Zalewski; Peter R. Silverglate; Mark Landers

1993-01-01

60

Progressive band processing for hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging has emerged as an image processing technique in many applications. The reason that hyperspectral data is called hyperspectral is mainly because the massive amount of information provided by the hundreds of spectral bands that can be used for data analysis. However, due to very high band-to-band correlation much information may be also redundant. Consequently, how to effectively and best utilize such rich spectral information becomes very challenging. One general approach is data dimensionality reduction which can be performed by data compression techniques, such as data transforms, and data reduction techniques, such as band selection. This dissertation presents a new area in hyperspectral imaging, to be called progressive hyperspectral imaging, which has not been explored in the past. Specifically, it derives a new theory, called Progressive Band Processing (PBP) of hyperspectral data that can significantly reduce computing time and can also be realized in real-time. It is particularly suited for application areas such as hyperspectral data communications and transmission where data can be communicated and transmitted progressively through spectral or satellite channels with limited data storage. Most importantly, PBP allows users to screen preliminary results before deciding to continue with processing the complete data set. These advantages benefit users of hyperspectral data by reducing processing time and increasing the timeliness of crucial decisions made based on the data such as identifying key intelligence information when a required response time is short.

Schultz, Robert C.

61

A parallel unmixing algorithm for hyperspectral images  

Microsoft Academic Search

We present a new algorithm for feature extraction in hyperspectral images based on source separation and parallel computing. In source separation, given a linear mixture of sources, the goal is to recover the components by producing an unmixing matrix. In hyperspectral imagery, the mixing transform and the separated components can be associated with endmembers and their abundances. Source separation based

Stefan A. Robila; Lukasz G. Maciak

62

Hyperspectral sensors and the conservation of monumental buildings  

NASA Astrophysics Data System (ADS)

The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties including moisture, organic content and salinity (2). Among the existing VNIR techniques (Laboratory Spectroscopy - LS, Portable Spectroscopy - PS and Imaging Spectroscopy - IS), PS and IS can play a crucial role in the characterization of components of exposed stone surfaces. In particular, the Imaging Spectroscopic (remote sensing), which uses sensors placed both on land or airborne, may contribute to the monitoring of large areas in consideration of its ability to produce large areal maps at relatively low costs. In this presentation the application of hyperspectral instruments (mainly PS and IS, not applied before in the field of monumental building diagnostic) to quantify the degradation of carbonate surfaces will be discussed. In particular, considering gypsum as the precursor symptom of damage, many factors which may affect the estimation of gypsum content on the surface will be taken into consideration. Two hyperspectral sensors will be considered: 1) A portable radiometer (ASD-FieldSpec FP Pro spectroradiometer), which continuously acquires punctual reflectance spectra in the range 350-2500 nm, both in natural light conditions and by a contact probe (fixed geometry of shot). This instrument is used on field for the identification of different materials, as well as for the definition of maps (e.g geological maps) if coupled with other hyperspectral instruments. 2) Hyperspectral sensor SIM-GA (Selex Galileo Multisensor Hyperspectral System), a system with spatial acquisition of data which may be used on an earth as well as on an airborne platform. SIM-GA consists of two electro-optical heads, which operate in the VNIR and SWIR regions, respectively, between 400-1000 nm and 1000-2500 nm (3). Although the spectral signature in the VNIR of many minerals is known, the co-presence of more minerals on a surface can affect the quantitative analysis of gypsum. Different minerals, such as gypsum, calcite, weddellite, whewellite, and other components (i.e. carbon particles in black crusts) are, in fact, commonly found on historical surfaces. In order to illustrate the complexity, but also the potentiality of hyperspectral sensors (portable or remote sensing) for the characterization of stone surfaces, a case study, the Facade of Santa Maria Novella in Florence - Italy, will be presented. References 1) R.N. Clark and G.A. Swayze, 1995, "Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice, and snow, and other materials: The USGS Tricorder Algorithm", in "Summaries of the Fifth Annual JPL Airborne Earth Science Workshop", JPL Publication 95-1,1,39-40 2) E. Ben-Dor, K. Patin, A. Banin and A. Karnieli, 2002, "Mapping of several soil properties using DATS-7915 hyperspectral scanner data. A case study over clayely soils in Israel", International Journal of Remote Sensing, 23(6), 1043-1062 3) S. Vettori, M. Benvenuti, M. Camaiti, L. Chiarantini, P. Costagliola, S. Moretti, E. Pecchioni, 2008, "Assessment of the deterioration status of historical buildings by Hyperspectral Imaging techniques&q

Camaiti, Mara; Benvenuti, Marco; Chiarantini, Leandro; Costagliola, Pilar; Moretti, Sandro; Paba, Francesca; Pecchioni, Elena; Vettori, Silvia

2010-05-01

63

Analyzing the effect of synthetic scene resolution, sampling interval, and signal-to-noise ratio on hyperspectral imaging sensor simulations.  

PubMed

Sensor simulation modeling is an important tool for the design of new earth imaging systems. As the input of the model, the characteristics of the synthetic spectral scene image data cube (SSSIDC) play an important role in the accuracy of the simulation. Based on a general sensor simulation model, the effects of SSSIDC resolution, sampling interval (SI), and signal-to-noise ratio (SNR) on simulated data are analyzed. Analysis shows that the simulated data characteristics are a function of the model parameters and the SSSIDC characteristics. The results can be used for evaluating the errors of simulated data, giving criteria for scene image synthesis, and designing appropriate model parameters for expected simulation. Simulation experiments are included to demonstrate the discussed analysis, with the results showing that the analysis is valid. PMID:25322221

Dongxing, Tao; Huijie, Zhao; Guorui, Jia; Yan, Yuan

2014-10-01

64

Hyperspectral Imager for the Coastal Ocean: instrument description and first images.  

PubMed

The Hyperspectral Imager for the Coastal Ocean (HICO) is the first spaceborne hyperspectral sensor designed specifically for the coastal ocean and estuarial, riverine, or other shallow-water areas. The HICO generates hyperspectral images, primarily over the 400-900 nm spectral range, with a ground sample distance of ?90 m (at nadir) and a high signal-to-noise ratio. The HICO is now operating on the International Space Station (ISS). Its cross-track and along-track fields of view are 42 km (at nadir) and 192 km, respectively, for a total scene area of 8000 km(2). The HICO is an innovative prototype sensor that builds on extensive experience with airborne sensors and makes extensive use of commercial off-the-shelf components to build a space sensor at a small fraction of the usual cost and time. Here we describe the instrument's design and characterization and present early images from the ISS. PMID:21478922

Lucke, Robert L; Corson, Michael; McGlothlin, Norman R; Butcher, Steve D; Wood, Daniel L; Korwan, Daniel R; Li, Rong R; Snyder, Willliam A; Davis, Curt O; Chen, Davidson T

2011-04-10

65

Developing a new hyperspectral imaging interferometer for earth observation  

NASA Astrophysics Data System (ADS)

The Aerospace Leap-frog Imaging Stationary interferometer for Earth Observation (ALISEO) is a hyperspectral imaging interferometer for Earth remote sensing. The instrument belongs to the class of Sagnac stationary interferometers and acquires the image of the target superimposed to the pattern of autocorrelation functions of the electromagnetic field coming from each pixel. The ALISEO sensor together with the data processing algorithms that retrieve the at-sensor spectral radiance are discussed. A model describing the instrument OPD and interferogram center is also discussed, improving the procedures for phase retrieval and spectral estimation. Images acquired by ALISEO are shown, and examples of retrieved reflectance spectra are presented.

Barducci, Alessandro; Castagnoli, Francesco; Castellini, Guido; Guzzi, Donatella; Lastri, Cinzia; Marcoionni, Paolo; Nardino, Vanni; Pippi, Ivan

2012-11-01

66

Radiometric sensitivity contrast metrics for hyperspectral remote sensors  

NASA Astrophysics Data System (ADS)

This paper discusses the calculation, interpretation, and implications of various radiometric sensitivity metrics for Earth-observing hyperspectral imaging (HSI) sensors. The most commonly used sensor performance metric is signal-to-noise ratio (SNR), from which additional noise equivalent quantities can be computed, including: noise equivalent spectral radiance (NESR), noise equivalent delta reflectance (NE??), noise equivalent delta emittance (NE??), and noise equivalent delta temperature (NE?T). For hyperspectral sensors, these metrics are typically calculated from an at-aperture radiance (typically generated by MODTRAN) that includes both target radiance and non-target (atmosphere and background) radiance. Unfortunately, these calculations treat the entire at-aperture radiance as the desired signal, even when the target radiance is only a fraction of the total (such as when sensing through a long or optically dense atmospheric path). To overcome this limitation, an augmented set of metrics based on contrast signal-to-noise ratio (CNSR) is developed, including their noise equivalent counterparts (CNESR, CNE??, CNE??, and CNE?T). These contrast metrics better quantify sensor performance in an operational environment that includes remote sensing through the atmosphere.

Silny, John F.; Zellinger, Lou

2014-09-01

67

Spherical harmonics as a shape descriptor for hyperspectral image classification  

NASA Astrophysics Data System (ADS)

Hyperspectral images have traditionally been analyzed by pixel based methods. Invariant methods that consider surface and shape geometry have not been used with these images. However, there is a need for such methods due to the spectral and spatial variability present in these images. In this paper, we develop a method for classifying these images invariant to translation and rotation. The method is based on developing shape descriptors using spherical harmonics. These orthogonal functions have been widely used as a powerful tool for 3D shape recognition and are better suited for hyperspectral images due to its inherent dimensionality. A spherical function defined on the surface of a shape extracts rotation invariant features. In this case, the hyperspectral image is converted to spherical coordinates, decomposed as a sum of its harmonics and then converted to Cartesian coordinates. A classifier is trained with spherical harmonic descriptors computed from training samples. Support vector machines and Maximum Likelihood are considered for classification. The method is tested with hyperspectral image from AISA, AVIRIS and HYDICE sensors. The results show that the descriptors are effective in improving the accuracy of classification.

Nina-Paravecino, Fanny; Manian, Vidya

2010-04-01

68

A variational approach to hyperspectral image fusion  

NASA Astrophysics Data System (ADS)

There has been significant research on pan-sharpening multispectral imagery with a high resolution image, but there has been little work extending the procedure to high dimensional hyperspectral imagery. We present a wavelet-based variational method for fusing a high resolution image and a hyperspectral image with an arbitrary number of bands. To ensure that the fused image can be used for tasks such as classification and detection, we explicitly enforce spectral coherence in the fusion process. This procedure produces images with both high spatial and spectral quality. We demonstrate this procedure on several AVIRIS and HYDICE images.

Moeller, Michael; Wittman, Todd; Bertozzi, Andrea L.

2009-05-01

69

DISTRIBUTED PROCESSING OF HYPERSPECTRAL IMAGES  

Microsoft Academic Search

This paper examines several hyperspectral data processing algorithms designed for a distributed computing environment. Due to the large size, hyperspectral data requires long computational times to process. In a distributed environment, the processing can be split into several components, many of them being executed simultaneously, thus leading to increased time efficiency. The algorithms are derived from previously introduced feature extraction

Stefan Robila

70

HYDICE: an airborne system for hyperspectral imaging  

NASA Astrophysics Data System (ADS)

HYDICE (the Hyperspectral Digital Imagery Collection Experiment) is a program to build and operate an advanced airborne imaging spectrometer. Scheduled to be operating in 1994, it will provide high quality hyperspectral data for use by a number of US civil agencies in determining its utility for a wide range of applications, as well as in support of basic research. The current status of the system under construction and plans for its operation are reviewed.

Rickard, Lee J.; Basedow, Robert W.; Zalewski, Edward F.; Silverglate, Peter R.; Landers, Mark

1993-09-01

71

Airborne Hyperspectral Imaging of Supraglacial Lakes in Greenland's Ablation Zone  

NASA Astrophysics Data System (ADS)

In 2010 an airborne instrument was assembled to image supraglacial lakes near the Jakobshavn Isbrae of the Greenland Ice Sheet. The instrument was designed to fly on a helicopter, and consists of a hyperspectral imager, a GPS/inertial measurement unit (GPS/IMU), and a data-logging computer. A series of narrow visible optical channels ~13nm wide, such as found in a hyperspectral imager, are theorized to be useful in determining the depths of supraglacial lakes using techniques based on the Beer-Lambert-Bouguer Law. During June, several supraglacial lakes were selected for study each day, based upon MODIS imagery taken during the previous week. Flying over a given lake, several track lines were flown to image both shallow and deep sections of the lake, imaging the full range of depth for future algorithm development. The telescoping instrument mount was constructed to allow the sensor package to be deployed from a helicopter in-flight, with an unobstructed downward-facing field of view. The GPS/IMU records the pointing orientation, altitude, and geographical coordinates of the imager to the data-logger, in order to allow post-flight geo-referencing of the raw hyperspectral imagery. With this geo-referenced spectrum data, a depth map for a given lake can be calculated through reference to a water absorptivity model. This risk-reduction expedition to fly a helicopter-borne hyperspectral imager over the supraglacial lakes of Greenland was a success. The instrument mount for the imager worked as designed, and no vibration issues were encountered. As a result, we have confidence in the instrument platform's performance during future surveys of Greenland's supraglacial lakes. The hyperspectral imager, data acquisition computer, and geo-referencing services are provided by Resonon, Inc. of Bozeman, MT, and the GPS/IMU is manufactured by Cloudcap Technology of Hood River, OR.

Adler, J.; Behar, A. E.; Jacobson, N. T.

2010-12-01

72

Real-time snapshot hyperspectral imaging endoscope  

PubMed Central

Hyperspectral imaging has tremendous potential to detect important molecular biomarkers of early cancer based on their unique spectral signatures. Several drawbacks have limited its use for in vivo screening applications: most notably the poor temporal and spatial resolution, high expense, and low optical throughput of existing hyperspectral imagers. We present the development of a new real-time hyperspectral endoscope (called the image mapping spectroscopy endoscope) based on an image mapping technique capable of addressing these challenges. The parallel high throughput nature of this technique enables the device to operate at frame rates of 5.2 frames per second while collecting a (x, y, ?) datacube of 350 × 350 × 48. We have successfully imaged tissue in vivo, resolving a vasculature pattern of the lower lip while simultaneously detecting oxy-hemoglobin. PMID:21639573

Kester, Robert T.; Bedard, Noah; Gao, Liang; Tkaczyk, Tomasz S.

2011-01-01

73

Customizing kernel functions for SVM-based hyperspectral image classification.  

PubMed

Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms. However, few efforts have been made to extend SVMs to cover the specific requirements of hyperspectral image classification, for example, by building tailor-made kernels. Observation of real-life spectral imagery from the AVIRIS hyperspectral sensor shows that the useful information for classification is not equally distributed across bands, which provides potential to enhance the SVM's performance through exploring different kernel functions. Spectrally weighted kernels are, therefore, proposed, and a set of particular weights is chosen by either optimizing an estimate of generalization error or evaluating each band's utility level. To assess the effectiveness of the proposed method, experiments are carried out on the publicly available 92AV3C dataset collected from the 220-dimensional AVIRIS hyperspectral sensor. Results indicate that the method is generally effective in improving performance: spectral weighting based on learning weights by gradient descent is found to be slightly better than an alternative method based on estimating "relevance" between band information and ground truth. PMID:18390369

Guo, B; Gunn, Steve R; Damper, R I; Nelson, J B

2008-04-01

74

Adaptive hyperspectral imaging with a MEMS-based full-frame programmable spectral filter  

NASA Astrophysics Data System (ADS)

Rapidly programmable spatial light modulation devices based on MEMS technology have opened an exciting new arena in spectral imaging: rapidly reprogrammable, high spectral resolution, multi-band spectral filters that enable hyperspectral processing directly in the optical hardware of an imaging sensor. Implemented as a multiplexing spectral selector, a digital micro-mirror device (DMD) can independently choose or reject dozens or hundreds of spectral bands and present them simultaneously to an imaging sensor, forming a complete 2D image. The result is a high-speed, highresolution, programmable spectral filter that gives the user complete control over the spectral content of the image formed at the sensor. This technology enables a wide variety of rapidly reprogrammable operational capabilities within the same sensor including broadband, color, false color, multispectral, hyperspectral and target specific, matched filter imaging. Of particular interest is the ability to implement target-specific hyperspectral matched filters directly into the optical train of the sensor, producing an image highlighting a target within a spectrally cluttered scene in real time without further processing. By performing the hyperspectral image processing at the sensor, such a system can operate with high performance, greatly reduced data volume, and at a fraction of the cost of traditional push broom hyperspectral instruments. Examples of color, false color and target-specific matched-filter images recorded with our visible-spectrum prototype will be displayed, and extensions to other spectral regions will be discussed.

Graff, David L.; Love, Steven P.

2014-05-01

75

Hyperspectral imaging of melanocytic lesions.  

PubMed

Hyperspectral imaging (HSI) allows the identification of objects through the analysis of their unique spectral signatures. Although first developed many years ago for use in terrestrial remote sensing, this technology has more recently been studied for application in the medical field. With preliminary data favoring a role for HSI in distinguishing normal and lesional skin tissues, we sought to investigate the potential use of HSI as a diagnostic aid in the classification of atypical Spitzoid neoplasms, a group of lesions that often leave dermatopathologists bewildered. One hundred and two hematoxylin and eosin-stained tissue samples were divided into 1 of 4 diagnostic categories (Spitz nevus, Spitz nevus with unusual features, atypical Spitzoid neoplasm, and Spitzoid malignant melanoma) and 1 of 2 control groups (benign melanocytic nevus and malignant melanoma). A region of interest was selected from the dermal component of each sample, thereby maximizing the examination of melanocytes. Tissue samples were examined at ×400 magnification using a spectroscopy system interfaced with a light microscope. The absorbance patterns of wavelengths from 385 to 880 nm were measured and then analyzed within and among groups. All tissue groups demonstrated 3 common absorbance spectra at 496, 533, and 838 nm. Each sample group contained at least one absorption point that was unique to that group. The Spitzoid malignant melanoma category had the highest number of total and unique absorption points for any sample group. The data were then clustered into 12 representative spectral classes. Although each of the sample groups contained all 12 spectral vectors, they did so in differing proportions. These preliminary results reveal differences in the spectral signatures of the Spitzoid lesions examined in this study. Further investigation into a role for HSI in classifying atypical Spitzoid neoplasms is encouraged. PMID:24247577

Gaudi, Sudeep; Meyer, Rebecca; Ranka, Jayshree; Granahan, James C; Israel, Steven A; Yachik, Theodore R; Jukic, Drazen M

2014-02-01

76

Surface emissivity and temperature retrieval for a hyperspectral sensor  

SciTech Connect

With the growing use of hyper-spectral imagers, e.g., AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. The author believes that this will enable him to get around using the present temperature-emissivity separation algorithms using methods which take advantage of the many channels available in hyper-spectral imagers. A simple fact used in coming up with a novel algorithm is that a typical surface emissivity spectrum are rather smooth compared to spectral features introduced by the atmosphere. Thus, a iterative solution technique can be devised which retrieves emissivity spectra based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. One such iterative algorithm solves the radiative transfer equation for the radiance at the sensor for the unknown emissivity and uses the blackbody temperature computed in an atmospheric window to get a guess for the unknown surface temperature. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.

Borel, C.C.

1998-12-01

77

Biometric study using hyperspectral imaging during stress  

NASA Astrophysics Data System (ADS)

To the casual observer, transient stress results in a variety of physiological changes that can be seen in the face. Although the conditions can be seen visibly, the conditions affect the emissivity and absorption properties of the skin, which imaging spectrometers, commonly referred to as Hyperspectral (HS) cameras, can quantify at every image pixel. The study reported on in this paper, using Hyperspectral cameras, provides a basis for continued study of HS imaging to eventually quantify biometric stress. This study was limited to the visible to near infrared (VNIR) spectral range. Signal processing tools and algorithms have been developed and are described for using HS face data from human subjects. The subjects were placed in psychologically stressful situations and the camera data were analyzed to detect stress through changes in dermal reflectance and emissivity. Results indicate that hyperspectral imaging may potentially serve as a non-invasive tool to measure changes in skin emissivity indicative of a stressful incident. Particular narrow spectral bands in the near-infrared region of the electromagnetic spectrum seem especially important. Further studies need to be performed to determine the optimal spectral bands and to generalize the conclusions. The enormous information available in hyperspectral imaging needs further analysis and more spectral regions need to be exploited. Non-invasive stress detection is a prominent area of research with countless applications for both military and commercial use including border patrol, stand-off interrogation, access control, surveillance, and non-invasive and un-attended patient monitoring.

Nagaraj, Sheela; Quoraishee, Shafik; Chan, Gabriel; Short, Kenneth R.

2010-04-01

78

Unsupervised hyperspectral image analysis with projection pursuit  

Microsoft Academic Search

Principal components analysis (PCA) is effective at compressing information in multivariate data sets by computing orthogonal projections that maximize the amount of data variance. Unfortunately, information content in hyperspectral images does not always coincide with such projections. The authors propose an application of projection pursuit (PP), which seeks to find a set of projections that are \\

Agustin Ifarraguerri; Chein-I Chang

2000-01-01

79

Automatic Denoising and Unmixing in Hyperspectral Image Processing  

NASA Astrophysics Data System (ADS)

This thesis addresses two important aspects in hyperspectral image processing: automatic hyperspectral image denoising and unmixing. The first part of this thesis is devoted to a novel automatic optimized vector bilateral filter denoising algorithm, while the remainder concerns nonnegative matrix factorization with deterministic annealing for unsupervised unmixing in remote sensing hyperspectral images. The need for automatic hyperspectral image processing has been promoted by the development of potent hyperspectral systems, with hundreds of narrow contiguous bands, spanning the visible to the long wave infrared range of the electromagnetic spectrum. Due to the large volume of raw data generated by such sensors, automatic processing in the hyperspectral images processing chain is preferred to minimize human workload and achieve optimal result. Two of the mostly researched processing for such automatic effort are: hyperspectral image denoising, which is an important preprocessing step for almost all remote sensing tasks, and unsupervised unmixing, which decomposes the pixel spectra into a collection of endmember spectral signatures and their corresponding abundance fractions. Two new methodologies are introduced in this thesis to tackle the automatic processing problems described above. Vector bilateral filtering has been shown to provide good tradeoff between noise removal and edge degradation when applied to multispectral/hyperspectral image denoising. It has also been demonstrated to provide dynamic range enhancement of bands that have impaired signal to noise ratios. Typical vector bilateral filtering usage does not employ parameters that have been determined to satisfy optimality criteria. This thesis also introduces an approach for selection of the parameters of a vector bilateral filter through an optimization procedure rather than by ad hoc means. The approach is based on posing the filtering problem as one of nonlinear estimation and minimizing the Stein's unbiased risk estimate (SURE) of this nonlinear estimator. Along the way, this thesis provides a plausibility argument with an analytical example as to why vector bilateral filtering outperforms band-wise 2D bilateral filtering in enhancing SNR. Experimental results show that the optimized vector bilateral filter provides improved denoising performance on multispectral images when compared to several other approaches. Non-negative matrix factorization (NMF) technique and its extensions were developed to find part based, linear representations of non-negative multivariate data. They have been shown to provide more interpretable results with realistic non-negative constrain in unsupervised learning applications such as hyperspectral imagery unmixing, image feature extraction, and data mining. This thesis extends the NMF method by incorporating deterministic annealing optimization procedure, which will help solve the non-convexity problem in NMF and provide a better choice of sparseness constrain. The approach is based on replacing the difficult non-convex optimization problem of NMF with an easier one by adding an auxiliary convex entropy constrain term and solving this first. Experiment results with hyperspectral unmixing application show that the proposed technique provides improved unmixing performance compared to other state-of-the-art methods.

Peng, Honghong

80

Metric Learning to Enhance Hyperspectral Image Segmentation  

NASA Technical Reports Server (NTRS)

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

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

2013-01-01

81

[Spectral calibration of hyperspectral imager based on spectral absorption target].  

PubMed

Retrieval of center wavelength and bandwidth is a key step for quantitative analysis of hyperspectral data. The present paper proposes a spectral calibration method of hyperspectral imager, whose spectrum covers visible and near-infrared band, using spectral absorption target. Ground calibration experiment was designed for a hyperspectral imager with a bandwidth of 6 nm. Hyperspectral imager and ASD spectrometer measured the same spectral absorption target synchronously. Reflectance spectrum was derived from the different data set. Center wavelength and bandwidth were retrieved by matching the reflectance data from hyperspectral imager and ASD spectrometer. The experiment result shows that this method can be applied in spectral calibration of hyperspectral imagers to improve the quantitative studies on hyperspectral imagery. PMID:23697157

Gou, Zhi-Yang; Yan, Lei; Chen, Wei; Zhao, Hong-Ying; Yin, Zhong-Yi; Duan, Yi-Ni

2013-02-01

82

Airborne Hyperspectral Imaging of Seagrass and Coral Reef  

NASA Astrophysics Data System (ADS)

This talk presents the process of project preparation, airborne data collection, data pre-processing and comparative analysis of a series of airborne hyperspectral projects focused on the mapping of seagrass and coral reef communities in the Florida Keys. As part of a series of large collaborative projects funded by the NASA ROSES program and the Florida Fish and Wildlife Conservation Commission and administered by the NASA UAV Collaborative, a series of airborne hyperspectral datasets were collected over six sites in the Florida Keys in May 2012, October 2012 and May 2013 by Galileo Group, Inc. using a manned Cessna 172 and NASA's SIERRA Unmanned Aerial Vehicle. Precise solar and tidal data were used to calculate airborne collection parameters and develop flight plans designed to optimize data quality. Two independent Visible and Near-Infrared (VNIR) hyperspectral imaging systems covering 400-100nm were used to collect imagery over six Areas of Interest (AOIs). Multiple collections were performed over all sites across strict solar windows in the mornings and afternoons. Independently developed pre-processing algorithms were employed to radiometrically correct, synchronize and georectify individual flight lines which were then combined into color balanced mosaics for each Area of Interest. The use of two different hyperspectral sensor as well as environmental variations between each collection allow for the comparative analysis of data quality as well as the iterative refinement of flight planning and collection parameters.

Merrill, J.; Pan, Z.; Mewes, T.; Herwitz, S.

2013-12-01

83

SPARSE REPRESENTATION BASED FUSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES  

E-print Network

SPARSE REPRESENTATION BASED FUSION OF MULTISPECTRAL AND HYPERSPECTRAL IMAGES Qi Wei(1) , Jos�e M the observed images. Then, condition- ally on these dictionaries and supports, the fusion problem is solved compared with the state-of-the-art. Index Terms-- Image fusion, hyperspectral image, multispec- tral image

Dobigeon, Nicolas

84

Use of Hyperspectral Data with Intensity Images for Automatic Building Modeling  

Microsoft Academic Search

Geospatial databases are needed for many tasks in ci- vilian and military applications. Automated building de- tection and description systems attempt to construct 3-D models using primarily PAN (panchromatic) images. These systems can make use of cues derived from other sensor modalities to make the task easier and more ro- bust. The recent development of hyperspectral sensors such as HYDICE

A. Huertas; R. Nevatia; D. Landgrebe

1999-01-01

85

Hyperspectral identification algorithm for VIS-SWIR sensors  

NASA Astrophysics Data System (ADS)

The objective is to use spectral image data to determine the identity of materials present in the image. In order to accomplish material identification, material-specific spectral signatures need to be developed, as do algorithms that exploit those signatures. The performance of the algorithms and signatures will be tested against real data collected at multiple altitudes and locations, calibrated to reflectance using different techniques. Spectral signatures will be derived for the targets that were deployed at various test using the HYDICE sensor. These signatures are used to detect and locate those targets in the data sets. The false alarm performance of the algorithms and signatures provides evidence for the uniqueness of those signatures. Similar false alarm performance between the calibration techniques demonstrates the ability to create robust spectral signatures without using a priori information on any material in the image for calibration. This has implications for a)hyperspectral sensor that have pixels with a large GSD and do not facilitate the use of calibration panels, b) collection scenarios where calibration panels cannot be deployed, and c) data exploitation.

Wolboldt, Mark; Pilati, Martin L.

1997-10-01

86

Theoretical Analysis of the Sensitivity and Speed Improvement of ISIS over a Comparable Traditional Hyperspectral Imager  

SciTech Connect

The analysis presented herein predicts that, under signal-independent noise limited conditions, an Information-efficient Spectral Imaging Sensor (ISIS) style hyperspectral imaging system design can obtain significant signal-to-noise ratio (SNR) and speed increase relative to a comparable traditional hyperspectral imaging (HSI) instrument. Factors of forty are reasonable for a single vector, and factors of eight are reasonable for a five-vector measurement. These advantages can be traded with other system parameters in an overall sensor system design to allow a variety of applications to be done that otherwise would be impossible within the constraints of the traditional HSI style design.

Brian R. Stallard; Stephen M. Gentry

1998-09-01

87

Hyperspectral imaging for cancer surgical margin delineation: registration of hyperspectral and histological images  

NASA Astrophysics Data System (ADS)

The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection.

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo G.; Fei, Baowei

2014-03-01

88

Hyperspectral Imaging for Cancer Surgical Margin Delineation: Registration of Hyperspectral and Histological Images  

PubMed Central

The determination of tumor margins during surgical resection remains a challenging task. A complete removal of malignant tissue and conservation of healthy tissue is important for the preservation of organ function, patient satisfaction, and quality of life. Visual inspection and palpation is not sufficient for discriminating between malignant and normal tissue types. Hyperspectral imaging (HSI) technology has the potential to noninvasively delineate surgical tumor margin and can be used as an intra-operative visual aid tool. Since histological images provide the ground truth of cancer margins, it is necessary to warp the cancer regions in ex vivo histological images back to in vivo hyperspectral images in order to validate the tumor margins detected by HSI and to optimize the imaging parameters. In this paper, principal component analysis (PCA) is utilized to extract the principle component bands of the HSI images, which is then used to register HSI images with the corresponding histological image. Affine registration is chosen to model the global transformation. A B-spline free form deformation (FFD) method is used to model the local non-rigid deformation. Registration experiment was performed on animal hyperspectral and histological images. Experimental results from animals demonstrated the feasibility of the hyperspectral imaging method for cancer margin detection. PMID:25328640

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-01-01

89

Hyperspectral imaging spectro radiometer improves radiometric accuracy  

NASA Astrophysics Data System (ADS)

Reliable and accurate infrared characterization is necessary to measure the specific spectral signatures of aircrafts and associated infrared counter-measures protections (i.e. flares). Infrared characterization is essential to improve counter measures efficiency, improve friend-foe identification and reduce the risk of friendly fire. Typical infrared characterization measurement setups include a variety of panchromatic cameras and spectroradiometers. Each instrument brings essential information; cameras measure the spatial distribution of targets and spectroradiometers provide the spectral distribution of the emitted energy. However, the combination of separate instruments brings out possible radiometric errors and uncertainties that can be reduced with Hyperspectral imagers. These instruments combine both spectral and spatial information into the same data. These instruments measure both the spectral and spatial distribution of the energy at the same time ensuring the temporal and spatial cohesion of collected information. This paper presents a quantitative analysis of the main contributors of radiometric uncertainties and shows how a hyperspectral imager can reduce these uncertainties.

Prel, Florent; Moreau, Louis; Bouchard, Robert; Bullis, Ritchie D.; Roy, Claude; Vallières, Christian; Levesque, Luc

2013-06-01

90

Software for Simulation of Hyperspectral Images  

NASA Technical Reports Server (NTRS)

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.

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

2002-01-01

91

Polarimetric Hyperspectral Imaging Systems and Applications  

NASA Technical Reports Server (NTRS)

This paper reports activities in the development of AOTF Polarimetric Hyperspectral Imaging (PHI) Systems at JPL along with field observation results for illustrating the technology capabilities and advantages in remote sensing. In addition, the technology was also used to measure thickness distribution and structural imperfections of silicon-on-silicon wafers using white light interference phenomenon for demonstrating the potential in scientific and industrial applications.

Cheng, Li-Jen; Mahoney, Colin; Reyes, George; Baw, Clayton La; Li, G. P.

1996-01-01

92

Hyperspectral image band selection based on genetic algorithm  

NASA Astrophysics Data System (ADS)

Optimum band selection for visual interpretation and classification is an interesting task in conventional remote sensing, and, as an effective means to mitigate the curse of dimensionality, which has assumed growing importance with the availability of hyperspectral remote sensing data. In determining three-channel combination for a informative display in an image-cube and determining feature combination for fast classification, band selection is regarded indispensable in hyperspectral remote sensing. When applied to data acquired from a hyperspectral sensor, which is usually with a set of hundreds of band, however, conventional band selection procedure, of any criterion, becomes not viable with respect to the particularly time consuming. To cope with this pitfall, a method based upon genetic algorithm is proposed in this paper. An experiment, with a 121 band data set, demonstrate the efficiency. For simplification, the algorithm is designed to choose a combination which produces the most informative visual result when used as the top color preference in an image- cube. With little modification in criterion, the algorithm can be used to select features for classification purpose. The corresponding result is also presented in this paper.

Ma, Jiping; Zheng, Zhaobao; Tong, Qingxi; Zheng, Lanfen; Zhang, Bin

2001-09-01

93

Dynamic scene generation, multimodal sensor design, and target tracking demonstration for hyperspectral\\/polarimetric performance-driven sensing  

Microsoft Academic Search

Simulation of moving vehicle tracking has been demonstrated using hyperspectral and polarimetric imagery (HSI\\/PI). Synthetic HSI\\/PI image cubes of an urban scene containing moving vehicle content were generated using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) Megascene #1 model. Video streams of sensor-reaching radiance frames collected from a virtual orbiting aerial platform's imaging sensor

Michael D. Presnar; Alan D. Raisanen; David R. Pogorzala; John P. Kerekes; Andrew C. Rice

2010-01-01

94

Adaptive Band Selection for Hyperspectral Image Fusion Using Mutual Information  

E-print Network

Adaptive Band Selection for Hyperspectral Image Fusion Using Mutual Information Baofeng Guo, Steve propose a new information-based band selection method for hyperspectral image fusion, which uses Gunn, Bob Damper and James Nelson Image, Speech and Intelligent Systems Group School of Electronics

Nelson, James

95

Hyperspectral Image Turbulence Measurements of the Atmosphere  

NASA Technical Reports Server (NTRS)

A Forward Looking Interferometer (FLI) sensor has the potential to be used as a means of detecting aviation hazards in flight. One of these hazards is mountain wave turbulence. The results from a data acquisition activity at the University of Colorado s Mountain Research Station will be presented here. Hyperspectral datacubes from a Telops Hyper-Cam are being studied to determine if evidence of a turbulent event can be identified in the data. These data are then being compared with D&P TurboFT data, which are collected at a much higher time resolution and broader spectrum.

Lane, Sarah E.; West, Leanne L.; Gimmestad, Gary G.; Kireev, Stanislav; Smith, William L., Sr.; Burdette, Edward M.; Daniels, Taumi; Cornman, Larry

2012-01-01

96

Hyperspectral all-sky imaging of auroras.  

PubMed

A prototype auroral hyperspectral all-sky camera has been constructed and tested. It uses electro-optical tunable filters to image the night sky as a function of wavelength throughout the visible spectrum with no moving mechanical parts. The core optical system includes a new high power all-sky lens with F-number equal to f/1.1. The camera has been tested at the Kjell Henriksen Observatory (KHO) during the auroral season of 2011/2012. It detects all sub classes of aurora above ~½ of the sub visual 1kR green intensity threshold at an exposure time of only one second. Supervised classification of the hyperspectral data shows promise as a new method to process and identify auroral forms. PMID:23262713

Sigernes, Fred; Ivanov, Yuriy; Chernouss, Sergey; Trondsen, Trond; Roldugin, Alexey; Fedorenko, Yury; Kozelov, Boris; Kirillov, Andrey; Kornilov, Ilia; Safargaleev, Vladimir; Holmen, Silje; Dyrland, Margit; Lorentzen, Dag; Baddeley, Lisa

2012-12-01

97

Instrumental error in chromotomosynthetic hyperspectral imaging.  

PubMed

Chromotomosynthetic imaging (CTI) is a method of convolving spatial and spectral information that can be reconstructed into a hyperspectral image cube using the same transforms employed in medical tomosynthesis. A direct vision prism instrument operating in the visible (400-725 nm) with 0.6 mrad instantaneous field of view (IFOV) and 0.6-10 nm spectral resolution has been constructed and characterized. Reconstruction of hyperspectral data cubes requires an estimation of the instrument component properties that define the forward transform. We analyze the systematic instrumental error in collected projection data resulting from prism spectral dispersion, prism alignment, detector array position, and prism rotation angle. The shifting and broadening of both the spectral lineshape function and the spatial point spread function in the reconstructed hyperspectral imagery is compared with experimental results for monochromatic point sources. The shorter wavelength (?<500 nm) region where the prism has the highest spectral dispersion suffers mostly from degradation of spectral resolution in the presence of systematic error, while longer wavelengths (?>600 nm) suffer mostly from a shift of the spectral peaks. The quality of the reconstructed hyperspectral imagery is most sensitive to the misalignment of the prism rotation mount. With less than 1° total angular error in the two axes of freedom, spectral resolution was degraded by as much as a factor of 2 in the blue spectral region. For larger errors than this, spectral peaks begin to split into bimodal distributions, and spatial point response functions are reconstructed in rings with radii proportional to wavelength and spatial resolution. PMID:22858961

Bostick, Randall L; Perram, Glen P

2012-07-20

98

Hyperspectral Infrared Images of Terrain  

NASA Technical Reports Server (NTRS)

Images at 128 wavelengths allow direct identification of many earth surface materials. Two reports describe advanced airborne spectrometer that creates images of terrain at many wavelengths. Airborne imaging spectrometer (AIS) produces two-dimensional images in 128 spectral bands in 1.2-to-2.4-micrometer wavelength region. Images created by 32-by-32 array of mercury cadmium telluride detector elements. Array views swath of Earth below moving aircraft. Used for agricultural, geological, and other surveys.

Vane, G.; Goetz, A. F. H.; Wellman, J. B.; Labaw, C. C.

1986-01-01

99

Hyperspectral image classification using Support Vector Machine  

NASA Astrophysics Data System (ADS)

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.

Moughal, T. A.

2013-06-01

100

Using spectral distances for speedup in hyperspectral image processing  

Microsoft Academic Search

This paper investigates the efficiency of spectral screening as a tool for speedup in hyperspectral image processing. Spectral screening is a technique for reducing the hyperspectral data to a representative subset of spectra. The subset is formed such that any two spectra in it are dissimilar and, for any spectrum in the original image cube, there is a similar spectrum

S. A. Robila

2005-01-01

101

Meat Quality Evaluation by Hyperspectral Imaging Technique: An Overview  

Microsoft Academic Search

During the last two decades, a number of methods have been developed to objectively measure meat quality attributes. Hyperspectral imaging technique as one of these methods has been regarded as a smart and promising analytical tool for analyses conducted in research and industries. Recently there has been a renewed interest in using hyperspectral imaging in quality evaluation of different food

Gamal Elmasry; Douglas F. Barbin; Da-Wen Sun; Paul Allen

2012-01-01

102

Notes on reconstructing the data cube in hyperspectral image processing  

E-print Network

Notes on reconstructing the data cube in hyperspectral image processing Charles Byrne (Charles 01854 May 3, 2004 Abstract The hyperspectral imaging technique described in [12] leads to the inter- esting problem of reconstructing a three-dimensional data cube from measured data. This problem involves

Byrne, Charles

103

Ore minerals textural characterization by hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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.

Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia

2013-02-01

104

Real-time data processor for the COMPASS hyperspectral sensor system  

Microsoft Academic Search

The NVESD COMPASS instrument is an airborne dispersive hyperspectral imager that covers the VNIR through SWIR bands and incorporates a real-time data processing system. The processing system consists of a Data Processing Computer (DPC) and an Operator Display\\/Control Computer (ODC). The high-performance DPC executes real-time sensor calibration and multiple spectral detection algorithms on 13 G4-processors in a Race++ switched backplane.

William E. Schaff; Anthony Copeland; Mike Steffen; Rory O'Connor; Christopher Simi; Jerry Zadnik; Ed M. Winter; Glenn Healey

2003-01-01

105

Real-time data processor for the COMPASS hyperspectral sensor system  

Microsoft Academic Search

The NVESD COMPASS instrument is an airborne dispersive hyperspectral imager that covers the VNIR through SWIR bands and incorporates a real-time data processing system. The processing system consists of a Data Processing Computer (DPC) and an Operator Display\\/Control Computer (ODC). The high-performance DPC executes real-time sensor calibration and multiple spectral detection algorithms on 13 G4-processors in a Race++ switched backplane.

William E. Schaff; Anthony Copeland; Mike Steffen; Rory O'Connor; Christopher Simi; Jerry Zadnik; Ed M. Winter; Glenn Healey

2004-01-01

106

Reconfigurable Hardware for Compressing Hyperspectral Image Data  

NASA Technical Reports Server (NTRS)

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 the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

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

2010-01-01

107

Calibration and application of airborne pushbroom hyperspectral imager (PHI)  

NASA Astrophysics Data System (ADS)

Pushbroom Hyperspectral Imaging technology is a new method to acquire the imaging spectrum data. Based on the area CCD technology, pushbroom imager can provide the higher SNR and more bands. Since 1995, Shanghai Institute of Technical Physics was developing the Pushbroom Hyperspectral Imager. In the paper, two generation of pushbroom hyperspectral imager (PHI) and the principle of instrument are introduced. The method and result of spectral calibration and radiation calibration are written in detail. PHI had been used in remote sensing of environment monitoring, geology study, oil and gas prospecting, vegetation, ocean observation, city layout, fine agriculture, forest fireproofing at home and abroad.

Shu, Rong; Xue, Yong-Qi; Yang, Yi-De

2004-02-01

108

Sparse Superpixel Unmixing for Hyperspectral Image Analysis  

NASA Technical Reports Server (NTRS)

Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

Castano, Rebecca; Thompson, David R.; Gilmore, Martha

2010-01-01

109

Hyperspectral imaging from space: Warfighter-1  

NASA Astrophysics Data System (ADS)

The Air Force Research Laboratory Integrated Space Technology Demonstrations (ISTD) Program Office has partnered with Orbital Sciences Corporation (OSC) to complement the commercial satellite's high-resolution panchromatic imaging and Multispectral imaging (MSI) systems with a moderate resolution Hyperspectral imaging (HSI) spectrometer camera. The program is an advanced technology demonstration utilizing a commercially based space capability to provide unique functionality in remote sensing technology. This leveraging of commercial industry to enhance the value of the Warfighter-1 program utilizes the precepts of acquisition reform and is a significant departure from the old-school method of contracting for government managed large demonstration satellites with long development times and technology obsolescence concerns. The HSI system will be able to detect targets from the spectral signature measured by the hyperspectral camera. The Warfighter-1 program will also demonstrate the utility of the spectral information to theater military commanders and intelligence analysts by transmitting HSI data directly to a mobile ground station that receives and processes the data. After a brief history of the project origins, this paper will present the details of the Warfighter-1 system and expected results from exploitation of HSI data as well as the benefits realized by this collaboration between the Air Force and commercial industry.

Cooley, Thomas; Seigel, Gary; Thorsos, Ivan

1999-01-01

110

Hyperspectral Image Analysis Using Genetic Programming Brian J. Ross and Anthony G. Gualtieri  

E-print Network

for use on hyperspectral images. Separate mineral classifiers are evolved for three spe- cific minerals in the infrared), taken over Cuprite, Nevada, with the AVIRIS hy- perspectral sensor. A composite mineral im- age indicating the overall reflectance percent- age of three minerals (alunite, kaolnite, bud- dingtonite

Ross, Brian J.

111

Dimensionality reduction of hyperspectral imaging data using local principal components transforms  

Microsoft Academic Search

The spectral exploitation of hyperspectral imaging (HSI) data is based on their representation as vectors in a high dimensional space defined by a set of orthogonal coordinate axes, where each axis corresponds to one spectral band. The larger number of bands, which varies from 100-400 in existing sensors, makes the storage, transmission, and processing of HSI data a challenging task.

Dimitris G. Manolakis; David B. Marden

2004-01-01

112

Noise properties of a corner-cube Michelson interferometer LWIR hyperspectral imager  

Microsoft Academic Search

Interferometric hyperspectral imagers using infrared focal plane array (FPA) sensors have received increasing interest within the field of security and defence. Setups are commonly based upon either the Sagnac or the Michelson configuration, where the former is usually preferred due to its mechanical robustness. However, the Michelson configuration shows advantages in larger FOV due to better vignetting performance and improved

D. Bergstrom; I. Renhorn; T. Svensson; R. Persson; T. Hallberg; R. Lindell; G. Boreman

2010-01-01

113

FUSION OF HYPERSPECTRAL AND PANCHROMATIC IMAGES USING MULTIRESOLUTION ANALYSIS AND NONLINEAR PCA BAND REDUCTION  

E-print Network

FUSION OF HYPERSPECTRAL AND PANCHROMATIC IMAGES USING MULTIRESOLUTION ANALYSIS AND NONLINEAR PCA Network, NLPCA, Hyperspectral image, Pansharpening, Image fusion. 1. INTRODUCTION Generally, for satellite resolution PAN image in the context of pansharpening. Pansharpening, or image fusion, is the process

Condat, Laurent

114

Hyperspectral low-light camera for imaging of biological samples  

Microsoft Academic Search

The capability of acquiring hyperspectral information in low light conditions is potentially important for a variety of applications, ranging from remote sensing to biomedical fluorescence imaging. Particularly interesting is its use in optical analysis of biological samples in which the light level should be kept low to prevent tissue damage. For this purpose a low-light hyperspectral camera has been developed

J. Hernandez-Palacios; L. L. Randeberg; I. Baarstad; T. Loke; T. Skauli

2010-01-01

115

Interference-invariant target detection in hyperspectral images  

Microsoft Academic Search

In this paper we address the problem of detecting targets in hyperspectral images when the target signature is buried in random noise and interference (from other materials in the same pixel). We assume that the hyperspectral pixel measurement is a linear combination of the target and interference signatures observed in additive noise. The linear mixing assumption leads to a linear

Terry L. Nichols; John K. Thomas; Wolfgang Kober; Vincent J. Velten

1998-01-01

116

Hyperspectral image classification by collaboration of spatial and spectral information  

Microsoft Academic Search

The classification of hyperspectral image data has drawn much attention in recent years. Consequently, it contains not only spectral information of objects, but also spatial arrangement of objects. The most established Hyperspectral classifiers are based on the observed spectral signal, and ignore the spatial relations among observations. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. To

Yu-Zhou Yan; Yongqiang Zhao; Hui-Feng Xue; Xiao-Dong Kou; Yuanzheng Liu

2009-01-01

117

Hyperspectral imaging for melanoma screening  

NASA Astrophysics Data System (ADS)

The 5-year survival rate for patients diagnosed with Melanoma, a deadly form of skin cancer, in its latest stages is about 15%, compared to over 90% for early detection and treatment. We present an imaging system and algorithm that can be used to automatically generate a melanoma risk score to aid clinicians in the early identification of this form of skin cancer. Our system images the patient's skin at a series of different wavelengths and then analyzes several key dermoscopic features to generate this risk score. We have found that shorter wavelengths of light are sensitive to information in the superficial areas of the skin while longer wavelengths can be used to gather information at greater depths. This accompanying diagnostic computer algorithm has demonstrated much higher sensitivity and specificity than the currently commercialized system in preliminary trials and has the potential to improve the early detection of melanoma.

Martin, Justin; Krueger, James; Gareau, Daniel

2014-03-01

118

Dried fruits quality assessment by hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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.

Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe

2012-05-01

119

Feature reduction and morphological processing for hyperspectral image data.  

PubMed

An automatic target detection system that uses hyperspectral (HS) imagery is proposed. HS images contain both spatial and spectral response information that provides detailed descriptions of an object. These new, to our knowledge, sensor data are useful in automatic target recognition applications. To provide discrimination information from the HS images and to select features that generalize well, we describe a new, to our knowledge, high-dimensional generalized discriminant feature-extraction algorithm and compare its performance with that of other feature-reduction methods for two HS target detection applications (mine and vehicle detection) by using a nearest-neighbor classifier. We also advance an approach to simultaneously optimize both spatial and spectral responses. PMID:14735942

Casasent, David; Chen, Xue-Wen

2004-01-10

120

Image analysis of hyperspectral and multispectral data using projection pursuit  

NASA Astrophysics Data System (ADS)

Given recent advancements of modern hyperspectral (HS) sensors, the potential for information extraction has increased drastically given the continual improvements in spatial and spectral resolution. As a result, more sophisticated feature extraction and target detection (TD) algorithms are needed to improve the performance of the image analyst, whether computer-based or human. In this paper, a novel TD algorithm based on Projection Pursuit (PP) is proposed and implemented. PP is a well-known technique for dimensionality reduction in multi-band data sets without loss of any critical information. This technique highlights different features of interest in an image, thus improving and simplifying subsequent anomaly detection. The new target detection technique is based on a hybrid of PP and Reed_Xiaoli (RX) anomaly detector. In this study, the combining of PP with the RX detector (PPRX) adds some extra value to the standard RX detection technique and leads the development of a TD method that can be applied on hyperspectral/multispectral (MS) data sets. This novel technique, after being trained by using the Projection Index (PI) and a priori information of target of interest, utilizes RX detector to evaluate each potential projection. The main drawback of previously introduced PP methods such as those based on Information Divergence and Kurtosis/Skewness is that these techniques are sensitive to statistical outliers and cannot be used to highlight a specific target of interest. This study uses three data sets: (1) 4-band IKONOS multispectral data (2) 210-band HYDICE, and (3) 200-band simulated hyperspectral data set.

Azizi, Nilofar; Meng, Julian

2008-01-01

121

Detection of gaseous plumes in IR hyperspectral images using hierarchical clustering.  

PubMed

The emergence of IR hyperspectral sensors in recent years enables their use in remote environmental monitoring of gaseous plumes. IR hyperspectral imaging combines the unique advantages of traditional remote sensing methods such as multispectral imagery and nonimaging Fourier transform infrared spectroscopy, while eliminating their drawbacks. The most significant improvement introduced by hyperspectral technology is the capability of standoff detection and discrimination of effluent gaseous plumes without need for a clear reference background or any other temporal information. We introduce a novel approach for detection and discrimination of gaseous plumes in IR hyperspectral imagery using a divisive hierarchical clustering algorithm. The utility of the suggested detection algorithm is demonstrated on IR hyperspectral images of the release of two atmospheric tracers. The application of the proposed detection method on the experimental data has yielded a correct identification of all the releases without any false alarms. These encouraging results show that the presented approach can be used as a basis for a complete identification algorithm for gaseous pollutants in IR hyperspectral imagery without the need for a clear background. PMID:17805376

Hirsch, Eitan; Agassi, Eyal

2007-09-01

122

System and method for progressive band selection for hyperspectral images  

NASA Technical Reports Server (NTRS)

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for progressive band selection for hyperspectral images. A system having module configured to control a processor to practice the method calculates a virtual dimensionality of a hyperspectral image having multiple bands to determine a quantity Q of how many bands are needed for a threshold level of information, ranks each band based on a statistical measure, selects Q bands from the multiple bands to generate a subset of bands based on the virtual dimensionality, and generates a reduced image based on the subset of bands. This approach can create reduced datasets of full hyperspectral images tailored for individual applications. The system uses a metric specific to a target application to rank the image bands, and then selects the most useful bands. The number of bands selected can be specified manually or calculated from the hyperspectral image's virtual dimensionality.

Fisher, Kevin (Inventor)

2013-01-01

123

LWIR hyperspectral imaging application and detection of chemical precursors  

NASA Astrophysics Data System (ADS)

Detection and identification of Toxic industrial chemicals (TICs) represent a major challenge to protect and sustain first responder and public security. In this context, passive Hyperspectral Imaging (HSI) is a promising technology for the standoff detection and identification of chemical vapors emanating from a distant location. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test Very Long Wave Infrared (VLWIR) HSI sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs), surrogates and precursors. Sensors such as the Improved Compact ATmospheric Sounding Interferometer (iCATSI) and the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) were developed for this application. This paper presents the sensor developments and preliminary results of standoff detection and identification of TICs and precursors. The iCATSI and MoDDIFS sensors are based on the optical differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios are reported. These results serve to establish the potential of passive standoff HSI detection of TICs, precursors and surrogates.

Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis

2012-10-01

124

Detection of chemical pollutants by passive LWIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Toxic industrial chemicals (TICs) represent a major threat to public health and security. Their detection constitutes a real challenge to security and first responder's communities. One promising detection method is based on the passive standoff identification of chemical vapors emanating from the laboratory under surveillance. To investigate this method, the Department of National Defense and Public Safety Canada have mandated Defense Research and Development Canada (DRDC) - Valcartier to develop and test passive Long Wave Infrared (LWIR) hyperspectral imaging (HSI) sensors for standoff detection. The initial effort was focused to address the standoff detection and identification of toxic industrial chemicals (TICs) and precursors. Sensors such as the Multi-option Differential Detection and Imaging Fourier Spectrometer (MoDDIFS) and the Improved Compact ATmospheric Sounding Interferometer (iCATSI) were developed for this application. This paper describes the sensor developments and presents initial results of standoff detection and identification of TICs and precursors. The standoff sensors are based on the differential Fourier-transform infrared (FTIR) radiometric technology and are able to detect, spectrally resolve and identify small leak plumes at ranges in excess of 1 km. Results from a series of trials in asymmetric threat type scenarios will be presented. These results will serve to establish the potential of the method for standoff detection of TICs precursors and surrogates.

Lavoie, Hugo; Thériault, Jean-Marc; Bouffard, François; Puckrin, Eldon; Dubé, Denis

2012-09-01

125

Hyperspectral imaging in diabetic foot wound care.  

PubMed

Diabetic foot ulceration is a major complication of diabetes and afflicts as many as 15 to 25% of type 1 and 2 diabetes patients during their lifetime. If untreated, diabetic foot ulcers may become infected and require total or partial amputation of the affected limb. Early identification of tissue at risk of ulcerating could enable proper preventive care, thereby reducing the incidence of foot ulceration. Furthermore, noninvasive assessment of tissue viability around already formed ulcers could inform the diabetes caregiver about the severity of the wound and help assess the need for amputation. This article reviews how hyperspectral imaging between 450 and 700 nm can be used to assess the risk of diabetic foot ulcer development and to predict the likelihood of healing noninvasively. Two methods are described to analyze the in vivo hyperspectral measurements. The first method is based on the modified Beer-Lambert law and produces a map of oxyhemoglobin and deoxyhemoglobin concentrations in the dermis of the foot. The second is based on a two-layer optical model of skin and can retrieve not only oxyhemoglobin and deoxyhemoglobin concentrations but also epidermal thickness and melanin concentration along with skin scattering properties. It can detect changes in the diabetic foot and help predict and understand ulceration mechanisms. PMID:20920429

Yudovsky, Dmitry; Nouvong, Aksone; Pilon, Laurent

2010-09-01

126

Hyperspectral Imaging in Diabetic Foot Wound Care  

PubMed Central

Diabetic foot ulceration is a major complication of diabetes and afflicts as many as 15 to 25% of type 1 and 2 diabetes patients during their lifetime. If untreated, diabetic foot ulcers may become infected and require total or partial amputation of the affected limb. Early identification of tissue at risk of ulcerating could enable proper preventive care, thereby reducing the incidence of foot ulceration. Furthermore, noninvasive assessment of tissue viability around already formed ulcers could inform the diabetes caregiver about the severity of the wound and help assess the need for amputation. This article reviews how hyperspectral imaging between 450 and 700 nm can be used to assess the risk of diabetic foot ulcer development and to predict the likelihood of healing noninvasively. Two methods are described to analyze the in vivo hyperspectral measurements. The first method is based on the modified Beer-Lambert law and produces a map of oxyhemoglobin and deoxyhemoglobin concentrations in the dermis of the foot. The second is based on a two-layer optical model of skin and can retrieve not only oxyhemoglobin and deoxyhemoglobin concentrations but also epidermal thickness and melanin concentration along with skin scattering properties. It can detect changes in the diabetic foot and help predict and understand ulceration mechanisms. PMID:20920429

Yudovsky, Dmitry; Nouvong, Aksone; Pilon, Laurent

2010-01-01

127

Development of an Integrated Hyperspectral Imager and 3D-Flash LADAR for Terrestrial Characterization  

NASA Astrophysics Data System (ADS)

The characterization of terrestrial ecosystems using remote sensing technology has a long history with using multi-spectral imagers for vegetation classification indices, ecosystem health, and change detection. Traditional multi-band imagers are now being replaced with more advanced hyperspectral imagers, which offer finer spectral resolution and more specific characterization of terrestrial reflectances. Recently, 3- dimensional (3D) imaging technologies, such as radar interferometry and scanning laser rangers, have added a vertical dimensional to the characterization of ecosystems. The combination of hyperspectral imagery with 3D LADAR allows for detailed analysis of terrestrial biomass, health and species identification. Recognizing the need, and the technical feasibility of this type of environmental assessment, the National Research Counsel has advocated two future NASA satellite missions to measure terrestrial ecosystem health and structure, the DESDynI and HyspIRI missions. These programs will orbit synthetic aperture radar, LADAR and hyperspectral imagers. To mitigate program risk it is desirable and prudent to first demonstrate the integration of these instruments on an airborne platform. Although systems developed for separate purposes have been flown on a single aircraft, the requirements and performance of a dual sensor system has not yet been developed nor integrated as a single unit. We demonstrate a development pathway from an aircraft platform with an integrated sensor suite, using a hyperspectral imager and a laser ranger for a comprehensive remote sensing characterization of terrestrial ecology.

Swanson, A. L.; Sandor-Leahy, S.; Shepanski, J.; Wong, C.; Bracikowski, C.; Abelson, L.; Helmlinger, M.; Bauer, D.; Folkman, M.

2009-05-01

128

Detection and correction of bad pixels in hyperspectral sensors  

NASA Astrophysics Data System (ADS)

Hyperspectral sensors may use a 2D array such that one direction across the array is spatial and the other direction is spectral. Any pixels therein having very poor signal-to-noise performance must have their values replaced. Because of the anisotropic nature of information at the array, common image processing techniques should not be used. A bad-pixel replacement algorithm has been developed which uses the information closest in both spectral and spatial sense to obtain a value which has both the spectral and reflectance properties of the adjacent terrain in the image. A simple and fast implementation that `repairs' individual bad pixels or clusters of bad pixels has three steps; the first two steps are done only once: (1) Pixels are flagged as `bad' if their noise level or responsivity fall outside acceptable limits for their spectral channel. (2) For each bad pixel, the minimum-sized surrounding rectangle is determined that has good pixels at all 4 corners and at the 4 edge-points where the row/column of the bad pixel intersect the rectangle boundary (five cases are possible due to bad pixels near an edge or corner of the detector array); the specifications of this rectangle are saved. (3) After a detector data frame has been radiometrically corrected (dark subtraction and gain corrections), the spectral shapes represented by the rectangle edges extending in the dispersion direction are averaged; this shape is then interpolated through the two pixels in the other edges of the rectangle. This algorithm has been implemented for HYDICE.

Kieffer, Hugh H.

1996-11-01

129

Linear mixture analysis-based compression for hyperspectral image analysis  

Microsoft Academic Search

Due to significantly improved spectral resolution produced by hyperspectral sensors, the band-to-band correlation is generally very high and can be removed without loss of crucial information. Data compression is an effective means to eliminate such redundancy resulting from high interband correlation. In hyperspectral imagery, various information comes from different signal sources, which include man-made targets, natural backgrounds, unknown clutters, interferers,

Qian Du; Chein-I Chang

2004-01-01

130

Inspection of poultry skin tumor using hyperspectral fluorescence imaging  

NASA Astrophysics Data System (ADS)

Hyperspectral fluorescence images reveal useful information for detecting skin tumor on poultry carcasses. In this paper, a hyperspectral fluorescence imaging system with fuzzy interference scheme is presented for detecting skin tumors on poultry carcasses. Image samples are obtained from a hyperspectral fluorescence imaging system for 65 spectral bands whose wavelength is ranged from 425(nm) to 711(nm). The approximation component of the level-1 decomposition of discrete wavelet transform is used for processing to reduce a large amount of hyperspectral image data. Features are computed from two spectral bands corresponding to the two peaks of relative fluorescence intensity. A fuzzy interference system with a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses.

Kong, Seong-Gon

2003-04-01

131

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation  

NASA Astrophysics Data System (ADS)

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

132

Food quality assessment by NIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Near infrared reflectance (NIR) spectroscopy is well established in the food industry for rapid compositional analysis of bulk samples. NIR hyperspectral imaging provides new opportunities to measure the spatial distribution of components such as moisture and fat, and to identify and measure specific regions of composite samples. An NIR hyperspectral imaging system has been constructed for food research applications, incorporating a SWIR camera with a cooled 14 bit HgCdTe detector and N25E spectrograph (Specim Ltd, Finland). Samples are scanned in a pushbroom mode using a motorised stage. The system has a spectral resolution of 256 pixels covering a range of 970-2500 nm and a spatial resolution of 320 pixels covering a swathe adjustable from 8 to 300 mm. Images are acquired at a rate of up to 100 lines s-1, enabling samples to be scanned within a few seconds. Data are captured using SpectralCube software (Specim) and analysed using ENVI and IDL (ITT Visual Information Solutions). Several food applications are presented. The strength of individual absorbance bands enables the distribution of particular components to be assessed. Examples are shown for detection of added gluten in wheat flour and to study the effect of processing conditions on fat distribution in chips/French fries. More detailed quantitative calibrations have been developed to study evolution of the moisture distribution in baguettes during storage at different humidities, to assess freshness of fish using measurements of whole cod and fillets, and for prediction of beef quality by identification and separate measurement of lean and fat regions.

Whitworth, Martin B.; Millar, Samuel J.; Chau, Astor

2010-04-01

133

URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR , A. Villa ,  

E-print Network

URBAN AREA PRODUCT SIMULATION FOR THE ENMAP HYPERSPECTRAL SENSOR P. Gamba , A. Villa , , A. Plaza for remote sensing classification, especially in a urban environment. In this work, we will focus on the simulation of urban area environment at a low spatial resolution, comparable to the new hyperspectral sensors

Plaza, Antonio J.

134

Hyperspectral imaging for safety inspection of food and agricultural products  

NASA Astrophysics Data System (ADS)

Development of effective food inspection systems is critical in successful implementation of the hazard analysis and critical control points (HACCP) program. Hyperspectral imaging or imaging spectroscopy, which combines techniques of imaging and spectroscopy to acquire spatial and spectral information simultaneously, has great potential in food quality and safety inspection. This paper reviewed the basic principle and features of hyperspectral imaging and its hardware and software implementation. The potential areas of application for hyperspectral imaging in food quality and safety inspection were identified and its limitations were discussed. A hyperspectral imaging system developed for research in food quality and safety inspection was described. Experiments were performed to acquire hyperspectral images from four classes of poultry carcasses: normal, cadaver, septicemia, and tumor. Noticeable differences in the spectra of the relative reflectance and its second difference in the wavelengths between 430 nm and 900 nm were observed between wholesome and unwholesome carcasses. Differences among the three classes of unwholesome carcasses were also observed from their respective spectra. These results showed that hyperspectral imaging can be an effective tool for safety inspection of poultry carcasses.

Lu, Renfu; Chen, Yud-Ren

1999-01-01

135

Black Beauty's Rainbow: Hyperspectral Imaging of Northwest Africa 7034  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging is used to characterize the first basaltic breccia from Mars, Northwest Africa 7034. Initial results show the spectral character of NWA 7034 is unlike other SNC meteorites and may be more representative of average martian crust.

Cannon, K. M.; Mustard, J. F.; Agee, C. B.; Wilson, J. H.; Greenberger, R. N.

2014-07-01

136

Unsupervised hyperspectral image analysis using independent component analysis (ICA)  

SciTech Connect

In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

S. S. Chiang; I. W. Ginsberg

2000-06-30

137

Extraction of Spectral Channels From Hyperspectral Images for Classification Purposes  

Microsoft Academic Search

This paper proposes a procedure to extract spectral channels of variable bandwidths and spectral positions from the hyperspectral image in such a way as to optimize the accuracy for a specific classification problem. In particular, each spectral channel (\\

Sebastiano B. Serpico; Gabriele Moser

2007-01-01

138

Hyperspectral Image Classification Using Discriminative Dictionary Learning  

NASA Astrophysics Data System (ADS)

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.

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

2014-03-01

139

Standoff detection results with the infrared hyperspectral MoDDIFS sensor  

NASA Astrophysics Data System (ADS)

The passive standoff monitoring of vapor precursors emanating from a location under surveillance can provide relevant information on the nature of products fabrication. Defence Research & Development Canada Valcartier recently completed the development and field-validation of a novel R&D prototype, MoDDIFS (Multi-option Differential Detection and Imaging Fourier Spectrometer), to address this remote sensing application. The proposed methodology combines the clutter suppression efficiency of the differential detection approach with the high spatial resolution provided by the hyperspectral imaging approach. This consists of integrating a differential CATSI-type (Compact ATmospheric Sounding Interferometer) sensor with the imaging capability of the Hyper-Cam infrared imager. The MoDDIFS sensor includes two configuration options, one for remote gas detection, and the other for polarization sensing of surface contaminants. This paper focuses on the infrared spectral detection of gases. A series of measurements done with MoDDIFS on selected laboratory solvents in vapor form are analyzed and discussed.

Fortin, Gilles; Thériault, Jean-Marc; Lacasse, Paul; Bouffard, François; Lavoie, Hugo; Puckrin, Eldon; Desilets, Sylvain; Montembeault, Yan; Farley, Vincent

2012-06-01

140

Improved Scanners for Microscopic Hyperspectral Imaging  

NASA Technical Reports Server (NTRS)

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, the window would be a slit, the CCD would contain a one-dimensional array of pixels, and the objective lens would be moved along an axis perpendicular to the slit to spatially scan the image of the specimen in pushbroom fashion. The image built up by scanning in this case would be an ordinary (non-spectral) image. In another version, the optics of which are depicted in the lower part of the figure, the spatial window would be a slit, the CCD would contain a two-dimensional array of pixels, the slit image would be refocused onto the CCD by a relay-lens pair consisting of a collimating and a focusing lens, and a prism-gratingprism optical spectrometer would be placed between the collimating and focusing lenses. Consequently, the image on the CCD would be spatially resolved along the slit axis and spectrally resolved along the axis perpendicular to the slit. As in the first-mentioned version, the objective lens would be moved along an axis perpendicular to the slit to spatially scan the image of the specimen in pushbroom fashion.

Mao, Chengye

2009-01-01

141

Raman Hyperspectral Imaging of Microfossils: Potential Pitfalls  

PubMed Central

Abstract Initially, Raman spectroscopy was a specialized technique used by vibrational spectroscopists; however, due to rapid advancements in instrumentation and imaging techniques over the last few decades, Raman spectrometers are widely available at many institutions, allowing Raman spectroscopy to become a widespread analytical tool in mineralogy and other geological sciences. Hyperspectral imaging, in particular, has become popular due to the fact that Raman spectroscopy can quickly delineate crystallographic and compositional differences in 2-D and 3-D at the micron scale. Although this rapid growth of applications to the Earth sciences has provided great insight across the geological sciences, the ease of application as the instruments become increasingly automated combined with nonspecialists using this techique has resulted in the propagation of errors and misunderstandings throughout the field. For example, the literature now includes misassigned vibration modes, inappropriate spectral processing techniques, confocal depth of laser penetration incorrectly estimated into opaque crystalline solids, and a misconstrued understanding of the anisotropic nature of sp2 carbons. Key Words: Raman spectroscopy—Raman imaging—Confocal Raman spectroscopy—Disordered sp2 carbons—Hematite—Microfossils. Astrobiology 13, 920–931. PMID:24088070

Olcott Marshall, Alison

2013-01-01

142

Speeding up the MATLAB™ Hyperspectral Image Analysis Toolbox using GPUs and the Jacket Toolbox  

Microsoft Academic Search

The Hyperspectral Image Analysis Toolbox (HIAT) is a MATLABtrade toolbox for the analysis of hyperspectral imagery. HIAT includes a collection of algorithms for processing of hyperspectral and multispectral imagery under the MATLAB environment. The objective of HIAT is to provide a suite of information extraction algorithms to users of hyperspectral and multispectral imagery across different application domains. HIAT has been

Sam uel Rosario-Torres; Miguel Vélez-Reyes

2009-01-01

143

Design and test of an integrated stabilization and navigation system for the Advanced Airborne Hyperspectral Imaging System (AAHIS)  

Microsoft Academic Search

Science and Technology International (STI) has developed an integrated navigation and stabilization system for the Advanced Airborne Hyperspectral Imaging System (AAHIS). The sensor itself operates as a pushbroom imager, covering the wavelengths range from 435 nm to 830 nm with a ground resolution of 0.2 m2 per pixel and a spectral resolution of 182 channels. The system was designed for

Detlev M. Even; Carl Johnson; Joe Fala; Mark A. Voelker; Gregory C. Mooradian; Frederick P. Portigal

1997-01-01

144

Impacts of hyperspectral sensor spectral coverage, sampling and resolution on cross-comparison with broadband sensor for reflective solar bands  

NASA Astrophysics Data System (ADS)

A new generation of hyperspectral imagers requires a much higher absolute accuracy for reflected solar radiation measurements to further improve climate monitoring capabilities. For example, the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission, a future satellite mission led and developed by NASA and partner organizations, is currently considered to consist of two hyperspectral imagers that cover the reflected solar (RS) and infrared radiation. The design of the CLARREO RS instrument operates from 320 to 2300 nm with 4 nm in spectral sampling and 8 nm in spectral resolution. In this study, the sensitivity of spectral coverage, sampling and resolution of the CLARREO RS type instrument is tested for their impacts on integrated radiances using the relative spectral responses (RSR) of existing broadband sensors. As a proxy, our hyperspectral data is based on MODTRAN simulations and SCIAMACHY observations and the RSR data is from those used in MODIS, VIIRS and AVHRR level 1B (L1B) products. The sensitivity is conducted for ocean, forest, desert, snow and cloud.

Wu, Aisheng; Xiong, Xiaoxiong; Wenny, Brian

2013-09-01

145

Band regrouping-based lossless compression of hyperspectral images  

NASA Astrophysics Data System (ADS)

Hyperspectral remote sensing has been widely utilized in high-resolution climate observation, environment monitoring, resource mapping, etc. However, it brings undesirable difficulties for transmission and storage due to the huge amount of the data. Lossless compression has been demonstrated to be an efficient strategy to solve these problems. In this paper, a novel Band Regrouping based Lossless Compression (BRLlC) algorithm is proposed for lossless compression of hyperspectral images. The affinity propagation clustering algorithm, which can achieve adaptive clustering with high efficiency, is firstly applied to classify all of the hyperspectral bands into several groups based on the inter-band correlation matrix of hyperspectral images. Consequently, hyperspectral bands with high correlation are clustered into one group so that the prediction efficiency in each group can be greatly enhanced. In addition, a linear prediction algorithm based on context prediction is applied to the hyperspectral images in each group followed by arithmetic coding. Experimental results demonstrate that the proposed algorithm outperforms some classic lossless compression algorithms in terms of bit per pixel per band and in terms of processing performance.

He, Mingyi; Bai, Lin; Dai, Yuchao; Zhang, Jing

2010-12-01

146

Utilizing fluorescence hyperspectral imaging to differentiate corn inoculated with toxigenic and atoxigenic fungal strains  

NASA Astrophysics Data System (ADS)

Naturally occurring Aspergillus flavus strains can be either toxigenic or atoxigenic, indicating their ability to produce aflatoxin or not, under specific conditions. Corn contaminated with toxigenic strains of A. flavus can result in great losses to the agricultural industry and pose threats to public health. Past research showed that fluorescence hyperspectral imaging could be a potential tool for rapid and non-invasive detection of aflatoxin contaminated corn. The objective of the current study was to assess, with the use of a hyperspectral sensor, the difference in fluorescence emission between corn kernels inoculated with toxigenic and atoxigenic inoculums of A. flavus. Corn ears were inoculated with AF13, a toxigenic strain of A. flavus, and AF38, an atoxigenic strain of A. flavus, at dough stage of development and harvested 8 weeks after inoculation. After harvest, single corn kernels were divided into three groups prior to imaging: control, adjacent, and glowing. Both sides of the kernel, germplasm and endosperm, were imaged separately using a fluorescence hyperspectral imaging system. It was found that the classification accuracies of the three manually designated groups were not promising. However, the separation of corn kernels based on different fungal inoculums yielded better results. The best result was achieved with the germplasm side of the corn kernels. Results are expected to enhance the potential of fluorescence hyperspectral imaging for the detection of aflatoxin contaminated corn.

Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Brown, Robert L.; Bhatnagar, Deepak; Cleveland, Thomas E.

2012-05-01

147

Snapshot dual-band visible hyperspectral imaging spectrometer  

E-print Network

. The manifestation of an imaging spectrometer is the creation of a data cube. A data cube is a three provide a monochromatic image of the scene, whereas a spatial location in the data cube at a particular xSnapshot dual-band visible hyperspectral imaging spectrometer John Hartke, MEMBER SPIE United

Dereniak, Eustace L.

148

Georegistration of airborne hyperspectral image data  

Microsoft Academic Search

A suite of geometric sensor and platform modeling tools has been developed which have achieved consistent subpixel accuracy in orthorectification experiments. Aircraft platforms in turbulent atmospheric conditions present unique challenges and have required creative modeling approaches. The geometric relationship between an image point and a ground object has been modeled by rigorous photogrammetric methods. First and second order Gauss-Markov processes

Changno Lee; James Bethel

2001-01-01

149

Dynamic Scene Generation, Multimodal Sensor Design, and Target Tracking Demonstration for Hyperspectral/Polarimetric  

E-print Network

for Hyperspectral/Polarimetric Performance-Driven Sensing Michael D. Presnarab , Alan D. Raisanenc , David R tracking has been demonstrated using hyperspectral and polarimetric imagery (HSI/PI). Synthetic HSI. Video streams of sensor-reaching radiance frames collected from a virtual orbiting aerial platform

Kerekes, John

150

Localized processing for hyperspectral image analysis  

NASA Astrophysics Data System (ADS)

Target detection is one of the major tasks in hyperspectral image analysis. Constrained Energy Minimization (CEM) is a popular technique for target detection. It designs a finite impulse response filter in such a manner that the filter output energy is minimized subject to a constraint imposed by the desired target of interest. It is particular useful when only the desired target signature is available. When those undesired signatures to be eliminated are also known, Target Constrained Interference Minimization Filter (TCIMF) can be used to minimize the output of undesired signatures to further improve the performance. It has been demonstrated that TCIMF can better differentiate targets with similar spectral signatures. Both CEM and TCIMF involve the calculation of the data sample correlation matrix R and its inverse matrix R-1. The function of R-1 is background suppression. When the target to be detected is very small and embedded at the sub-pixel level, it is difficult to detect it. But if the data sample correlation matrix R can well present the statistics of the background surrounding the pixel containing the object such that R-1 can well suppress the background, the target may still have a chance to be detected. So in this paper we propose a localized processing technique. Instead of using all the pixels in an image scene to calculate the R, only several lines of pixels near the pixel to be processed are used for the R computation. The preliminary result using an HYDICE image scene demonstrates the effectiveness of such a localized processing technique in the detection of targets at sub-pixel level. Interestingly, in some cases it can also improve the performance of CEM in target discrimination.

Du, Qian

2004-12-01

151

In vivo and in vitro hyperspectral imaging of cervical neoplasia  

NASA Astrophysics Data System (ADS)

Cervical cancer is a prevalent disease in many developing countries. Colposcopy is the most common approach for screening cervical intraepithelial neoplasia (CIN). However, its clinical efficacy heavily relies on the examiner's experience. Spectroscopy is a potentially effective method for noninvasive diagnosis of cervical neoplasia. In this paper, we introduce a hyperspectral imaging technique for noninvasive detection and quantitative analysis of cervical neoplasia. A hyperspectral camera is used to collect the reflectance images of the entire cervix under xenon lamp illumination, followed by standard colposcopy examination and cervical tissue biopsy at both normal and abnormal sites in different quadrants. The collected reflectance data are calibrated and the hyperspectral signals are extracted. Further spectral analysis and image processing works are carried out to classify tissue into different types based on the spectral characteristics at different stages of cervical intraepithelial neoplasia. The hyperspectral camera is also coupled with a lab microscope to acquire the hyperspectral transmittance images of the pathological slides. The in vivo and the in vitro imaging results are compared with clinical findings to assess the accuracy and efficacy of the method.

Wang, Chaojian; Zheng, Wenli; Bu, Yanggao; Chang, Shufang; Tong, Qingping; Zhang, Shiwu; Xu, Ronald X.

2014-02-01

152

Hyperspectral retinal imaging with a spectrally tunable light source  

NASA Astrophysics Data System (ADS)

Hyperspectral retinal imaging can measure oxygenation and identify areas of ischemia in human patients, but the devices used by current researchers are inflexible in spatial and spectral resolution. We have developed a flexible research prototype consisting of a DLP®-based spectrally tunable light source coupled to a fundus camera to quickly explore the effects of spatial resolution, spectral resolution, and spectral range on hyperspectral imaging of the retina. The goal of this prototype is to (1) identify spectral and spatial regions of interest for early diagnosis of diseases such as glaucoma, age-related macular degeneration (AMD), and diabetic retinopathy (DR); and (2) define required specifications for commercial products. In this paper, we describe the challenges and advantages of using a spectrally tunable light source for hyperspectral retinal imaging, present clinical results of initial imaging sessions, and describe how this research can be leveraged into specifying a commercial product.

Francis, Robert P.; Zuzak, Karel J.; Ufret-Vincenty, Rafael

2011-03-01

153

Effects of light pollution revealed during a nocturnal aerial survey by two hyperspectral imagers  

Microsoft Academic Search

A remote-sensing campaign was performed in September 2001 at nighttime under clear-sky conditions before moonrise to assess the level of light pollution of urban and industrial origin. Two hyperspectral sensors, namely, the Multispectral Infrared and Visible Imaging Spectrometer and the Visible Infrared Scanner-200, which provide spectral coverage from the visible to the thermal infrared, were flown over the Tuscany coast

Alessandro Barducci; Paolo Marcoionni; Ivan Pippi; Marco Poggesi

2003-01-01

154

3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes  

E-print Network

3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes Fuan Tsai, Chun-Kai Chang of two remote sens- ing hyperspectral image cubes and comparing their performance with conventional GLCM co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image

Tsai, Fuan "Alfonso"

155

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach  

NASA Astrophysics Data System (ADS)

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Jazaeri, Amin

156

Distributed source separation algorithms for hyperspectral image processing  

NASA Astrophysics Data System (ADS)

This paper describes a new algorithm for feature extraction on hyperspectral images based on blind source separation (BSS) and distributed processing. I use Independent Component Analysis (ICA), a particular case of BSS, where, given a linear mixture of statistical independent sources, the goal is to recover these components by producing the unmixing matrix. In the multispectral/hyperspectral imagery, the separated components can be associated with features present in the image, the source separation algorithm projecting them in different image bands. ICA based methods have been employed for target detection and classification of hyperspectral images. However, these methods involve an iterative optimization process. When applied to hyperspectral data, this iteration results in significant execution times. The time efficiency of the method is improved by running it on a distributed environment while preserving the accuracy of the results. The design of the distributed algorithm as well as issues related to the distributed modeling of the hyperspectral data were taken in consideration and presented. The effectiveness of the proposed algorithm has been tested by comparison to the sequential source separation algorithm using data from AVIRIS and HYDICE. Preliminary results indicate that, while the accuracy of the results is preserved, the new algorithm provides a considerable speed-up in processing.

Robila, Stefan A.

2004-08-01

157

Efficient interactive agglomerative hierarchical clustering algorithm for hyperspectral image processing  

NASA Astrophysics Data System (ADS)

Traditional hierarchical clustering algorithms require the calculation of a dissimilarity matrix which is mapped to a binary tree or 'dendogram' based upon some predetermined criterion. Although 'optimally efficient' algorithms requiring O(N2) time and O(N) storage are known for several clustering methods, with few exceptions these algorithms are relatively inefficient in practice as many pairwise distance are measured which are not necessary for generation of the binary tree. We describe here a novel 'almost single link' algorithm which is efficient both theoretically and in practice, and which can be extended to provide fast algorithms for centroid, medium and single link clustering of large data sets. Generalization to other related clustering methods is expected to be straightforward. Our algorithm also suggests a fairly efficient method for generating minimal spanning trees. In performing the segmentation we employ a particular representation of the binary tree which simplifies the task of manual investigation of the hierarchy. A customized graphical user interface including a 2D scatter plot, a visual display of the dendogram, and a false color image with overlayered clusters makes the clustering procedure a highly interactive one. By suggesting, for each of the clustering methods, possible criteria which might be useful for extracting relevant clusters from the tree information, we are able to fully automate the cluster selection procedure and thereby further reduce the effort required to segment an image. The algorithms described have been transcribed into C code and combined into a single package, the 'hierarchical agglomerative clusterer', which has been applied to the analysis of hyperspectral image data of various forest and desert scenes acquired by the HYDICE sensor. The analyses were performed on a 266 Mhz Pentium PC platform running Windows NT 4.0. Typical segmentation times for the fastest algorithm ranged form 17 seconds for a 15232-pixel image to 2833 seconds for a 209840-pixel image, each pixel representing a 210-band spectrum. These initial studies suggest that the HAC package will provide a sound framework for making detailed comparisons of the effects of different clustering algorithms or dissimilarity measures. Its overall speed makes it a promising tool not only for hyperspectral image processing applications but for multivariate data analysis as a whole.

Rahman, Sabbir A.

1998-10-01

158

Target Detection in Hyperspectral Images Based on Independent Component Analysis  

Microsoft Academic Search

ABSTRACT The paper presents an algorithm ,based on Independent ,Component ,Analysis (ICA) for the detection of small ,targets present in hyperspectral images. ICA is a multivariate data analysis ,method ,that attempts to produce ,statistically independent components. This method is based on fourth order statistics. Small, man-made targets in a natural background,can be seen as anomalies in the image scene and

S Robila; P Varshney

2002-01-01

159

[Hyperspectral image compression technology research based on EZW].  

PubMed

Along with the development of hyperspectral remote sensing technology, hyperspectral imaging technology has been applied in the aspect of aviation and spaceflight, which is different from multispectral imaging, and with the band width of nanoscale spectral imaging the target continuously, the image resolution is very high. However, with the increasing number of band, spectral data quantity will be more and more, and these data storage and transmission is the problem that the authors must face. Along with the development of wavelet compression technology, in field of image compression, many people adopted and improved EZW, the present paper used the method in hyperspectral spatial dimension compression, but does not involved the spectrum dimension compression. From hyperspectral image compression reconstruction results, whether from the peak signal-to-noise ratio (PSNR) and spectral curve or from the subjective comparison of source and reconstruction image, the effect is well. If the first compression of image from spectrum dimension is made, then compression on space dimension, the authors believe the effect will be better. PMID:22007434

Wei, Jun-Xia; Xiangli, Bin; Duan, Xiao-Feng; Xu, Zhao-Hui; Xue, Li-Jun

2011-08-01

160

Hyperspectral Imaging with Stimulated Raman Scattering by Chirped Femtosecond Lasers  

E-print Network

Hyperspectral Imaging with Stimulated Raman Scattering by Chirped Femtosecond Lasers Dan Fu, Gary imaging system using chirped femtosecond lasers to achieve rapid Raman spectra acquisition while retaining laser beams with an energy difference tuned to the vibrational frequency of the molecule of interest

Xie, Xiaoliang Sunney

161

Optimal Segmentation Strategy for Compact Representation of Hyperspectral Image Cubes  

Microsoft Academic Search

By producing compact representations of hyperspectral image cubes (hypercubes), image storage requirements and the amount of time it takes to extract essential elements of information can both be dramatically reduced. However, these compact representations must preserve the important spectral features within hypercube pixels and the spatial structure associated with background and objects or phenomena of interest. This paper describes a

D Paglieroni; R Roberts

2000-01-01

162

Content-based hyperspectral image retrieval using spectral unmixing  

NASA Astrophysics Data System (ADS)

The purpose of content-based image retrieval (CBIR) is to retrieve, from real data stored in a database, information that is relevant to a query. A major challenge for the development of efficient CBIR systems in the context of hyperspectral remote sensing applications is how to deal with the extremely large volumes of data produced by current Earth-observing (EO) imaging spectrometers. The data resulting from EO campaigns often comprises many Gigabytes per flight. When multiple instruments or timelines are combined, this leads to the collection of massive amounts of data coming from heterogeneous sources, and these data sets need to be effectively stored, managed, shared and retrieved. Furthermore, the growth in size and number of hyperspectral data archives demands more sophisticated search capabilities to allow users to locate and reuse data acquired in the past. In this paper we develop a new strategy to effectively retrieve hyperspectral image data sets using spectral unmixing concepts. Spectral unmixing is a very important task for hyperspectral data exploitation since the spectral signatures collected in natural environments are invariably a mixture of the pure signatures of the various materials found within the spatial extent of the ground instantaneous field view of the imaging instrument. In this work, we use the information provided by spectral unmixing (i.e. the spectral endmembers and their corresponding abundances in the scene) as effective meta-data to develop a new CBIR system that can assist users in the task of efficiently searching hyperspectral image instances in large data repositories. The proposed approach is validated using a collection of 154 hyperspectral data sets (comprising seven full flightlines) gathered by NASA using the Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center (WTC) area in New York City during the last two weeks of September, 2001, only a few days after the terrorist attacks that collapsed the two main towers and other buildings in the WTC complex.

Plaza, Antonio J.

2011-11-01

163

A new morphological anomaly detection algorithm for hyperspectral images and its GPU implementation  

NASA Astrophysics Data System (ADS)

Anomaly detection is considered a very important task for hyperspectral data exploitation. It is now routinely applied in many application domains, including defence and intelligence, public safety, precision agriculture, geology, or forestry. Many of these applications require timely responses for swift decisions which depend upon high computing performance of algorithm analysis. However, with the recent explosion in the amount and dimensionality of hyperspectral imagery, this problem calls for the incorporation of parallel computing techniques. In the past, clusters of computers have offered an attractive solution for fast anomaly detection in hyperspectral data sets already transmitted to Earth. However, these systems are expensive and difficult to adapt to on-board data processing scenarios, in which low-weight and low-power integrated components are essential to reduce mission payload and obtain analysis results in (near) real-time, i.e., at the same time as the data is collected by the sensor. An exciting new development in the field of commodity computing is the emergence of commodity graphics processing units (GPUs), which can now bridge the gap towards on-board processing of remotely sensed hyperspectral data. In this paper, we develop a new morphological algorithm for anomaly detection in hyperspectral images along with an efficient GPU implementation of the algorithm. The algorithm is implemented on latest-generation GPU architectures, and evaluated with regards to other anomaly detection algorithms using hyperspectral data collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the World Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in the WTC complex. The proposed GPU implementation achieves real-time performance in the considered case study.

Paz, Abel; Plaza, Antonio

2011-10-01

164

Applying region growing algorithm to hyperspectral image for oil segmentation  

NASA Astrophysics Data System (ADS)

Region growing is one of the popular segmentation algorithms for 2-D image, which comes up a continuous interested region. How to extent this method to hyperspectral image processing effectively is a problem needs to be discussed deeply. Here in this paper, three ways of using region growing in hyperspectral scenario are explored to separate oil from sea water. Furthermore, in order to release the influence of sunlight, a modification to growing rule is prompted, considering the property of local region. At last, a normalized ATGP is used to obtain more potential target. The experiment results show that combining unmixing techniques with region growing is better than other methods.

Song, Mei-ping; Xu, Xing-wei; Lu, Shuangyang; Xu, Wei; Bao, Hai-mo

2014-05-01

165

Development of a compressive sampling hyperspectral imager prototype  

NASA Astrophysics Data System (ADS)

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".

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

2013-10-01

166

SHARE 2012: large edge targets for hyperspectral imaging applications  

NASA Astrophysics Data System (ADS)

Spectral unmixing is a type of hyperspectral imagery (HSI) sub-pixel analysis where the constituent spectra and abundances within the pixel are identified. However, validating the results obtained from spectral unmixing is very difficult due to a lack of real-world data and ground-truth information associated with these real-world images. Real HSI data is preferred for validating spectral unmixing, but when there is no HSI truth-data available, then validation of spectral unmixing algorithms relies on user-defined synthetic images which can be generated to exploit the benefits (or hide the flaws) in the new unmixing approaches. Here we introduce a new dataset (SHARE 2012: large edge targets) for the validation of spectral unmixing algorithms. The SHARE 2012 large edge targets are uniform 9m by 9m square regions of a single material (grass, sand, black felt, or white TyVek). The spectral profile and the GPS of the corners of the materials were recorded so that the heading of the edge separating any two materials can be determined from the imagery. An estimate for the abundance of two neighboring materials along a common edge can be calculated geometrically by identifying the edge which spans multiple pixels. These geometrically calculated abundances can then be used as validation of spectral unmixing algorithms. The size, shape, and spectral profiles of these targets also make them useful for radiometric calibration, atmospheric adjacency effects, and sensor MTF calculations. The imagery and ground-truth information are presented here.

Canham, Kelly; Goldberg, Daniel; Kerekes, John; Raqueno, Nina; Messinger, David

2013-05-01

167

Advances in Spectral-Spatial Classification of Hyperspectral Images  

NASA Technical Reports Server (NTRS)

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

168

Hyperspectral imaging of an inter-coastal waterway  

NASA Astrophysics Data System (ADS)

This paper demonstrates the characterization of the water properties, bathymetry, and bottom type of the Indian River Lagoon (IRL) on the eastern coast of Florida using hyperspectral imagery. Images of this region were collected from an aircraft in July 2004 using the Portable Hyperspectral Imager for Low Light Spectroscopy (PHILLS). PHILLS is a Visible Near InfraRed (VNIR) spectrometer that was operated at an altitude of 3000 m providing 4 m resolution with 128 bands from 400 to 1000 nm. The IRL is a well studied water body that receives fresh water drainage from the Florida Everglades and also tidal driven flushing of ocean water through several outlets in the barrier islands. Ground truth measurements of the bathymetry of IRL were acquired from recent sonar and LIDAR bathymetry maps as well as water quality studies concurrent to the hyperspectral data collections. From these measurements, bottom types are known to include sea grass, various algae, and a gray mud with water depths less than 6 m over most of the lagoon. Suspended sediments are significant (~35 mg/m3) with chlorophyll levels less than 10 mg/m3 while the absorption due to Colored Dissolved Organic Matter (CDOM) is less than 1 m-1 at 440 nm. Hyperspectral data were atmospherically corrected using an NRL software package called Tafkaa and then subjected to a Look-Up Table (LUT) approach which matches hyperspectral data to calculated spectra with known values for bathymetry, suspended sediments, chlorophyll, CDOM, and bottom type.

Bowles, Jeffrey H.; Maness, Shelia J.; Chen, Wei; Davis, Curtiss O.; Donato, Tim F.; Gillis, David B.; Korwan, Daniel; Lamela, Gia; Montes, Marcos J.; Rhea, W. Joseph; Snyder, William A.

2005-10-01

169

Dynamic scene generation, multimodal sensor design, and target tracking demonstration for hyperspectral/polarimetric performance-driven sensing  

NASA Astrophysics Data System (ADS)

Simulation of moving vehicle tracking has been demonstrated using hyperspectral and polarimetric imagery (HSI/PI). Synthetic HSI/PI image cubes of an urban scene containing moving vehicle content were generated using the Rochester Institute of Technology's Digital Imaging and Remote Sensing Image Generation (DIRSIG) Megascene #1 model. Video streams of sensor-reaching radiance frames collected from a virtual orbiting aerial platform's imaging sensor were used to test adaptive sensor designs in a target tracking application. A hybrid division-of-focal-plane imaging sensor boasting an array of 2×2 superpixels containing both micromirrors and micropolarizers was designed for co-registered HSI/PI aerial remote sensing. Pixel-sized aluminum wire-grid linear polarizers were designed and simulated to measure transmittance, extinction ratio, and diattenuation responses in the presence of an electric field. Wire-grid spacings of 500 [nm] and 80 [nm] were designed for lithographic deposition and etching processes. Both micromirror-relayed panchromatic imagery and micropolarizer-collected PI were orthorectified and then processed by Numerica Corporation's feature-aided target tracker to perform multimodal adaptive performance-driven sensing of moving vehicle targets. Hyperspectral responses of selected target pixels were measured using micromirror-commanded slits to bolster track performance. Unified end-to-end track performance case studies were completed using both panchromatic and degree of linear polarization sensor modes.

Presnar, Michael D.; Raisanen, Alan D.; Pogorzala, David R.; Kerekes, John P.; Rice, Andrew C.

2010-04-01

170

Image multispectral sensing: a new and innovative instrument for hyperspectral imaging using dispersive techniques  

NASA Astrophysics Data System (ADS)

IMSS utilizes a very simple optical design that enables a robust and low cost hyperspectral imaging instrument. This technology was developed under a phase II SBIR with the Air Force Philips Lab. (Dr. Paul LeVan), for the midwave IR to perform clutter rejection and target identification based upon IR spectral signatures. The prototype instrument has been field tested on numerous occasions and successfully measured background, aircraft, and misile plume spectra. PAT currently has several contracts to commercialize this technology both for the DoD and the commercial market. Under contract to the BMDO, (Paul McCarley), with matching funds from Amber Engineering, we are developing an F/2.3 system that will be sold by Amber Engineering as an accessory to the Radiance 1 camera. PAT is also under contract with ONR (Mr. Jim Buss), to develop a longwave IR version of IMSS as well as an MWIR version tuned to operate as a 'little sister sensor for target identification' for the Navy's IRST's. The purpose of this paper is to briefly describe the hyperspectral image data that was collected in the field at Long Jump '94, and Santa Ynez Peak using IMSS prototype hyperspectral imager. Examples of spectral images, as well as spectra of different aircraft at various ranges, power settings, and aspect angles, an Atlas liquid hydrocarbon burning missile, and a solid beester. All data presented in this paper are a result of a single spectral scan. The limitation in digital storage of the prototype system do not allow multiple scans in order to improve signal to noise. In spite of this limitation, the performance of the prototype system has proven to be excellent.

Hinnrichs, Michele; Massie, Mark A.

1995-06-01

171

Hyperspectral Image Analysis for Precision Viticulture  

E-print Network

classification allowed the discrimination of two varieties: Cabernet Sauvignon and Shiraz. Good classification authors have investigated the capability of remote sensed hyperspectral data for grape variety mapping [7, 8]. At the vineyard level, there is a need for grape variety discrimination as a useful tool

Paris-Sud XI, Université de

172

Analysis of hyperspectral fluorescence images for poultry skin tumor inspection  

NASA Astrophysics Data System (ADS)

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.

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

2004-02-01

173

Hyperspectral imaging from a light-weight (up to 75 kg) unmanned aerial vehicle platform  

NASA Astrophysics Data System (ADS)

Since 2009 the Idaho National Lab (INL) has been developing advanced remote sensing capabilities that combine increasingly sophisticated miniaturized sensors with relatively affordable, light weight (under 75 kg) unmanned aerial vehicles (UAVs). UAV-based hyperspectral sensing capabilities have been routinely refined via flight tests conducted at INL's UAV Runway Research Park in southeastern Idaho, and at the Orchard Training Area in central Idaho. Idaho State University (ISU) Boise Center Aerospace Lab (BCAL) has provided field data collection and image processing support to target ground versus aerial data comparisons, assess spectral and geometric data accuracy and determine classification algorithms appropriate for vegetation management applications. We report instrumentation, sensor and image validation results, optimal flight parameters, and methods for improving the geometric accuracies of the datasets. We also assess the accuracy of narrowband vegetation indices and shrub cover estimates derived from the imagery. Preliminary results indicate that the UAV-based hyperspectral imaging system has potential to bridge the gap between costly in-situ data collections, coarse resolution satellite data collections, or infrequent and costly manned hyperspectral data collections. Furthermore, new areas of research may be possible with this UAV platform by providing an affordable, on-demand platform that can rapidly collect transect data and stay on station for hours.

Mitchell, J.; Hruska, R.; Anderson, M.; Glenn, N. F.

2011-12-01

174

Fast processing spectral discrimination for hyperspectral imagers based on interferometry  

NASA Astrophysics Data System (ADS)

Hyperspectral imagers based on interferometry associate with each pixel of the image the spectrum calculated with the Fourier transform of the measured interferogram. This class of hyperspectral imagers is intrinsically faster than imagers based on optical filters and on dispersive means when the noise is dominated by detector noise. This speed advantage could be hampered by the large computing power necessary to extract the spectral content of the image from the large number of data acquired by the camera. We have realized a real-time algorithm to discriminate different spectra of the pixels of a scene directly from the acquired interferograms. The technique showed very good discrimination of pixels illuminated by narrow band radiation. This algorithm is based on principal component analysis and could be implemented directly in the camera processor to discriminate spectra in the image in real time using factorization with singular value decomposition.

Zucco, M.; Pisani, M.

2014-05-01

175

Hyperspectral Imaging Applied to Medical Diagnoses and Food Safety  

Microsoft Academic Search

This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than

Oscar Carrasco; Richard Gomez; Arun Chainani; William Roper

176

Hyperspectral imaging applied to medical diagnoses and food safety  

Microsoft Academic Search

This paper analyzes the feasibility and performance of HSI systems for medical diagnosis as well as for food safety. Illness prevention and early disease detection are key elements for maintaining good health. Health care practitioners worldwide rely on innovative electronic devices to accurately identify disease. Hyperspectral imaging (HSI) is an emerging technique that may provide a less invasive procedure than

Oscar Carrasco; Richard B. Gomez; Arun Chainani; William E. Roper

2003-01-01

177

Multispectral and hyperspectral image analysis with convex cones  

Microsoft Academic Search

A new approach to multispectral and hyperspectral image analysis is presented. This method, called convex cone analysis (CCA), is based on the bet that some physical quantities such as radiance are nonnegative. The vectors formed by discrete radiance spectra are linear combinations of nonnegative components, and they lie inside a nonnegative, convex region. The object of CCA is to find

Agustin Ifarraguerri; Chein-I Chang

1999-01-01

178

Hyperspectral Imaging Experiments in Preparation for Upcoming Mars Surface Missions  

NASA Technical Reports Server (NTRS)

We present several infrared hyperspectral images acquired from the perspective of a rover or lander, similar to those that will be acquired from the Mars Surveyor 2001, 2003, and 2005 missions. Super-resolution techniques are used to enhance detail in the scenes observed.

Moersch, J. E.; Roush, T. L.; Farmer, J.

2000-01-01

179

Portable hyperspectral imager for assessment of skin disorders: preliminary measurements  

NASA Astrophysics Data System (ADS)

Oxygenation of the facial skin was evaluated in rosacea using a hyperspectral camera. A portable imaging system utilizing crossed-polarization optics for illumination and recording is described. Relative oxygen saturation was determined from rosacea features and compared with normal skin. Saturation maps and light absorption spectra showed a significant increase in the oxygen saturation of the blood in rosacea-affected skin.

Beach, James M.; Lanoue, Mark A.; Brabham, Kori; Khoobehi, Bahram

2005-04-01

180

Visible Hyperspectral Imaging for Standoff Detection of Explosives on Surfaces  

SciTech Connect

There is an ever-increasing need to be able to detect the presence of explosives, preferably from standoff distances. This paper presents an application of visible hyperspectral imaging using anomaly, polarization and spectral identification approaches for the standoff detection (13 meters) of nitroaromatic explosives on realistic painted surfaces based upon the colorimetric differences between tetryl and TNT which are enhanced by solar irradiation.

Bernacki, Bruce E.; Blake, Thomas A.; Mendoza, Albert; Johnson, Timothy J.

2010-11-01

181

Notes on reconstructing the data cube in hyperspectral image processing  

Microsoft Academic Search

The hyperspectral imaging technique described in (12) leads to the inter- esting problem of reconstructing a three-dimensional data cube from measured data. This problem involves three separate steps in which we must estimate values of a function from values of its Fourier transform. Depending on which of the two functions involved at each step has bounded support, that is, is

Charles Byrne

182

The use of hyperspectral imaging (HSI) in wound healing  

NASA Astrophysics Data System (ADS)

A hyperspectral imaging system (HsI), described previously, was utilized to evaluate and monitor wounds and their healing surgery and post-operatively. Briefly, the system consists of a DLP® based spectral light modulator providing active spectral illumination that is synchronized with a digital focal plan array for collecting spectroscopic images that are processed for mapping the percentage of oxyhemoglobin at each detector pixel non-invasively and at near video rates ~8 chemically encode images per second.

La Fontaine, Javier; Lavery, Lawrence; Zuzak, Karel

2014-03-01

183

Hyperspectral enhanced dark field microscopy for imaging blood cells.  

PubMed

In this work, a novel methodology based on hyperspectral imagery with enhanced Darkfield microscopy for probing and characterizing changes in blood cell components was tested. Two main categories of blood cells were analyzed, red and white blood cells. Unique spectral signatures of ordinary and most common deformed morphologies of red blood cells were identified. Moreover, examination of white blood cells allowed to characterize and differentiate active from inactive cells. The findings indicate the ability of this technique to detect changes in light scattering property of blood cells due to their morphological properties Since pathological states can alterate the discocyte shape, this preliminary, but promising application of the hyperspectral analysis to blood cells can be useful to evaluate significant correlations of blood cell spectral features in healthy and pathological conditions. The combination of the quali- and quantitative spectral signatures of hyperspectral imaging microscopy with the information of the subject health conditions may provide a new tool for clinical applications. PMID:23913514

Verebes, Giulia Sacco; Melchiorre, Michele; Garcia-Leis, Adianez; Ferreri, Carla; Marzetti, Carla; Torreggiani, Armida

2013-12-01

184

Classification of hyperspectral remote sensing image based on genetic algorithm and SVM  

NASA Astrophysics Data System (ADS)

Hyperspectral remote sensing data has been widely used in Terrain Classification for its high resolution. The classification of urban vegetation, identified as an indispensable and essential part of urban development system, is now facing a major challenge as different complex land-cover classes having similar spectral signatures. For a better accuracy in classification of urban vegetation, a classifier model was designed in this paper based on genetic algorithm (GA) and support vector machine (SVM) to address the multiclass problem, and tests were made with the classification of PHI hyperspectral remote sensing images acquired in 2003 which partially covers a corner of the Shanghai World Exposition Park, while PHI is a hyper-spectral sensor developed by Shanghai Institute of Technical Physics. SVM, based on statistical learning theory and structural risk minimization, is now widely used in classification in many fields such as two-class classification, and also the multi-class classification later due to its superior performance. On the other hand as parameters are very important factors affecting SVM's ability in classification, therefore, how to choose the optimal parameters turned out to be one of the most urgent problems. In this paper, GA was used to acquire the optimal parameters with following 3 steps. Firstly, useful training samples were selected according to the features of hyperspectral images, to build the classifier model by applying radial basis function (RBF) kernel function and decision Directed Acyclic Graph (DAG) strategy. Secondly, GA was introduced to optimize the parameters of SVM classification model based on the gridsearch and Bayesian algorithm. Lastly, the proposed GA-SVM model was tested for results' accuracy comparison with the maximum likelihood estimation and neural network model. Experimental results showed that GA-SVM model performed better classified accuracy, indicating the coupling of GA and SVM model could improve classification accuracy of hyperspectral remote sensing images, especially in vegetation classification.

Zhou, Mandi; Shu, Jiong; Chen, Zhigang

2010-08-01

185

Hyperspectral imaging applied to end-of-life concrete recycling  

NASA Astrophysics Data System (ADS)

In this paper a new technology, based on HyperSpectral Imaging (HSI) sensors, and related detection architectures, is investigated in order to develop suitable and low cost strategies addressed to: i) preliminary detection and characterization of the composition of the structure to dismantle and ii) definition and implementation of innovative smart detection engines for sorting and/or demolition waste flow stream quality control. The proposed sensing architecture is fast, accurate, affordable and it can strongly contribute to bring down the economic threshold above which recycling is cost efficient. Investigations have been carried out utilizing an HSI device working in the range 1000-1700 nm: NIR Spectral Camera™, embedding an ImSpector™ N17E (SPECIM Ltd, Finland). Spectral data analysis was carried out utilizing the PLS_Toolbox (Version 6.5.1, Eigenvector Research, Inc.) running inside Matlab® (Version 7.11.1, The Mathworks, Inc.), applying different chemometric techniques, selected depending on the materials under investigation. The developed procedure allows assessing the characteristics, in terms of materials identification, such as recycled aggregates and related contaminants, as resulting from end-of-life concrete processing. A good classification of the different classes of material was obtained, being the model able to distinguish aggregates from other materials (i.e. glass, plastic, tiles, paper, cardboard, wood, brick, gypsum, etc.).

Serranti, Silvia; Bonifazi, Giuseppe

2014-03-01

186

CMOS image sensors  

Microsoft Academic Search

In this article, we provide a basic introduction to CMOS image-sensor technology, design and performance limits and present recent developments and future directions in this area. We also discuss image-sensor operation and describe the most popular CMOS image-sensor architectures. We note the main non-idealities that limit CMOS image sensor performance, and specify several key performance measures. One of the most

A. El Gamal; H. Eltoukhy

2005-01-01

187

Development of an Integrated Hyperspectral Imager and 3D-Flash Lidar for Terrestrial Characterization  

NASA Astrophysics Data System (ADS)

The characterization of terrestrial ecosystems using remote sensing technology has a long history with using multi-spectral imagers for vegetation classification indices, ecosystem health, and change detection. Traditional multi-band imagers are now being replaced with more advanced hyperspectral imagers, which offer finer spectral resolution and more specific characterization of terrestrial reflectances. Recently, 3-dimensional (3D) imaging technologies, such as radar interferometry and scanning laser rangers, have added a vertical dimension to the characterization of ecosystems. The combination of hyperspectral imagery with 3D Lidar allows for detailed analysis of terrestrial biomass, health and species identification. Recognizing the need, and the technical feasibility of this type of environmental assessment, the National Research Counsel has advocated two future NASA satellite missions to measure terrestrial ecosystem health and structure, the DESDynI and HyspIRI missions. These programs will orbit synthetic aperture radar, Lidar and a hyperspectral imager. Northrop Grumman has integrated a hyperspectral vis-IR imager and 3D-flash Lidar and flown it on a twin-otter aircraft platform for measurements of terrestrial ecology. The goal of the system is to demonstrate an integrated system design, similar to that flown by Asner et al. on the Carnegie Airborne Observatory, but with a design path to high altitude systems that could offer pathfinders for an operational satellite system. Lidar systems are typically limited to either low altitude small-footprint sampling or higher altitude broad pixel resolution. The Northrop Grumman system goals are to be able to image terrestrial ecosystems at small horizontal resolutions from high altitude, while maintaining a relatively broad swath capability. Performance of the integrated system during collections from the twin-otter will be discussed, as well as design performance for a dual sensor system for high altitude platforms that could offer early development of space based systems.

Abelson, L.; Swanson, A. L.; Sandor-Leahy, S.; Shepanski, J.; Wong, C.; Helmlinger, M.; Folkman, M.

2009-12-01

188

Spectral change space representation for invariant material tracking in hyperspectral images  

Microsoft Academic Search

An invariant material tracking algorithm requires a representation that is unaffected by environmental factors. An airborne hyperspectral sensor measures a radiance spectrum that, in general, will vary with atmospheric conditions and the scene geometry. Material tracking algorithms that directly match hyperspectral sensor measurements are therefore limited under general conditions. In this paper, we develop a low- dimensional subspace representation that

David Slater; Glenn Healey

1999-01-01

189

Hyperspectral image classification by collaboration of spatial and spectral information  

NASA Astrophysics Data System (ADS)

The classification of hyperspectral image data has drawn much attention in recent years. Consequently, it contains not only spectral information of objects, but also spatial arrangement of objects. The most established Hyperspectral classifiers are based on the observed spectral signal, and ignore the spatial relations among observations. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. To combine the spectral and spatial information in the classification process, in this paper, a Multidimensional Local Spatial Autocorrelation (MLSA) is proposed for hyperspectral image data. Based on this measure, a collaborative classification method is proposed, which integrates the spectral and spatial autocorrelation during the decision-making process. The trials of our experiment are conducted on two scenes, one from HYDICE 210-band imagery collected over an area that contains a diverse range of terrain features and the other is toy car hyperspectral image captured at Instrumentation and Sensing Laboratory (ISL) at Beltsville Agricultural Research Center. Quantitative measures of local consistency (smoothness) and global labeling, along with class maps, demonstrate the benefits of applying this method for unsupervised and supervised classification.

Yan, Yu-zhou; Zhao, Yongqiang; Xue, Hui-feng; Kou, Xiao-dong; Liu, Yuanzheng

2009-07-01

190

Hyperspectral image noise reduction based on rank-1 tensor decomposition  

NASA Astrophysics Data System (ADS)

In this study, a novel noise reduction algorithm for hyperspectral imagery (HSI) is proposed based on high-order rank-1 tensor decomposition. The hyperspectral data cube is considered as a three-order tensor that is able to jointly treat both the spatial and spectral modes. Subsequently, the rank-1 tensor decomposition (R1TD) algorithm is applied to the tensor data, which takes into account both the spatial and spectral information of the hyperspectral data cube. A noise-reduced hyperspectral image is then obtained by combining the rank-1 tensors using an eigenvalue intensity sorting and reconstruction technique. Compared with the existing noise reduction methods such as the conventional channel-by-channel approaches and the recently developed multidimensional filter, the spatial-spectral adaptive total variation filter, experiments with both synthetic noisy data and real HSI data reveal that the proposed R1TD algorithm significantly improves the HSI data quality in terms of both visual inspection and image quality indices. The subsequent image classification results further validate the effectiveness of the proposed HSI noise reduction algorithm.

Guo, Xian; Huang, Xin; Zhang, Liangpei; Zhang, Lefei

2013-09-01

191

Detection of camouflaged targets using hyperspectral imaging technology  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging technology shows great potential for detection of camouflaged targets. Hyperspectral imagery provides fully registered high resolution spatial and spectral images that are invaluable in discriminating between camouflaged targets and backgrounds. However, current research on the processing of hyperspectral imagery tends to focus exclusively on spectral dimension, and thus the spatial and spectral information are not treated simultaneously. In order to get the shape of target, we have developed a new method based on mathematical morphology for edge detection in hyperspectal data. On the basis of analysis, spectral angle distance is utilized in extended morphological operations, which combine spectral and spatial information together. Then operator of edge extraction is used to extract the edge of target. Three major contributions are presented for detection of camouflaged targets in the paper. Firstly, in spectral domain, the best wave band to distinguish camouflaged targets and background is obtained by subtracting reflex intensity of targets and background. Secondly, we confirm the effectiveness of spectral angle mapping in detecting camouflaged targets, which lays a foundation for the use of spectral angle distance on the following study. Finally, as the prior knowledge about extended morphological operations and edge extraction known already, we successful extract the edge of the camouflaged target which is collected by a hyperspectral imager based on AOTF in the VIS-SWIR region.

Yang, Jia; Hua, Wenshen; Ma, Zuohong; Zhang, Yue

2013-08-01

192

New developments and application of the UPRM MATLAB hyperspectral image analysis toolbox  

Microsoft Academic Search

The Hyperspectral Image Analysis Toolbox (HIAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose the Toolbox is to provide a suite of information extraction algorithms to users of hyperspectral and multispectral imagery. HIAT has been developed as part of the NSF Center for

Samuel Rosario-Torres; Miguel Vélez-Reyes; Shawn D. Hunt; Luis O. Jiménez

2007-01-01

193

SUCHI: The Space Ultra-Compact Hyperspectral Imager for small satellites  

NASA Astrophysics Data System (ADS)

The Space Ultra Compact Hyperspectral Imager is a long wave infrared hyperspectral imager being built at the University of Hawaii. The sensor will be the primary payload on the HiakaSat small satellite scheduled for launch on the Office of Responsive Space ORS-4 mission, and planned for a 6 month primary mission which is extendable up to two years of operation on orbit. SUCHI is based on a variable-gap Fabry-Perot interferometer employed as a Fourier transform spectrometer and uses an uncooled 320x256 microbolometer array to collect the images. The sensor is low volume (16" x 4" x 5") and low mass (<9kg), to conform to the volume, mass, and power requirements of the small satellite. The commercial microbolometer camera and vacuum-sensitive electronics are contained within a sealed vessel pressurized to 1 atm. The sensor will collect spectral radiance data in the long wave infrared region (8-14 microns) and demonstrate the potential of this instrument for advancing the geological sciences (e.g. mapping of major rock-forming minerals) as well as for volcanic hazard assessment (mapping volcanic ash, quantification of volcanic sulfur dioxide pollution and lava flow cooling rates). The sensor is scheduled for delivery to the satellite in Spring 2013, with launch scheduled for Fall 2013.

Crites, S. T.; Lucey, P. G.; Wright, R.; Chan, J.; Garbeil, H.; Horton, K. A.; Imai, Amber; Wood, M.; Yoneshige, L.

2013-05-01

194

Hyperspectral image superresolution: An edge-preserving convex formulation  

E-print Network

Hyperspectral remote sensing images (HSIs) are characterized by having a low spatial resolution and a high spectral resolution, whereas multispectral images (MSIs) are characterized by low spectral and high spatial resolutions. These complementary characteristics have stimulated active research in the inference of images with high spatial and spectral resolutions from HSI-MSI pairs. In this paper, we formulate this data fusion problem as the minimization of a convex objective function containing two data-fitting terms and an edge-preserving regularizer. The data-fitting terms are quadratic and account for blur, different spatial resolutions, and additive noise; the regularizer, a form of vector Total Variation, promotes aligned discontinuities across the reconstructed hyperspectral bands. The optimization described above is rather hard, owing to its non-diagonalizable linear operators, to the non-quadratic and non-smooth nature of the regularizer, and to the very large size of the image to be inferred. We tac...

Simões, Miguel; Almeida, Luis B; Chanussot, Jocelyn

2014-01-01

195

A hyperspectral image analysis workbench for environmental science applications  

SciTech Connect

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.

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

1992-10-01

196

A hyperspectral image analysis workbench for environmental science applications  

SciTech Connect

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.

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

1992-01-01

197

Hyperspectral imaging for non-contact analysis of forensic traces.  

PubMed

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 significant potential for the detection, visualization, identification and age estimation of forensic traces. The rapid, non-destructive and non-contact features of HSI mark its suitability as an analytical tool for forensic science. This paper provides an overview of the principles, instrumentation and analytical techniques involved in hyperspectral imaging. We describe recent advances in HSI technology motivating forensic science applications, e.g. the development of portable and fast image acquisition systems. Reported forensic science applications are reviewed. Challenges are addressed, such as the analysis of traces on backgrounds encountered in casework, concluded by a summary of possible future applications. PMID:23088824

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

2012-11-30

198

Ningaloo reef: shallow marine habitats mapped using a hyperspectral sensor.  

PubMed

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 km(2) 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 km(2)). 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

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

2013-01-01

199

Ningaloo Reef: Shallow Marine Habitats Mapped Using a Hyperspectral Sensor  

PubMed Central

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

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

2013-01-01

200

Hyperspectral Image Processing for Automatic Target Detection Applications  

Microsoft Academic Search

? This article presents an overview of the theoretical and practical issues associated with the development, analysis, and application of detection algorithms to exploit hyperspectral imaging data. We focus on techniques that exploit spectral information exclusively to make decisions regarding the type of each pixel—target or nontarget—on a pixel-by-pixel basis in an image. First we describe the fundamental structure of

Dimitris Manolakis; David Marden; Gary A. Shaw

2003-01-01

201

About Classification Methods Based on Tensor Modelling for Hyperspectral Images  

Microsoft Academic Search

\\u000a Denoising and Dimensionality reduction (DR) are key issue to improve the classifiers efficiency for Hyperspectral images (HSI).\\u000a The multi-way Wiener filtering recently developed is used, Principal and independent component analysis (PCA, ICA) and projection pursuit (PP) approaches to DR have been investigated. These matrix algebra methods are applied on vectorized images. Thereof, the spatial\\u000a rearrangement is lost. To jointly take advantage

Salah Bourennane; Caroline Fossati

2009-01-01

202

Demonstration of a Corner-cube-interferometer LWIR Hyperspectral Imager  

Microsoft Academic Search

An interferometric long-wavelength infrared (LWIR) hyperspectral imager is demonstrated, based on a Michelson corner-cube\\u000a interferometer. This class of system is inherently mechanically robust, and should have advantages over Sagnac-interferometer\\u000a systems in terms of relaxed beamsplitter-coating specifications, and wider unvignetted field of view. Preliminary performance\\u000a data from the laboratory prototype system are provided regarding imaging, spectral resolution, and fidelity of acquired

Ingmar G. E. Renhorn; Thomas Svensson; Staffan Cronström; Tomas Hallberg; Rolf Persson; Roland Lindell; Glenn D. Boreman

2010-01-01

203

Overview of hyperspectral remote sensing for mapping marine benthic habitats from airborne and underwater sensors  

NASA Astrophysics Data System (ADS)

The seafloor, with its diverse and dynamic benthic habitats varying on meter to centimeter scales, is difficult to accurately monitor with traditional techniques. The technology used to build imaging spectrometers has rapidly advanced in recent years with the advent of smaller sensors and better signal-to-noise capabilities that has facilitated their use in mapping fine-scale benthic features. Here, the use of such sensors for hyperspectral remote sensing of the seafloor from both airborne and underwater platforms is discussed. Benthic constituents provide a so-called optical fingerprint with spectral properties that are often too subtle to be discerned with simple color photographs or multichannel spectrometers. Applications include the recent field validation of the airborne Portable Remote Imaging SpectroMeter (PRISM), a new imaging sensor package optimized for coastal ocean processes in Elkorn Slough California. In these turbid sediment-laden waters, only subtle spectral differences differentiate seafloor with sediment from that with eelgrass. The ultimate goal is to provide robust radiometric approaches that accurately consider light attenuation by the water column and are able to be applied to diverse habitats without considerable foreknowledge.

Dierssen, Heidi M.

2013-09-01

204

Investigation of the potential use of hyperspectral imaging for stand-off detection of person-borne IEDs  

NASA Astrophysics Data System (ADS)

Advances in hyperspectral sensors and algorithms may benefit the detection of person-borne improvised explosive devices (PB-IEDs). While portions of the electromagnetic spectrum, such as the x-ray and terahertz regions, have been investigated for this application, the spectral region of the ultraviolet (UV) through shortwave infrared (SWIR) (250 nm to 2500 nm) has received little attention. The purpose of this work was to investigate what, if any, potential there may be for exploiting the spectral region of the UV through SWIR for the detection of hidden objects under the clothing of individuals. The optical properties of both common fabrics and materials potentially used to contain threat objects were measured, and a simple example using a hyperspectral imager is provided to illustrate the combined effect. The approach, measurement methods, and results are described in this paper, and the potential for hyperspectral imaging is addressed.

Cooksey, Catherine; Allen, David

2011-06-01

205

A novel infrared hyperspectral imager for passive standoff detection of explosives and explosive precursors  

NASA Astrophysics Data System (ADS)

The passive standoff detection of vapors from particular explosives and precursors emanating from a location under surveillance can provide early detection and warning of illicit explosives fabrication. DRDC Valcartier recently initiated the development and field-validation of a novel R&D prototype, MoDDIFS (Multi-Option Differential and Imaging Fourier Spectrometer) to address this security vulnerability. The proposed methodology combines the clutter suppression efficiency of the differential detection approach with the high spatial resolution provided by the hyperspectral imaging approach. This consists of integrating the imaging capability of the Hyper-Cam IR imager with a differential CATSI-type sensor. This paper presents the MoDDIFS sensor methodology and the first investigation results that were recently obtained.

Thériault, Jean-Marc; Montembeault, Yan; Lavoie, Hugo; Bouffard, Francois; Fortin, Gilles; Lacasse, Paul; Vallières, Alexandre; Puckrin, Eldon; Farley, Vincent; Chamberland, Daniel; Bubner, Tim

2011-05-01

206

Modelling the appearance of chromatic environment using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Color of objects is a spectral composition of incident light source, reflection properties of the object itself, and spectral tuning of the eye. Light sources with different spectral characteristics can produce metameric representation of color; however most variable in this regard is vision. Pigments of color vision are continuously bleached by different stimuli and optical density of the pigment is changed, while continuous conditions provide an adaptation and perception of white. Special cases are color vision deficiencies which cover almost 8 % of male population in Europe. Hyperspectral imaging allows obtaining the spectra of the environment and modelling the performance of the dichromatic, anomalous trichromatic, as also normal trichromatic adapted behavior. First, CRI Nuance hyperspectral imaging system was spectrally calibrated for natural continuous spectral illumination of high color rendering index and narrow band fluorescent light sources. Full-scale images of color deficiency tests were acquired in the range of 420 to 720 nm to evaluate the modelling capacity for dichromatic and anomalous trichromatic vision. Hyperspectral images were turned to cone excitation images according to Stockman and Sharpe (2000) 1. Further, model was extended for anomalous trichromacy conditions. Cone sensitivity spectra were shifted by 4 nm according to each anomaly type. LWS and SWS cone signals were balanced in each condition to provide the appropriate appearance of colors in CIE system.

Fomins, S.; Ozolinsh, M.

2013-11-01

207

An optimized hybrid encode based compression algorithm for hyperspectral image  

NASA Astrophysics Data System (ADS)

Compression is a kernel procedure in hyperspectral image processing due to its massive data which will bring great difficulty in date storage and transmission. In this paper, a novel hyperspectral compression algorithm based on hybrid encoding which combines with the methods of the band optimized grouping and the wavelet transform is proposed. Given the characteristic of correlation coefficients between adjacent spectral bands, an optimized band grouping and reference frame selection method is first utilized to group bands adaptively. Then according to the band number of each group, the redundancy in the spatial and spectral domain is removed through the spatial domain entropy coding and the minimum residual based linear prediction method. Thus, embedded code streams are obtained by encoding the residual images using the improved embedded zerotree wavelet based SPIHT encode method. In the experments, hyperspectral images collected by the Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) were used to validate the performance of the proposed algorithm. The results show that the proposed approach achieves a good performance in reconstructed image quality and computation complexity.The average peak signal to noise ratio (PSNR) is increased by 0.21~0.81dB compared with other off-the-shelf algorithms under the same compression ratio.

Wang, Cheng; Miao, Zhuang; Feng, Weiyi; He, Weiji; Chen, Qian; Gu, Guohua

2013-12-01

208

Calibration and performance of the airborne fourier transform visible hyperspectral imager (FTVHSI)  

SciTech Connect

A new hyperspectral imager has recently been developed by Kestrel Corporation for use in light aircraft platforms. The instrument provides 256 spectral channels with 87 cm{sup -1} spectral bandwidth over the 350 nm to 1050 nm portion of the spectrum. Operated as a pushbroom imager, the FTVHSI has been shown to have a IFOV of 0.75 mrad, and a FOV of 0.23 rad. The sensor includes an internal spectral/radiometric calibration source, a self contained spectrally resolved downwelling sensor, and complete line of sight and GPS positioning information. The instrument is now completing an extensive set of calibration and performance measurements and is operating from a Cessan TU-206 single engine aircraft. It is anticipated that the sensor will be placed into service in the Spring of 1996. 5 refs., 12 figs., 2 tabs.

Otten, L.J. III; Meigs, A.D. [Kestrel Corp., Albuquerque, NM (United States); Sellar, R.G

1996-10-01

209

A minimum spanning forest based hyperspectral image classification method for cancerous tissue detection  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging is a developing modality for cancer detection. The rich information associated with hyperspectral images allow for the examination between cancerous and healthy tissue. This study focuses on a new method that incorporates support vector machines into a minimum spanning forest algorithm for differentiating cancerous tissue from normal tissue. Spectral information was gathered to test the algorithm. Animal experiments were performed and hyperspectral images were acquired from tumor-bearing mice. In vivo imaging experimental results demonstrate the applicability of the proposed classification method for cancer tissue classification on hyperspectral images.

Pike, Robert; Patton, Samuel K.; Lu, Guolan; Halig, Luma V.; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-03-01

210

A Minimum Spanning Forest Based Hyperspectral Image Classification Method for Cancerous Tissue Detection  

PubMed Central

Hyperspectral imaging is a developing modality for cancer detection. The rich information associated with hyperspectral images allow for the examination between cancerous and healthy tissue. This study focuses on a new method that incorporates support vector machines into a minimum spanning forest algorithm for differentiating cancerous tissue from normal tissue. Spectral information was gathered to test the algorithm. Animal experiments were performed and hyperspectral images were acquired from tumor-bearing mice. In vivo imaging experimental results demonstrate the applicability of the proposed classification method for cancer tissue classification on hyperspectral images.

Pike, Robert; Patton, Samuel K.; Lu, Guolan; Halig, Luma V.; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-01-01

211

Real-time data processor for the COMPASS hyperspectral sensor system  

NASA Astrophysics Data System (ADS)

The NVESD COMPASS instrument is an airborne dispersive hyperspectral imager that covers the VNIR through SWIR bands and incorporates a real-time data processing system. The processing system consists of a Data Processing Computer (DPC) and an Operator Display/Control Computer (ODC). The high-performance DPC executes real-time sensor calibration and multiple spectral detection algorithms on 13 G4-processors in a Race++ switched backplane. The DPC sends three-band pseudo-color hyperspectral data, high-resolution target chips, and GPS/INS data to the ODC. The ODC outputs a geo-registered display of HSI color imagery with detection cue overlays. The COMPASS detection algorithms, which are particularly well suited to CC&D targeting applications, include the SSRX spectral anomaly detector, the NFINDR/STD spectral unmixing-based anomaly detector, (3) a supervised spectral matched filter (SSMF), and (4) Healey's invariant subspace detector. The DPC airborne component is VME-based in a compact, ruggedized chassis. The COMPASS real-time processor is a second generation system based on NRL-sponsored WarHORSE demonstrations. This paper reviews the DPC system design, capabilities and performance.

Schaff, William E.; Copeland, Anthony; Steffen, Mike; O'Connor, Rory; Simi, Christopher; Zadnik, Jerry; Winter, Ed M.; Healey, Glenn

2003-12-01

212

Real-time data processor for the COMPASS hyperspectral sensor system  

NASA Astrophysics Data System (ADS)

The NVESD COMPASS instrument is an airborne dispersive hyperspectral imager that covers the VNIR through SWIR bands and incorporates a real-time data processing system. The processing system consists of a Data Processing Computer (DPC) and an Operator Display/Control Computer (ODC). The high-performance DPC executes real-time sensor calibration and multiple spectral detection algorithms on 13 G4-processors in a Race++ switched backplane. The DPC sends three-band pseudo-color hyperspectral data, high-resolution target chips, and GPS/INS data to the ODC. The ODC outputs a geo-registered display of HSI color imagery with detection cue overlays. The COMPASS detection algorithms, which are particularly well suited to CC&D targeting applications, include the SSRX spectral anomaly detector, the NFINDR/STD spectral unmixing-based anomaly detector, (3) a supervised spectral matched filter (SSMF), and (4) Healey's invariant subspace detector. The DPC airborne component is VME-based in a compact, ruggedized chassis. The COMPASS real-time processor is a second generation system based on NRL-sponsored WarHORSE demonstrations. This paper reviews the DPC system design, capabilities and performance.

Schaff, William E.; Copeland, Anthony; Steffen, Mike; O'Connor, Rory; Simi, Christopher; Zadnik, Jerry; Winter, Ed M.; Healey, Glenn

2004-01-01

213

Hyperspectral image classification based on NMF Features Selection Method  

NASA Astrophysics Data System (ADS)

Hyperspectral instruments are capable of collecting hundreds of images corresponding to wavelength channels for the same area on the earth surface. Due to the huge number of features (bands) in hyperspectral imagery, land cover classification procedures are computationally expensive and pose a problem known as the curse of dimensionality. In addition, higher correlation among contiguous bands increases the redundancy within the bands. Hence, dimension reduction of hyperspectral data is very crucial so as to obtain good classification accuracy results. This paper presents a new feature selection technique. Non-negative Matrix Factorization (NMF) algorithm is proposed to obtain reduced relevant features in the input domain of each class label. This aimed to reduce classification error and dimensionality of classification challenges. Indiana pines of the Northwest Indiana dataset is used to evaluate the performance of the proposed method through experiments of features selection and classification. The Waikato Environment for Knowledge Analysis (WEKA) data mining framework is selected as a tool to implement the classification using Support Vector Machines and Neural Network. The selected features subsets are subjected to land cover classification to investigate the performance of the classifiers and how the features size affects classification accuracy. Results obtained shows that performances of the classifiers are significant. The study makes a positive contribution to the problems of hyperspectral imagery by exploring NMF, SVMs and NN to improve classification accuracy. The performances of the classifiers are valuable for decision maker to consider tradeoffs in method accuracy versus method complexity.

Abe, Bolanle T.; Jordaan, J. A.

2013-12-01

214

The challenges of analysing blood stains with hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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.

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

2014-06-01

215

A Variational Approach to Hyperspectral Image Fusion Michael Moellera, Todd Wittmanb, Andrea L. Bertozzib  

E-print Network

A Variational Approach to Hyperspectral Image Fusion Michael Moellera, Todd Wittmanb, Andrea L in the fusion process. This procedure produces images with both high spatial and spectral quality. We demonstrate this procedure on several AVIRIS and HYDICE images. Keywords: image fusion, hyperspectral imagery

Soatto, Stefano

216

Target detection in hyperspectral images based on independent component analysis  

NASA Astrophysics Data System (ADS)

The paper presents an algorithm based on Independent Component Analysis (ICA) for the detection of small targets present in hyperspectral images. ICA is a multivariate data analysis method that attempts to produce statistically independent components. This method is based on fourth order statistics. Small, man-made targets in a natural background can be seen as anomalies in the image scene and correspond to independent components in the ICA model. The algorithm described here starts by preprocessing the hyperspectral data through centering and sphering, thus eliminating the first and second order statistics. It then separates the features present in the image using an ICA based algorithm. The method involves a gradient descent minimization of the mutual information between frames. The resulting frames are ranked according to their kurtosis (defined by normalized fourth order moment of the sample distribution). High kurtosis valued frames indicate the presence of small man-made targets. Thresholding the frames using zero detection in their histogram further identifies the targets. The effectiveness of the method has been studied on data from the hyperspectral digital imagery collection experiment (HYDICE). Preliminary results show that small targets present in the image are separated from the background in different frames and that information pertaining to them is concentrated in these frames. Frame selection using kurtosis and thresholding leads to automated identification of the targets. The experiments show that the method provides a promising new approach for target detection.

Robila, Stefan A.; Varshney, Pramod K.

2002-07-01

217

Hyperspectral imaging for detecting pathogens grown on agar plates  

NASA Astrophysics Data System (ADS)

This paper is concerned with the development of a hyperspectral imaging technique for detecting and identifying one of the most common foodborne pathogens, Campylobacter. Direct plating using agars is an effective tool for laboratory tests and analyses of microorganisms. The morphology (size, growth pattern, color, etc.) of colonies grown on agar plates has been widely used to tentatively differentiate organisms. However, it is sometimes difficult to differentiate target organisms like Campylobacters from other contaminants grown together on the same agar plates. A hyperspectral imaging system operating at the visible and near infrared (VNIR) spectral region from 400 nm to 900 nm was set up to measure spectral signatures of 17 different Campylobacter and non-Campylobacter subspecies. Protocols for culturing, imaging samples and for calibrating measured data were developed. The VNIR spectral library of all 17 organisms commonly encountered in poultry was established from calibrated hyperspectral images. A classification algorithm was developed to locate and identify Campylobacters, non-Campylobacter contaminants, and background agars with 99.29% accuracy. This research has a potential to be expanded to detect other pathogens grown on agar media.

Yoon, Seung Chul; Lawrence, Kurt C.; Siragusa, Gregory R.; Line, John E.; Park, Bosoon; Windham, William R.

2007-09-01

218

[Identification of cucumber disease using hyperspectral imaging and discriminate analysis].  

PubMed

Hyperspectral imaging (400-720 nm) and discriminate analysis were investigated for the detection of normal and diseased cucumber leaf samples with powdery mildew (Sphaerotheca fuliginea), angular leaf spot (Pseudomopnas syringae), downy mildew (Pseudoperonospora cubensis), and brown spot (Corynespora cassiicola). A hyperspectral imaging system was es tablished to acquire and pre-process leaf images, as well as to extract leaf spectral properties. Owing to the complexity of the original spectral data, stepwise discriminate and canonical discriminate were executed to reduce the numerous spectral information, in order to decrease the amount of calculation and improve the accuracy. By the stepwise discriminate we selected 12 optimal wavelengths from the original 55 wavelengths, and after the canonical discriminate, the 55 wavelengths were reduced to 2 canonical variables. Then the discriminate models were developed to classify the leaf samples. The result shows that the stepwise discriminate model achieved classification accuracies of 100% and 94% for the training and testing sets, respectively. For the canonical model, the classification accuracies for the training and testing sets were both 100%. These results indicated that it is feasible to identify and classify cucumber diseases using hyperspectral imaging technology and discriminate analysis. The preliminary study, which was done in a closed room with restrictions to avoid interference of the field environment, showed that there is a potential to establish an online field application in cucumber disease detection based on visible spectroscopy. PMID:20672633

Chai, A-Li; Liao, Ning-Fang; Tian, Li-Xun; Shi, Yan-Xia; Li, Bao-Ju

2010-05-01

219

Hyperspectral optical imaging of two different species of lepidoptera  

PubMed Central

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. PMID:21711872

2011-01-01

220

Objective color classification of ecstasy tablets by hyperspectral imaging.  

PubMed

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 and illicit tablets, created with different amounts of known colorants were analyzed. We derived reflectance spectra from hyperspectral images of these tablets, and successfully determined the most likely colorant used in the production of all self-manufactured tablets and four of five illicit tablets studied. Upon classification, the concentration of the colorant was estimated using a photon propagation model and a single reference measurement of a tablet of known concentration. The estimated concentrations showed a high correlation with the actual values (R(2) = 0.9374). The achieved color information, combined with other physical and chemical characteristics, can provide a powerful tool for the comparison of tablet seizures, which may reveal their origin. PMID:23683098

Edelman, Gerda; Lopatka, Martin; Aalders, Maurice

2013-07-01

221

Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction  

NASA Astrophysics Data System (ADS)

This article presents a novel method for the enhancement of the spatial quality of hyperspectral (HS) images through the use of a high resolution panchromatic (PAN) image. Due to the high number of bands, the application of a pan-sharpening technique to HS images may result in an increase of the computational load and complexity. Thus a dimensionality reduction preprocess, compressing the original number of measurements into a lower dimensional space, becomes mandatory. To solve this problem, we propose a pan-sharpening technique combining both dimensionality reduction and fusion, making use of non-linear principal component analysis (NLPCA) and Indusion, respectively, to enhance the spatial resolution of a HS image. We have tested the proposed algorithm on HS images obtained from CHRIS-Proba sensor and PAN image obtained from World view 2 and demonstrated that a reduction using NLPCA does not result in any significant degradation in the pan-sharpening results.

Licciardi, Giorgio Antonino; Khan, Muhammad Murtaza; Chanussot, Jocelyn; Montanvert, Annick; Condat, Laurent; Jutten, Christian

2012-12-01

222

A hyperspectral image data exploration workbench for environmental science applications  

SciTech Connect

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.

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

1994-08-01

223

Hyperspectral cathodoluminescence imaging of modern and fossil carbonate shells  

NASA Astrophysics Data System (ADS)

Optical cathodoluminescence (CL) is commonly used to identify diagenetically altered carbonate fossils, yet such an interpretation is problematic as present-day carbonate shells may also luminesce. Hyperspectral CL imaging combines CL microscopy and CL spectroscopy to quantitatively analyze luminescence emission. Cold optical CL and hyperspectral CL imaging were carried out on four modern biominerals, a Rhynchonelliform brachiopod, a Craniid brachiopod, a bivalve, and the eggshell of the domestic fowl. A fossil Craniid brachiopod was analyzed to compare luminescence emission with that from the modern Craniid brachiopod. The beam conditions used for optical CL vary between studies, which hinders the direct comparison of CL analyses. This study assesses the effect of beam current and beam diameter on the intensity of luminescence emission. By characterizing the effect of beam conditions on different CaCO3 biominerals, comparisons can be made between CL studies. Hyperspectral CL imaging can be carried out in combination with WDS element analysis. By comparing hyperspectral CL images with element maps the causes of luminescence can to some extent be determined. The intensity of luminescence emitted from the modern biominerals differs under the same beam conditions. All four modern shells emit blue luminescence. In N. anomala, there is a correlation between Mn2+ concentration and luminescence intensity in the 620- to 630-nm wavelength band, which is apparent in the inner region of the shell. The fossil Craniid also emits blue luminescence, and texture within the shell wall is apparent; however, the luminescence emission between 620 and 630 nm that is evident in N. anomala is absent.

England, Jennifer; Cusack, Maggie; Paterson, Niall W.; Edwards, Paul; Lee, Martin R.; Martin, Robert

2006-09-01

224

Non-destructive hyperspectral imaging of quarantined Mars Returned Samples  

NASA Astrophysics Data System (ADS)

Introduction: In preparation for the upcoming International Mars Sample Return mission (MSR), returning samples containing potential biohazards, we have implemented a hyperspec-tral method of in-situ analysis of grains performed in BSL4 quarantine conditions, by combining several non-destructive imaging diagnostics. This allows sample transportation on optimized experimental setups, while monitoring the sample quarantine conditions. Our hyperspectral methodology was tested during analyses of meteorites [1-2] and cometary and interstellar grains from the recent NASA Stardust mission [3-6]. Synchrotron Radiation protocols: X-ray analysis methods are widely accepted as the least destructive probes of fragile, unique samples. Diffraction, X-ray fluorescence and ab-sorption micro/nano-spectroscopies were performed on chondritic test samples using focused monochromatic beams at the ESRF synchrotron in Grenoble, France. 2D maps of grain com-position down to ppm concentrations and polycrystalline structure have simultaneously been acquired, followed by X-ray absorption performed on elements of Z 26. Ideally, absorption micro-tomography can later be performed in full-beam mode to record the 3D morphology of the grain followed by fluorescence-tomography in focus-beam mode which complements this picture with a 3D elemental image of the grain. Lab-based protocols: Raman and IR-based spectroscopies have been performed in reflection mode for mineralogical imaging of the grains in the laboratory using commercial microscopes. The spatial resolution varied in the 1-10 m range. Laser limited penetration of opaque samples permits only 2D imaging of the few nanometer-thick outer layers of the grains. Mineralogical maps are now routinely acquired using Raman spectroscopy at sub-micron scales through the 3 container walls of the Martian sample holder, followed by IR few-micrometer spot measurements recording C-based and potential aqueous alteration distributions. Sample Holder: A miniaturized sample-holder [7] has been designed and built to allow direct analyses of a set of extraterrestrial grains confined in a sealed triple container and remotely po-sitioned in front of the X-ray or laser beams of the various setups. The grains are held in several thin walls (10 m) ultrapure silica capillaries which are sufficiently resistant for manual/remote-controlled micro-manipulation but semitransparent for the characteristic X-rays, Raman and IR radiations. Miniaturized pressure/temperature sensors located in each container periodically monitor the integrity of the ensemble, ensuring BSL4 condi-tions. References: [1] B. Golosio, A. Simionovici, A. Somogyi, L. Lemelle, M. Chukalina, A. Brunetti, Jrnl. of App. Phys. 94, 145-157, 2003 [2] L. Lemelle, A. Simionovici, R. Truche, Ch. Rau, M. Chukalina, Ph. Gillet, Am. Min. 87 , 547-553, 2004 [3] Michael E. Zolensky et al., Science 314, 1735-1739, 2006 [4] G. J. Flynn et al., Science 314, 1731-1735, 2006 [5] Pierre Bleuet, Alexandre Simionovici, Laurence Lemelle, Tristan Ferroir, Peter Cloetens, Rémi Tu-coulou, Jean Susini, App. Phys. Lett. 92, 213111-1-3, 2008. [6] A. J. Westphal, et al., AIP Proceedings of the ICXOM Congress, (in print) 2010. [8] A. Simionovici and CNES, patent pending.

Simionovici, Alexandre; Viso, Michel; Beck, Pierre; Lemelle, Laurence; Westphal, Andrew; Vincze, Laszlo; Schoonjans, Tom; Fihman, Francois; Chazalnoel, Pascale; Ferroir, Tristan; Solé, Vicente Armando; Tucoulou, R.

225

Spatial and spectral performance of a chromotomosynthetic hyperspectral imaging system.  

PubMed

The spatial and spectral resolutions achievable by a prototype rotating prism chromotomosynthetic imaging (CTI) system operating in the visible spectrum are described. The instrument creates hyperspectral imagery by collecting a set of 2D images with each spectrally projected at a different rotation angle of the prism. Mathematical reconstruction techniques that have been well tested in the field of medical physics are used to reconstruct the data to produce the 3D hyperspectral image. The instrument operates with a 100 mm focusing lens in the spectral range of 400-900 nm with a field of view of 71.6 mrad and angular resolution of 0.8-1.6 ?rad. The spectral resolution is 0.6 nm at the shortest wavelengths, degrading to over 10 nm at the longest wavelengths. Measurements using a point-like target show that performance is limited by chromatic aberration. The system model is slightly inaccurate due to poor estimation of detector spatial resolution, this is corrected based on results improving model performance. As with traditional dispersion technology, calibration of the transformed wavelength axis is required, though with this technology calibration improves both spectral and spatial resolution. While this prototype does not operate at high speeds, components exist which will allow for CTI systems to generate hyperspectral video imagery at rates greater than 100 Hz. PMID:22462909

Bostick, Randall L; Perram, Glen P

2012-03-01

226

Spatial and spectral performance of a chromotomosynthetic hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

The spatial and spectral resolutions achievable by a prototype rotating prism chromotomosynthetic imaging (CTI) system operating in the visible spectrum are described. The instrument creates hyperspectral imagery by collecting a set of 2D images with each spectrally projected at a different rotation angle of the prism. Mathematical reconstruction techniques that have been well tested in the field of medical physics are used to reconstruct the data to produce the 3D hyperspectral image. The instrument operates with a 100 mm focusing lens in the spectral range of 400-900 nm with a field of view of 71.6 mrad and angular resolution of 0.8-1.6 ?rad. The spectral resolution is 0.6 nm at the shortest wavelengths, degrading to over 10 nm at the longest wavelengths. Measurements using a point-like target show that performance is limited by chromatic aberration. The system model is slightly inaccurate due to poor estimation of detector spatial resolution, this is corrected based on results improving model performance. As with traditional dispersion technology, calibration of the transformed wavelength axis is required, though with this technology calibration improves both spectral and spatial resolution. While this prototype does not operate at high speeds, components exist which will allow for CTI systems to generate hyperspectral video imagery at rates greater than 100 Hz.

Bostick, Randall L.; Perram, Glen P.

2012-03-01

227

[Compression of interference hyperspectral image based on FHALS-NTD].  

PubMed

A hyperspectral interference image compression algorithm based on fast hierarchical alternating least squares nonnegative tensor Tucker decomposition (FHALS-NTD) is proposed. Firstly, the interference hyperspectral image is decomposed by 3-D OPD lifting-based discrete wavelet transform (3D OPT-LDWT) in the OPD direction. Then, the 3D DWT sub-bands decomposed are used as a three order nonnegative tensor, which is decomposed by the proposed FHALS-NTD algorithm to obtain 8 core tensors and 24 unknown component matrices. Finally, to obtain the final compressed bit-stream, each unknown component matrices element is quantized, and each core tensor is encoded by the proposed bit-plane coding of significant coefficients. The experimental results showed that the proposed compression algorithm could be used for reliable and stable work and has good compressive property. In the compression ratio range from 32 : 1 to 4 : 1, the average peak signal to noise ratio of proposed compression algorithm is higher than 40 dB. Compared with traditional approaches, the proposed method could improve the average PSNR by 1.23 dB. This effectively improves the compression performance of hyperspectral interference image. PMID:23387199

Du, Li-Min; Li, Jin; Jin, Guang; Gao, Hui-Bin; Jin, Long-Xu; Zhang, Ke

2012-11-01

228

Real-time geo-spatial registration of target images from the WAR HORSE sensor  

NASA Astrophysics Data System (ADS)

The Naval Research Laboratory's airborne WAR HORSE sensor incorporates a hyperspectral line-scan sensor, a high- resolution video line-scanner, and a CMIGITS INS/GPS unit. Targets are detected in real time from the hyperspectral data, and images of the detected targets are chipped from the high-resolution video data for presentation to an operator. The INS/GPS data are used to geo-spatially register (georegister) both the hyperspectral data and the video chips. In this paper we show detection results for processing the hyperspectral data both before and after geo- spatial registration when assumed target size is incorporated into the detection algorithms. Then we illustrate the utility of presenting target image chips which are geo-spatially registered and fused with the hyperspectral data.

Kendall, William B.

2002-08-01

229

MIST Final Report: Multi-sensor Imaging Science and Technology  

SciTech Connect

The Multi-sensor Imaging Science and Technology (MIST) program was undertaken to advance exploitation tools for Long Wavelength Infra Red (LWIR) hyper-spectral imaging (HSI) analysis as applied to the discovery and quantification of nuclear proliferation signatures. The program focused on mitigating LWIR image background clutter to ease the analyst burden and enable a) faster more accurate analysis of large volumes of high clutter data, b) greater detection sensitivity of nuclear proliferation signatures (primarily released gasses) , and c) quantify confidence estimates of the signature materials detected. To this end the program investigated fundamental limits and logical modifications of the more traditional statistical discovery and analysis tools applied to hyperspectral imaging and other disciplines, developed and tested new software incorporating advanced mathematical tools and physics based analysis, and demonstrated the strength and weaknesses of the new codes on relevant hyperspectral data sets from various campaigns. This final report describes the content of the program and the outlines the significant results.

Lind, Michael A.; Medvick, Patricia A.; Foley, Michael G.; Foote, Harlan P.; Heasler, Patrick G.; Thompson, Sandra E.; Nuffer, Lisa L.; Mackey, Patrick S.; Barr, Jonathan L.; Renholds, Andrea S.

2008-03-15

230

Hyperspectral remote sensing monitoring on hot wastewater of Futtsu Power Plant in Tokyo Bay, Japan, using airborne Operational Modular Imaging Spectrometer (OMIS)  

Microsoft Academic Search

An experimental study in monitoring the hot wastewater which is discharged into sea by the Futtsu Power Plant on the east coast of Tokyo Bay, Japan, was carried out in August-September, 2001, by using airborne hyperspectral remote sensing (HRS) sensor OMIS (Operational Modular Imaging Spectrometer). The fundamental progress of experiment, features of OMIS HRS image, data progressing and information extraction

Yongchao Zhao; Qingxi Tong; Lanfen Zheng; Bing Zhang; Tuanjie Liu; Chuanqing Wu; Jiwei Bai; Xia Zhang

2003-01-01

231

BAYESIAN FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGES Qi Wei, Nicolas Dobigeon, and Jean-Yves Tourneret  

E-print Network

BAYESIAN FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGES Qi Wei, Nicolas Dobigeon, and Jean presents a Bayesian fusion technique for multi-band im- ages. The observed images are related to the high-- Fusion, multispectral and hyperspectral images, Bayesian estimation, Gibbs sampler, Hamiltonian Monte

Dobigeon, Nicolas

232

The HICO program - hyperspectral imaging of the coastal ocean from the International Space Station  

Microsoft Academic Search

The HICO (hyperspectral imager for the coastal ocean) program is a collaboration between the Naval Research Laboratory (NRL), the University of Hawai'i at Manoa, Utah State University, and NovaSol Inc., to image the coastal ocean and reef systems from the International Space Station. The first phase of the program will install the NRL portable hyperspectral imager for low light spectroscopy

M. R. Corson; J. H. Bowles; W. Chen; C. O. Davis; K. H. Gallelli; D. R. Korwan; P. G. Lucey; T. J. Mosher; R. Holasek

2004-01-01

233

Refinement of wavelength calibrations of hyperspectral imaging data using a spectrum-matching technique  

Microsoft Academic Search

The concept of imaging spectrometry, or hyperspectral imaging, is becoming increasingly popular in scientific communities in recent years. Hyperspectral imaging data covering the spectral region between 0.4 and 2.5 ?m and collected from aircraft and satellite platforms have been used in the study of the earth's atmosphere, land surface, and ocean color properties, as well as on planetary missions. In

Bo-Cai Gao; Marcos J. Montes; Curtiss O. Davis

2004-01-01

234

Hyperspectral image segmentation using a cooperative nonparametric approach  

NASA Astrophysics Data System (ADS)

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%.

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

235

Static hyperspectral fluorescence imaging of viscous materials based on a linear variable filter spectrometer.  

PubMed

This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis) wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent impurities in the viscous materials can be detected. For the illumination of the measurement object, a narrow-band high-power light-emitting diode (LED) with a center wavelength of 370 nm was used. The low-cost acquisition unit for the imaging consists of a linear variable filter (LVF) and a complementary metal oxide semiconductor (CMOS) 2D sensor array. The translucent wavelength range of the LVF is from 400 nm to 700 nm. For the confirmation of the concept, static measurements of fluorescent viscous materials with a non-fluorescent impurity have been performed and analyzed. With the presented setup, measurement surfaces in the micrometer range can be provided. The measureable minimum particle size of the impurities is in the nanometer range. The recording rate for the measurements depends on the exposure time of the used CMOS 2D sensor array and has been found to be in the microsecond range. PMID:24064604

Murr, Patrik J; Schardt, Michael; Koch, Alexander W

2013-01-01

236

Static Hyperspectral Fluorescence Imaging of Viscous Materials Based on a Linear Variable Filter Spectrometer  

PubMed Central

This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis) wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent impurities in the viscous materials can be detected. For the illumination of the measurement object, a narrow-band high-power light-emitting diode (LED) with a center wavelength of 370 nm was used. The low-cost acquisition unit for the imaging consists of a linear variable filter (LVF) and a complementary metal oxide semiconductor (CMOS) 2D sensor array. The translucent wavelength range of the LVF is from 400 nm to 700 nm. For the confirmation of the concept, static measurements of fluorescent viscous materials with a non-fluorescent impurity have been performed and analyzed. With the presented setup, measurement surfaces in the micrometer range can be provided. The measureable minimum particle size of the impurities is in the nanometer range. The recording rate for the measurements depends on the exposure time of the used CMOS 2D sensor array and has been found to be in the microsecond range. PMID:24064604

Murr, Patrik J.; Schardt, Michael; Koch, Alexander W.

2013-01-01

237

Standoff Hyperspectral Imaging of Explosives Residues Using Broadly Tunable External Cavity Quantum Cascade Laser Illumination  

SciTech Connect

We describe experimental results on the detection of explosives residues using active hyperspectral imaging by illumination of the target surface using an external cavity quantum cascade laser (ECQCL) and imaging using a room temperature microbolometer camera. The active hyperspectral imaging technique forms an image hypercube by recording one image for each tuning step of the ECQCL. The resulting hyperspectral image contains the full absorption spectrum produced by the illumination laser at each pixel in the image which can then be used to identify the explosive type and relative quantity using spectral identification approaches developed initially in the remote sensing community.

Bernacki, Bruce E.; Phillips, Mark C.

2010-05-01

238

[Atmospheric correction of hyperion hyperspectral image based on FLAASH].  

PubMed

Atmospheric correction of remote sensing image is the premise of quantitative remote sensing. The present paper evaluated the capability of FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes)in ENVI software to make atmospheric correction for EO-1 Hyperion hyperspectral image. Hyperion hyperspecreal image of Zhangye city in Heihe River valley of Gansu province, China was acquired on September 10, 2007. Canopy spectra, biochemical component and GPS data of 41 plots were measured in near real-time during the satellite overpass. Hyperion hyperspectral image was geometrically corrected using Lansat-7 ETM+ image, then DN values were transformed to radiance and apparent reflectance, and atmospheric correction of Hyperion image was made using FLAASH. The resulting radiance, apparent reflectance and reflectance after FLAASH of four typical objects, including corn, water body, desert and building, were compared. ASD spectra of corn were resampled to Hyperion corresponding bands using Gaussian filter function. The comparison between ASD resampled spectra and Hyperion spectra after FLAASH demonstrated that the atmospheric correction using FLAASH is very effective and these two spectra are consistent with each other and the correlation coefficient reached 0.987. PMID:19650448

Yuan, Jin-guo; Niu, Zheng; Wang, Xi-ping

2009-05-01

239

Research on method of geometry and spectral calibration of pushbroom dispersive hyperspectral imager  

NASA Astrophysics Data System (ADS)

Development and application of airborne and aerospace hyperspectral imager press for high precision geometry and spectral calibration of pixels of image cube. The research of geometry and spectral calibration of pushbroom hyperspectral imager, its target is giving the coordinate of angle field of view and center wavelength of each detect unit in focal plane detector of hyperspectral imager, and achieves the high precision, full field of view, full channel geometry and spectral calibration. It is importance for imaging quantitative and deep application of hyperspectal imager. The paper takes the geometry and spectral calibration of pushbroom dispersive hyperspectral imager as case study, and research on the constitution and analysis of imaging mathematical model. Aimed especially at grating-dispersive hyperspectral imaging, the specialty of the imaging mode and dispersive method has been concretely analyzed. Based on the analysis, the theory and feasible method of geometry and spectral calibration of dispersive hyperspectral imager is set up. The key technique has been solved is As follows: 1). the imaging mathematical model and feasible method of geometry and spectral calibration for full pixels of image cube has been set up, the feasibility of the calibration method has been analyzed. 2). the engineering model and method of the geometry and spectral calibration of pushbroom dispersive hyperspectral imager has been set up and the calibration equipment has been constructed, and the calibration precision has been analyzed.

He, Zhiping; Shu, Rong; Wang, Jianyu

2012-11-01

240

Superpixel-Augmented Endmember Detection for Hyperspectral Images  

NASA Technical Reports Server (NTRS)

Superpixels are homogeneous image regions comprised of several contiguous pixels. They are produced by shattering the image into contiguous, homogeneous regions that each cover between 20 and 100 image pixels. The segmentation aims for a many-to-one mapping from superpixels to image features; each image feature could contain several superpixels, but each superpixel occupies no more than one image feature. This conservative segmentation is relatively easy to automate in a robust fashion. Superpixel processing is related to the more general idea of improving hyperspectral analysis through spatial constraints, which can recognize subtle features at or below the level of noise by exploiting the fact that their spectral signatures are found in neighboring pixels. Recent work has explored spatial constraints for endmember extraction, showing significant advantages over techniques that ignore pixels relative positions. Methods such as AMEE (automated morphological endmember extraction) express spatial influence using fixed isometric relationships a local square window or Euclidean distance in pixel coordinates. In other words, two pixels covariances are based on their spatial proximity, but are independent of their absolute location in the scene. These isometric spatial constraints are most appropriate when spectral variation is smooth and constant over the image. Superpixels are simple to implement, efficient to compute, and are empirically effective. They can be used as a preprocessing step with any desired endmember extraction technique. Superpixels also have a solid theoretical basis in the hyperspectral linear mixing model, making them a principled approach for improving endmember extraction. Unlike existing approaches, superpixels can accommodate non-isometric covariance between image pixels (characteristic of discrete image features separated by step discontinuities). These kinds of image features are common in natural scenes. Analysts can substitute superpixels for image pixels during endmember analysis that leverages the spatial contiguity of scene features to enhance subtle spectral features. Superpixels define populations of image pixels that are independent samples from each image feature, permitting robust estimation of spectral properties, and reducing measurement noise in proportion to the area of the superpixel. This permits improved endmember extraction, and enables automated search for novel and constituent minerals in very noisy, hyperspatial images. This innovation begins with a graph-based segmentation based on the work of Felzenszwalb et al., but then expands their approach to the hyperspectral image domain with a Euclidean distance metric. Then, the mean spectrum of each segment is computed, and the resulting data cloud is used as input into sequential maximum angle convex cone (SMACC) endmember extraction.

Thompson, David R.; Castano, Rebecca; Gilmore, Martha

2011-01-01

241

Next generation miniature simultaneous multi-hyperspectral imaging systems  

NASA Astrophysics Data System (ADS)

The concept for a hyperspectral imaging system using a Fabry-Perot tunable filter (FPTF) array that is fabricated using "miniature optical electrical mechanical system" (MOEMS) technology. [1] Using an array of FPTF as an approach to hyperspectral imaging relaxes wavelength tuning requirements considerably because of the reduced portion of the spectrum that is covered by each element in the array. In this paper, Pacific Advanced Technology and ARL present the results of a concept design and performed analysis of a MOEMS based tunable Fabry-Perot array (FPTF) to perform simultaneous multispectral and hyperspectral imaging with relatively high spatial resolution. The concept design was developed with support of an Army SBIR Phase I program The Fabry-Perot tunable MOEMS filter array was combined with a miniature optics array and a focal plane array of 1024 x 1024 pixels to produce 16 colors every frame of the camera. Each color image has a spatial resolution of 256 x 256 pixels with an IFOV of 1.7 mrads and FOV of 25 degrees. The spectral images are collected simultaneously allowing high resolution spectral-spatial-temporal information in each frame of the camera, thus enabling the implementation of spectral-temporal-spatial algorithms in real-time to provide high sensitivity for the detection of weak signals in a high clutter background environment with low sensitivity to camera motion. The challenge in the design was the independent actuation of each Fabry Perot element in the array allowing for individual tuning. An additional challenge was the need to maximize the fill factor to improve the spatial coverage with minimal dead space. This paper will only address the concept design and analysis of the Fabry-Perot tunable filter array. A previous paper presented at SPIE DSS in 2012 explained the design of the optical array.

Hinnrichs, Michele; Gupta, Neelam

2014-03-01

242

Utility of hyperspectral imagers in the mining industry: Italy's gypsum reserves  

NASA Astrophysics Data System (ADS)

The mining industry is plagued with socioeconomic and safety roadblocks with not many solutions in the midst of a demanding market. As more and more geologic research using hyperspectral technology has been performed, along with an affordable price point for commercial use of hyperspectral technology, the benefits of hyperspectral imaging to the mining industry has become apparent. This study identifies the key areas of use for hyperspectral imaging in the mining industry through a case study of gypsum mine samples obtained from a mine in central Tuscany.

Wilson, Janette H.; Greenberger, Rebecca N.

2014-05-01

243

DIMENSIONAL REDUCTION IN HYPERSPECTRAL IMAGES BY DANGER THEORY BASED ARTIFICIAL IMMUNE SYSTEM  

Microsoft Academic Search

A new dynamical dimensional reduction model (HDRM) for hyperspectral images is proposed based on clone selection algorithm which is inspired from nature immune system in this paper. In existing dimensional reduction method, feature selection is most inefficient. To improve the efficiency, the feature selection problem in hyperspectral images is taken as a multi-objective optimization problem. The feasible band sets are

Lele Su; Xiangnan Liu; Xiaodong Wang; Nan Jiang

244

The role of digital bathymetry in mapping shallow marine vegetation from hyperspectral image data  

Microsoft Academic Search

Hyperspectral remote sensing is a proven technology for measurement of coastal ocean colour, including sea?bed mapping in optically shallow waters. Using hyperspectral imagery of shallow (<15 m deep) sea bed acquired with the Compact Airborne Spectrographic Imager (CASI?550), we examined how changes in the spatial resolution of bathymetric grids, created from sonar data (echosounding) and input to conventional image classifiers, affected

P. Gagnon; R. E. Scheibling; W. Jones; D. Tully

2008-01-01

245

Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review  

Microsoft Academic Search

The requirements of reliability, expeditiousness, accuracy, consistency, and simplicity for quality assessment of food products encouraged the development of non-destructive technologies to meet the demands of consumers to obtain superior food qualities. Hyperspectral imaging is one of the most promising techniques currently investigated for quality evaluation purposes in numerous sorts of applications. The main advantage of the hyperspectral imaging system

Gamal Elmasry; Mohammed Kamruzzaman; Da-Wen Sun; Paul Allen

2012-01-01

246

On the Statistics of Hyperspectral Imaging Data Dimitris Manolakis, David Marden, John Kerekes and Gary Shaw  

E-print Network

On the Statistics of Hyperspectral Imaging Data Dimitris Manolakis, David Marden, John Kerekes of the joint (among wavebands) probability density function (pdf) of hyperspectral imaging (HSI) data and statistical classifiers. HSI data are vector (or equivalently multivariate) data in a vector space

Kerekes, John

247

Analysis of VIS-LWIR hyperspectral image data for detailed geologic mapping  

Microsoft Academic Search

Research is being conducted into the usefulness of hyperspectral data for detailed geologic mapping applications. The data being analyzed were collected by the HYDICE (VIS-SWIR) and SEBASS (LWIR) airborne imaging spectrometers. Hyperspectral data provides a means of identifying surface minerology, which indicates lithology. In addition, because the data are collected in image format, photo-geologic observations can be made, such as

Timothy Bowers

2002-01-01

248

Affinity propagation for large size hyperspectral image classification  

NASA Astrophysics Data System (ADS)

The affinity propagation (AP)1 is now among the most used methods of unsupervised classification. However, it has two major disadvantages. On the one hand, the algorithm implicitly controls the number of classes from a preference parameter, usually initialized as the median value of the similarity matrix, which often gives over-clustering. On the other hand, when partitioning large size hyperspectral images, its computational complexity is quadratic and seriously hampers its application. To solve these two problems, we propose a method which consists of reducing the number of individuals to be classified before the application of the AP, and to concisely estimate the number of classes. For the reduction of the number of pixels, a pre-classification step that automatically aggregates highly similar pixels is introduced. The hyperspectral image is divided into blocks, and then the reduction step is applied independently within each block. This step requires less memory storage since the calculation of the full similarity matrix is not required. The AP is then applied on the new set of pixels which are then set up from the representatives of each previously formed cluster and non-aggregated individuals. To estimate the number of classes, we introduced a dichotomic method to assess classification results using a criterion based on inter-class variance. The application of this method on various test images has shown that AP results are stable and independent to the choice of the block size. The proposed approach was successfully used to partition large size real datasets (multispectral and hyperspectral images).

Soltani, Mariem; Chehdi, Kacem; Cariou, Claude

2013-10-01

249

Automated recognition and detection of dismounts and vehicles using close-in urban hyperspectral images  

NASA Astrophysics Data System (ADS)

Advances in Hyperspectral imaging (HSI) sensor offer new avenues for precise detection, identification and characterization of materials or targets of military interest. HSI technologies are capable of exploiting 10s to 100s of images of a scene collected at contiguous or selective spectral bands to seek out mission-critical objects. In this paper, we develop and analyze several HSI algorithms for detection, recognition and tracking of dismounts, vehicles and other objects. Preliminary work on detection, classification and fingerprinting of dismount, vehicle and UAV has been performed using visible band HSI data. The results indicate improved performance with HSI when compared to traditional EO processing. All the detection and classification results reported in this paper were based on single HSI pixel used for testing. Furthermore, the close-in Hyperspectral data were collected for the experiments at indoor or outdoor by the authors. The collections were taken in different lighting conditions using a visible HSI sensor. The algorithms studied for performance comparison include PCA, Linear Discriminant Analysis method (LDA), Quadratic classifier and Fisher's Linear Discriminant and comprehensive results have been included in terms of confusion matrices and Receiver Operating Characteristic (ROC) curves.

Karimkhan, Shamsaddin; Vongsy, Karmon; Shaw, Arnab K.; Wicker, Devert

2007-04-01

250

Using elliptically contoured distributions to model hyperspectral imaging data and generate statistically similar synthetic data  

NASA Astrophysics Data System (ADS)

Developing proper models for Hyperspectral imaging (HSI) data allows for useful and reliable algorithms for data exploitation. These models provide the foundation for development and evaluation of detection, classification, clustering, and estimation algorithms. To date, most algorithms have modeled real data as multivariate normal, however it is well known that real data often exhibits non-normal behavior. In this paper, Elliptically Contoured Distributions (ECDs) are used to model the statistical variability of HSI data. Non-homogeneous data sets can be modeled as a finite mixture of more than one ECD, with different means and parameters for each component. A larger family of distributions, the family of ECDs includes the multivariate normal distribution and exhibits most of its properties. ECDs are uniquely defined by their multivariate mean, covariance and the distribution of its Mahalanobis distance metric. This metric lets multivariate data be identified using a univariate statistic and can be adjusted to more closely match the longer tailed distributions of real data. One ECD member of focus is the multivariate t-distribution, which provides longer tailed distributions than the normal, and has an F-distributed Mahalanobis distance statistic. This work will focus on modeling these univariate statistics, using the Exceedance metric, a quantitative goodness-of-fit metric developed specifically to improve the accuracy of the model to match the long probabilistic tails of the data. This metric will be shown to be effective in modeling the univariate Mahalanobis distance distributions of hyperspectral data from the HYDICE sensor as either an F-distribution or as a weighted mixture of F-distributions. This implies that hyperspectral data has a multivariate t-distribution. Proper modeling of Hyperspectral data leads to the ability to generate synthetic data with the same statistical distribution as real world data.

Marden, David B.; Manolakis, Dimitris G.

2004-08-01

251

Thermal infrared hyperspectral data compression  

Microsoft Academic Search

Hyperspectral imagers sample the electromagnetic spectrum at greater resolution than more traditional imaging systems, which result in a higher band-to-band correlation and greater amounts of data. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and\\/or data compression will be very important. The data from a new hyperspectral sensor, SEBASS, which collects data in

Bernard V. Brower; Austin Lan; Rulon E. Simmons; David H. Haddock

1998-01-01

252

Hyperspectral sensor characteristics needed for coastal ocean science  

Microsoft Academic Search

The complexity of the coastal ocean, particularly when the bottom is visible, necessitates the use of hyperspectral imagery for remote measurement of bathymetry, bottom type, and water properties. This is in contrast to the open ocean where water column properties alone are of interest and for which the use of multispectral imagery is normally sufficient. The Remote Sensing Division of

Jeffrey H. Bowles; Michael R. Corson; Curtiss O. Davis; Daniel Korwan; Marcos J. Montes; William Snyder

2004-01-01

253

Quantum cascade lasers (QCL) for active hyperspectral imaging  

NASA Astrophysics Data System (ADS)

There is an increasing demand for wavelength agile laser sources covering the mid-infrared (MIR, 3.5-12 µm) wavelength range, among others in active imaging. The MIR range comprises a particularly interesting part of the electromagnetic spectrum for active hyperspectral imaging applications, due to the fact that the characteristic `fingerprint' absorption spectra of many chemical compounds lie in that range. Conventional semiconductor diode laser technology runs out of steam at such long wavelengths. For many applications, MIR coherent light sources based on solid state lasers in combination with optical parametric oscillators are too complex and thus bulky and expensive. In contrast, quantum cascade lasers (QCLs) constitute a class of very compact and robust semiconductor-based lasers, which are able to cover the mentioned wavelength range using the same semiconductor material system. In this tutorial, a brief review will be given on the state-of-the-art of QCL technology. Special emphasis will be addressed on QCL variants with well-defined spectral properties and spectral tunability. As an example for the use of wavelength agile QCL for active hyperspectral imaging, stand-off detection of explosives based on imaging backscattering laser spectroscopy will be discussed.

Yang, Quankui; Fuchs, Frank; Wagner, Joachim

2014-04-01

254

GPU implementation issues for fast unmixing of hyperspectral images  

NASA Astrophysics Data System (ADS)

Space missions usually use hyperspectral imaging techniques to analyse the composition of planetary surfaces. Missions such as ESA's Mars Express and Venus Express generate extensive datasets whose processing demands so far have exceeded the resources available to many researchers. To overcome this limitation, the challenge is to develop numerical methods allowing to exploit the potential of modern calculation tools. The processing of a hyperspectral image consists of the identification of the observed surface components and eventually the assessment of their fractional abundances inside each pixel area. In this latter case, the problem is referred to as spectral unmixing. This work focuses on a supervised unmixing approach where the relevant component spectra are supposed to be part of an available spectral library. Therefore, the question addressed here is reduced to the estimation of the fractional abundances, or abundance maps. It requires the solution of a large-scale optimization problem subject to linear constraints; positivity of the abundances and their partial/full additivity (sum less/equal to one). Conventional approaches to such a problem usually suffer from a high computational overhead. Recently, an interior-point optimization using a primal-dual approach has been proven an efficient method to solve this spectral unmixing problem at reduced computational cost. This is achieved with a parallel implementation based on Graphics Processing Units (GPUs). Several issues are discussed such as the data organization in memory and the strategy used to compute efficiently one global quantity from a large dataset in a parallel fashion. Every step of the algorithm is optimized to be GPU-efficient. Finally, the main steps of the global system for the processing of a large number of hyperspectral images are discussed. The advantage of using a GPU is demonstrated by unmixing a large dataset consisting of 1300 hyperspectral images from Mars Express' OMEGA instrument and uses a spectral library of 41 possible ground components. The parallel implementation proposed requires three days of calculation to unmix this dataset, instead of twenty days for the optimized CPU implementation previously in use.

Legendre, Maxime; Capriotti, Luca; Schmidt, Frédéric; Moussaoui, Saïd; Schmidt, Albrecht

2013-04-01

255

Leafy Spurge (Euphorbia esula) Classification Performance Using Hyperspectral and Multispectral Sensors  

Microsoft Academic Search

Two demonstration sites in southeast Idaho were used to extend the scope of remote sensing of leafy spurge research toward investigating coarser scale detection limits. Hyperspectral images were obtained to produce baseline leafy spurge maps, from which spatially and\\/or spectrally degraded images were subsequently derived for comparative purposes with Landsat 5 Thematic Mapper (TM). The baseline presence\\/absence maps had an

Jessica J. Mitchell; Nancy F. Glenn

2009-01-01

256

Advanced hyperspectral video imaging system using Amici prism.  

PubMed

In this paper, we propose an advanced hyperspectral video imaging system (AHVIS), which consists of an objective lens, an occlusion mask, a relay lens, an Amici prism and two cameras. An RGB camera is used for spatial reading and a gray scale camera is used for measuring the scene with spectral information. The objective lens collects more light energy from the observed scene and images the scene on an occlusion mask, which subsamples the image of the observed scene. Then, the subsampled image is sent to the gray scale camera through the relay lens and the Amici prism. The Amici prism that is used to realize spectral dispersion along the optical path reduces optical distortions and offers direct view of the scene. The main advantages of the proposed system are improved light throughput and less optical distortion. Furthermore, the presented configuration is more compact, robust and practicable. PMID:25321019

Feng, Jiao; Fang, Xiaojing; Cao, Xun; Ma, Chenguang; Dai, Qionghai; Zhu, Hongbo; Wang, Yongjin

2014-08-11

257

Automatic Spectral Target Recognition in Hyperspectral  

E-print Network

of targets from image data in an unsupervised manner which will subsequently be classified by the TCP Research Laboratory's HYperspectral Digital Imagery Collection Experiment (HYDICE) sensor and many more

Chang, Chein-I

258

Motion Adaptive Image Sensor  

Microsoft Academic Search

We propose a motion adaptive sensor for image enhancement and wide dynamic range sensing. The motion adaptive sensor is able to control integration time pixel by pixel. The integration time is determined by saturation and temporal changes of incident light. It is expected to have high temporal resolution in the moving area, high SNR in the static area, and wide

Takayuki Hamamoto; Kiyoharu Aizawa; Mitsutoshi Hatori

1998-01-01

259

NIR DLP hyperspectral imaging system for medical applications  

NASA Astrophysics Data System (ADS)

DLP® hyperspectral reflectance imaging in the visible range has been previously shown to quantify hemoglobin oxygenation in subsurface tissues, 1 mm to 2 mm deep. Extending the spectral range into the near infrared reflects biochemical information from deeper subsurface tissues. Unlike any other illumination method, the digital micro-mirror device, DMD, chip is programmable, allowing the user to actively illuminate with precisely predetermined spectra of illumination with a minimum bandpass of approximately 10 nm. It is possible to construct active spectral-based illumination that includes but is not limited to containing sharp cutoffs to act as filters or forming complex spectra, varying the intensity of light at discrete wavelengths. We have characterized and tested a pure NIR, 760 nm to 1600 nm, DLP hyperspectral reflectance imaging system. In its simplest application, the NIR system can be used to quantify the percentage of water in a subject, enabling edema visualization. It can also be used to map vein structure in a patient in real time. During gall bladder surgery, this system could be invaluable in imaging bile through fatty tissue, aiding surgeons in locating the common bile duct in real time without injecting any contrast agents.

Wehner, Eleanor; Thapa, Abhas; Livingston, Edward; Zuzak, Karel

2011-03-01

260

Detecting pits in tart cherries by hyperspectral transmission imaging  

NASA Astrophysics Data System (ADS)

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.

Qin, Jianwei; Lu, Renfu

2004-11-01

261

Calibration methodology and performance characterization of a polarimetric hyperspectral imager  

NASA Astrophysics Data System (ADS)

Polarimetric hyperspectral imaging (P-HSI) has the potential to improve target detection, material identification, and background characterization over conventional hyperspectral imaging and polarimetric imaging. To fully exploit the spectro-polarimetric signatures captured by such an instrument, a careful calibration process is required to remove the spectrally- and polarimetrically-dependent system response (gain). Calibration of instruments operating in the long-wave infrared (LWIR, 8?m to 12 ?m) is further complicated by the polarized spectral radiation generated within the instrument (offset). This paper presents a calibration methodology developed for a LWIR Telops Hyper-Cam modified for polarimetry by replacing the entrance window with a rotatable holographic wire-grid polarizer (4000 line/mm, ZnSe substrate, 350:1 extinction ratio). A standard Fourier-transform spectrometer (FTS) spectro-radiometric calibration is modified to include a Mueller-matrix approach to account for polarized transmission through and polarized selfemission from each optical interface. It is demonstrated that under the ideal polarizer assumption, two distinct blackbody measurements at polarizer angles of 0°, 45°, 90°, and 135° are sufficient to calibrate the system for apparent degree-of-linear-polarization (DoLP) measurements. Noise-equivalent s1, s2, and DoLP are quantified using a wide-area blackbody. A polarization-state generator is used to determine the Mueller deviation matrix. Finally, a realistic scene involving buildings, cars, sky radiance, and natural vegetation is presented.

Holder, Joel G.; Martin, Jacob A.; Pitz, Jeremey; Pezzaniti, Joseph L.; Gross, Kevin C.

2014-05-01

262

SETA-Hyperspectral Imaging Spectrometer for Marco Polo mission.  

NASA Astrophysics Data System (ADS)

The Marco Polo NEO sample return M-class mission has been selected for assessment study within the ESA Cosmic Vision 2015-2025 program. The Marco Polo mission proposes to do a sample return mission to Near Earth Asteroid. With this mission we have the opportunity to return for study in Earth-based laboratories a direct sample of the earliest record of how our solar system formed. The landing site and sample selection will be the most important scientific decision to make during the course of the entire mission. The imaging spectrometer is a key instrument being capable to characterize the mineralogical composition of the entire asteroid and to analyze the of the landing site and the returned sample in its own native environment. SETA is a Hyperspectral Imaging Spectrometer able to perform imaging spectroscopy in the spectral range 400-3300 nm for a complete mapping of the target in order to characterize the mineral properties of the surface. The spectral sampling is of at least 20 nm and the spatial resolution of the order of meter. SETA shall be able to return a detailed determination of the mineralogical composition for the different geologic units as well as the overall surface mineralogy with a spatial resolution of the order of few meters. These compositional characterizations involve the analysis of spectral parameters that are diagnostic of the presence and composition of various mineral species and materials that may be present on the target body. Most of the interesting minerals have electronic and vibrational absorption features in their VIS-NIR reflectance spectra. The SETA design is based on a pushbroom imaging spectrometer operating in the 400-3300 nm range, using a 2D array HgCdTe detector. This kind of instrument allows a simultaneous measurement of a full spectrum taken across the field of view defined by the slit's axis (samples). The second direction (lines) of the hyperspectral image shall be obtained by using the relative motion of the orbiter with respect to the target or by using a scan mirror. The SETA optical concept is mostly inherited from the SIMBIO-SYS/VIHI (Visible Infrared Hyperspectral Imager) imaging spectrometer aboard Bepi Colombo mission but also from other space flying imaging spectrometers, such as VIRTIS (on Rosetta and Venus Express, VIR on DAWN).

de Sanctis, M. Cristina; Filacchione, Gianrico; Capaccioni, Fabrizio; Piccioni, Giuseppe; Ammannito, Eleonora; Capria, M. Teresa; Coradini, Angioletta; Migliorini, Alessandra; Battistelli, Enrico; Preti, Giampaolo

2010-05-01

263

Jeffries Matusita based mixed-measure for improved spectral matching in hyperspectral image analysis  

NASA Astrophysics Data System (ADS)

This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9% and 91.47% accuracy compared to 73.13%, 79.41%, and 85.69% of minimum-distance, SAM and JM measures. It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands).

Padma, S.; Sanjeevi, S.

2014-10-01

264

Hyperspectral sensor for gypsum detection on monumental buildings  

Microsoft Academic Search

A portable hyperspectral device (ASD-FieldSpec FR Pro) has been employed for the characterization of alterations affecting the marble facade of the Santa Maria Novella church (XIII cent.) in Florence (Italy). The ASD-FieldSpec FR Pro collects the reflectance spectra of a selected target area (about 1.5 cm2). The spectra of calcite, gypsum and other mineral phases commonly occurring on outdoor surfaces

M. Camaiti; S. Vettori; M. Benvenuti; L. Chiarantini; P. Costagliola; F. Di Benedetto; S. Moretti; F. Paba; E. Pecchioni

2011-01-01

265

Compressive Fluorescence Microscopy for Biological and Hyperspectral Imaging  

E-print Network

The mathematical theory of compressed sensing (CS) asserts that one can acquire signals from measurements whose rate is much lower than the total bandwidth. Whereas the CS theory is now well developed, challenges concerning hardware implementations of CS-based acquisition devices---especially in optics---have only started being addressed. This paper presents an implementation of compressive sensing in fluorescence microscopy and its applications to biomedical imaging. Our CS microscope combines a dynamic structured wide-field illumination and a fast and sensitive single-point fluorescence detection to enable reconstructions of images of fluorescent beads, cells and tissues with undersampling ratios (between the number of pixels and number of measurements) up to 32. We further demonstrate a hyperspectral mode and record images with 128 spectral channels and undersampling ratios up to 64, illustrating the potential benefits of CS acquisition for higher dimensional signals which typically exhibits extreme redund...

Studer, Vincent; Chahid, Makhlad; Moussavi, Hamed; Candes, Emmanuel; Dahan, Maxime

2012-01-01

266

Time series hyperspectral chemical imaging data: challenges, solutions and applications.  

PubMed

Hyperspectral chemical imaging (HCI) integrates imaging and spectroscopy resulting in three-dimensional data structures, hypercubes, with two spatial and one wavelength dimension. Each spatial image pixel in a hypercube contains a spectrum with >100 datapoints. While HCI facilitates enhanced monitoring of multi-component systems; time series HCI offers the possibility of a more comprehensive understanding of the dynamics of such systems and processes. This implies a need for modeling strategies that can cope with the large multivariate data structures generated in time series HCI experiments. The challenges posed by such data include dimensionality reduction, temporal morphological variation of samples and instrumental drift. This article presents potential solutions to these challenges, including multiway analysis, object tracking, multivariate curve resolution and non-linear regression. Several real world examples of time series HCI data are presented to illustrate the proposed solutions. PMID:21962370

Gowen, A A; Marini, F; Esquerre, C; O'Donnell, C; Downey, G; Burger, J

2011-10-31

267

On the performance improvement for linear discriminant analysis-based hyperspectral image classification  

Microsoft Academic Search

In this paper, we present a strategy to improve the performance of Fisher's linear discriminant analysis (FLDA) in dimensionality reduction for hyperspectral image classification. The practical difficulty of applying FLDA to hyperspectral imagery includes the unavailability of enough training samples and unknown information for all the classes including background. The original FLDA has been modified to avoid the requirements of

Qian Du; Nicolas H. Younan

2008-01-01

268

Hyperspectral image segmentation of the common bile duct  

NASA Astrophysics Data System (ADS)

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.

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

2013-03-01

269

Classification of oat and groat kernels using NIR hyperspectral imaging.  

PubMed

An innovative procedure to classify oat and groat kernels based on coupling hyperspectral imaging (HSI) in the near infrared (NIR) range (1006-1650 nm) and chemometrics was designed, developed and validated. According to market requirements, the amount of groat, that is the hull-less oat kernels, is one of the most important quality characteristics of oats. Hyperspectral images of oat and groat samples have been acquired by using a NIR spectral camera (Specim, Finland) and the resulting data hypercubes were analyzed applying Principal Component Analysis (PCA) for exploratory purposes and Partial Least Squares-Discriminant Analysis (PLS-DA) to build the classification models to discriminate the two kernel typologies. Results showed that it is possible to accurately recognize oat and groat single kernels by HSI (prediction accuracy was almost 100%). The study demonstrated also that good classification results could be obtained using only three wavelengths (1132, 1195 and 1608 nm), selected by means of a bootstrap-VIP procedure, allowing to speed up the classification processing for industrial applications. The developed objective and non-destructive method based on HSI can be utilized for quality control purposes and/or for the definition of innovative sorting logics of oat grains. PMID:23200388

Serranti, Silvia; Cesare, Daniela; Marini, Federico; Bonifazi, Giuseppe

2013-01-15

270

Monitoring biofilm attachment on medical devices surfaces using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Microbial biofilm is a colony of single bacteria cells (planktonic) that attached to surfaces, attract other microorganisms to attach and grow, and together they build an extracellular matrix composed of polysaccharides, protein, and DNA. Eventually, some cells will detach and spread to other surface. Biofilm on medical devices can cause severe infection to all age ranges from infant to adult. Therefore, it is important to detect biofilm in a fast and efficient manner. Hyperspectral imaging was utilized for distinguishing wide area of biofilm coverage on various materials and on different textures of stainless steeltest coupons. Not only is the coverage of biofilm important, but also the shear stress of biofilm on the attached surfaces is significant. This study investigates the effects of shear stress on the adhesion of biofilms on common medical device surfaces such as glass, polycarbonate, polytetrafluoroethylene, and stainless steel with different textures. Biofilm was grown using Ps. aeruginosa and growth was monitored after 24 and 48 hours at 37° C. The coupons covered with biofilm were tilted at 45 degrees and 90 degrees for 30 seconds to induce shear stress and Hyperspectral images were taken. We hypothesize that stronger attachment on rough surface would be able to withstand greater shear stress compared to smooth surface.

Le, Hanh N. D.; Hitchins, Victoria M.; Ilev, Ilko K.; Kim, Do-Hyun

2014-02-01

271

A 868MHz-based wireless sensor network for ground truthing of soil moisture for a hyperspectral remote sensing campaign - design and preliminary results  

NASA Astrophysics Data System (ADS)

Soil moisture and plant available water are important environmental parameters that affect plant growth and crop yield. Hence, they are significant parameters for vegetation monitoring and precision agriculture. However, validation through ground-based soil moisture measurements is necessary for accessing soil moisture, plant canopy temperature, soil temperature and soil roughness with airborne hyperspectral imaging systems in a corresponding hyperspectral imaging campaign as a part of the INTERREG IV A-Project SMART INSPECTORS. At this point, commercially available sensors for matric potential, plant available water and volumetric water content are utilized for automated measurements with smart sensor nodes which are developed on the basis of open-source 868MHz radio modules, featuring a full-scale microcontroller unit that allows an autarkic operation of the sensor nodes on batteries in the field. The generated data from each of these sensor nodes is transferred wirelessly with an open-source protocol to a central node, the so-called "gateway". This gateway collects, interprets and buffers the sensor readings and, eventually, pushes the data-time series onto a server-based database. The entire data processing chain from the sensor reading to the final storage of data-time series on a server is realized with open-source hardware and software in such a way that the recorded data can be accessed from anywhere through the internet. It will be presented how this open-source based wireless sensor network is developed and specified for the application of ground truthing. In addition, the system's perspectives and potentials with respect to usability and applicability for vegetation monitoring and precision agriculture shall be pointed out. Regarding the corresponding hyperspectral imaging campaign, results from ground measurements will be discussed in terms of their contributing aspects to the remote sensing system. Finally, the significance of the wireless sensor network for the application of ground truthing shall be determined.

Näthe, Paul; Becker, Rolf

2014-05-01

272

Image reconstruction and subsurface detection by the application of Tikhonov regularization to inverse problems in hyperspectral images  

NASA Astrophysics Data System (ADS)

Hyperspectral Remote Sensing has the potential to be used as an effective coral monitoring system from space. The problems to be addressed in hyperspectral imagery of coastal waters are related to the medium, clutter, and the object to be detected. In coastal waters the variability due to the interaction between the coast and the sea can bring significant disparity in the optical properties of the water column and the sea bottom. In terms of the medium, there is high scattering and absorption. Related to clutter we have the ocean floor, dissolved salt and gases, and dissolved organic matter. The object to be detected, in this case the coral reefs, has a weak signal, with temporal and spatial variation. In real scenarios the absorption and backscattering coefficients have spatial variation due to different sources of variability (river discharge, different depths of shallow waters, water currents) and temporal fluctuations. The retrieval of information about an object beneath some medium with high scattering and absorption properties requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and detection. This paper presents the development of algorithms for retrieving information and its application to the recognition and classification of coral reefs under water with particles that provide high absorption and scattering. The data was gathered using a high resolution imaging spectrometer (hyperspectral) sensor. A mathematical model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. Tikhonov method of regularization was used in the inversion process to estimate the bottom albedo, ?, of the ocean floor using a priori information. The a priori information is in the form of measured spectral signatures of objects of interest, such as sand, corals, and sea grass.

Jiminez-Rodriguez, Luis O.; Rodriguez-Diaz, Eladio; Velez-Reyes, Miguel; DiMarzio, Charles A.

2003-05-01

273

Superpixel Segmentation for Endmember Detection in Hyperspectral Images  

NASA Astrophysics Data System (ADS)

"Superpixel segmentation" is a novel approach to facilitate statistical analyses of hyperspectral image data with high spatial resolution and subtle spectral features. The method oversegments the image into homogeneous regions each comprised of several contiguous pixels. This can reduce noise by exploiting scene features' spatial contiguity: isolated spectral features are likely to be noise, but spectral features that appear in several adjacent pixels probably indicate real materials in the scene. The mean spectra from each superpixel define a smaller, noise-reduced dataset. This preprocessing step improves endmember detection for the images in our study. Our endmember detection approach presumes a linear (geographic) mixing model for image spectra. We generate superpixels with the Felzenszwalb/Huttenlocher graph-based segmentation [1] with a Euclidean distance metric. This segmentation shatters the image into thousands of superpixels, each with an area of approximately 20 image pixels. We then apply Symmetric Maximum Angle Convex Cone (SMACC) endmember detection algorithm to the data set consisting of the mean spectrum from all superpixels. We evaluated the approach for several images from the Compact Reconnaissance Imaging Spectrometer (CRISM) [2]. We used the 1000-2500nm wavelengths of images frt00003e12 and frt00003fb9. We cleaned the images with atmospheric correction based on Olympus Mons spectra [3] and preprocessed with a radius-1 median filter in the spectral domain. Endmembers produced with and without the superpixel reduction are compared to the representative (mean) spectra of five representative mineral classes identified in an expert analysis of each scene. Expert-identified minerals include mafic minerals and phyllosilicate deposits that in some cases subtended just a few tens of pixels. Only the endmembers from the superpixel approach reflected all major mineral constituents in the images. Additionally, the superpixel endmembers are more quantitatively more faithful to the mean mineral spectra, reducing average squared error over all wavelengths for comparisons between endmembers and the closest-matching mineral spectrum (Figures). We conclude that superpixel segmentation holds promise for improving signal-to-noise for statistical analyses of hyperspectral images with high spatial resolution. References [1] P.F. Felzenszwalb and D.P. Huttenlocher, “Efficient graph-based image segmentation,” International Journal of Computer Vision, vol. 59:2, pp. 167-181, 2004. [2] S. Murchie et al., “Compact reconnaissance imaging spectrometer for Mars (CRISM) on Mars reconnaissance orbiter,” J. Geophys. Res, vol. 112, no. 5, 2007. [3] F. Morgan et al., “CAT tutorial,” CRISM Data User’s Workshop, Lunar and Planetary Science Conference 2009.

Thompson, D. R.; de Granville, C.; Gilmore, M. S.; Castano, R.

2009-12-01

274

Model acquisition and invariant tracking of unknown materials in hyperspectral images.  

PubMed

We consider the problem of acquiring models for unknown materials in airborne 0.4-2.5 microm hyperspectral imagery and using these models to identify the unknown materials in image data obtained under significantly different conditions. The material models are generated with use of an airborne sensor spectrum measured under unknown conditions and a physical model for spectral variability. For computational efficiency, the material models are represented by using low-dimensional spectral subspaces. We demonstrate the effectiveness of the material models by using a set of material tracking experiments in HYDICE images acquired in forest and desert environments over widely varying conditions. We show that techniques based on the new representation significantly outperform methods based on direct spectral matching. PMID:11488499

Slater, D; Healey, G

2001-08-01

275

Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging.  

PubMed

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. PMID:16306643

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

2005-12-01

276

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

NASA Astrophysics Data System (ADS)

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.

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

2010-04-01

277

Adaptive noise estimation from highly textured hyperspectral images.  

PubMed

Accurate approximation of noise in hyperspectral (HS) images plays an important role in better visualization and image processing. Conventional algorithms often hypothesize the noise type to be either purely additive or of a mixed noise type for the signal-dependent (SD) noise component and the signal-independent (SI) noise component in HS images. This can result in application-driven algorithm design and limited use in different noise types. Moreover, as the highly textured HS images have abundant edges and textures, existing algorithms may fail to produce accurate noise estimation. To address these challenges, we propose a noise estimation algorithm that can adaptively estimate both purely additive noise and mixed noise in HS images with various complexities. First, homogeneous areas are automatically detected using a new region-growing-based approach, in which the similarity of two pixels is calculated by a robust spectral metric. Then, the mixed noise variance of each homogeneous region is estimated based on multiple linear regression technology. Finally, intensities of the SD and SI noise are obtained with a modified scatter plot approach. We quantitatively evaluated our algorithm on the synthetic HS data. Compared with the benchmarking and state-of-the-art algorithms, the proposed algorithm is more accurate and robust when facing images with different complexities. Experimental results with real Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images further demonstrated the superiority of our algorithm. PMID:25402795

Fu, Peng; Li, Changyang; Xia, Yong; Ji, Zexuan; Sun, Quansen; Cai, Weidong; Feng, David Dagan

2014-10-20

278

About Classification Methods Based on Tensor Modelling for Hyperspectral Images  

NASA Astrophysics Data System (ADS)

Denoising and Dimensionality reduction (DR) are key issue to improve the classifiers efficiency for Hyperspectral images (HSI). The multi-way Wiener filtering recently developed is used, Principal and independent component analysis (PCA, ICA) and projection pursuit (PP) approaches to DR have been investigated. These matrix algebra methods are applied on vectorized images. Thereof, the spatial rearrangement is lost. To jointly take advantage of the spatial and spectral information, HSI has been recently represented as tensor. Offering multiple ways to decompose data orthogonally, we introduced filtering and DR methods based on multilinear algebra tools. The DR is performed on spectral way using PCA, or PP joint to an orthogonal projection onto a lower subspace dimension of the spatial ways. We show the classification improvement using the introduced methods in function to existing methods. This experiment is exemplified using real-world HYDICE data.

Bourennane, Salah; Fossati, Caroline

279

Efficient detection in hyperspectral imagery  

Microsoft Academic Search

Hyperspectral sensors collect hundreds of narrow and contiguously spaced spectral bands of data. Such sensors provide fully registered high resolution spatial and spectral images that are invaluable in discriminating between man-made objects and natural clutter backgrounds. The price paid for this high resolution data is extremely large data sets, several hundred of Mbytes for a single scene, that make storage

Susan M. Schweizer; José M. F. Moura

2001-01-01

280

Fusion of hyperspectral images and lidar-based dems for coastal mapping  

NASA Astrophysics Data System (ADS)

Coastal mapping is essential for a variety of applications such as coastal resource management, coastal environmental protection, and coastal development and planning. Various mapping techniques, like ground and aerial surveying, have been utilized in mapping coastal areas. Recently, multispectral and hyperspectral satellite images and elevation data from active sensors have also been used in coastal mapping. Integrating these datasets can provide more reliable coastal information. This paper presents a novel technique for coastal mapping from an airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral image and a light detection and ranging (LIDAR)-based digital elevation model (DEM). The DEM was used to detect and create a vector layer for building polygons. Subsequently, building pixels were removed from the AVIRIS image and the image was classified with a supervised classifier to discriminate road and water pixels. Two vector layers for the road network and the shoreline segments were vectorized from road pixels and water-body border pixels using several image-processing algorithms. The geometric accuracy and completeness of the results were evaluated. The average positional accuracies for the building, road network, and shoreline layers were 2.3, 5.7, and 7.2 m, respectively. The detection rates of the three layers were 93.2%, 91.3%, and 95.2%, respectively. Results confirmed that utilizing laser ranging data to detect and remove buildings from optical images before the classification process enhances the outcomes of this process. Consequently, integrating laser and optical data provides high-quality and more reliable coastal geospatial information.

Elaksher, Ahmed F.

2008-07-01

281

Application of hyperspectral fluorescence lifetime imaging to tissue autofluorescence: arthritis  

NASA Astrophysics Data System (ADS)

Tissue contains many natural fluorophores and therefore by exploiting autofluorescence, we can obtain information from tissue with less interference than conventional histological techniques. However, conventional intensity imaging is prone to artifacts since it is an absolute measurement. Fluorescence lifetime and spectral measurements are relative measurements and therefore allow for better measurements. We have applied FLIM and hyperspectral FLIM to the study of articular cartilage and its disease arthritis. We have analyzed normal human articular cartilage and cartilage which was in the early stages of disease. In this case, it was found that FLIM was able to detect changes in the diseased tissue that were not detectable with the conventional diagnosis. Specifically, the fluorescence lifetimes (FL) of the cells were different between the two samples. We have also applied hyperspectral FLIM to degraded cartilage through treatment with interleukin-1. In this case, it was found that there was a shift in the emission spectrum with treatment and that the lifetime had also increased. We also showed that there was greater contrast between the cells and the extracellular matrix (ECM) at longer wavelengths.

Talbot, C. B.; Benninger, R. K. P.; de Beule, P.; Requejo-Isidro, J.; Elson, D. S.; Dunsby, C.; Munro, I.; Neil, M. A.; Sandison, A.; Sofat, N.; Nagase, H.; French, P. M. W.; Lever, M. J.

2005-08-01

282

Vicarious calibration of the Ocean PHILLS hyperspectral sensor using a coastal tree-shadow method  

Microsoft Academic Search

Ocean color remote-sensing systems require highly accurate calibration (<0.5%) for accurate retrieval of water properties. This accuracy is typically achieved by vicarious calibration which is done by comparing the atmospherically corrected remote-sensing data to accurate estimates of the water-leaving radiance. Here we present a new method for vicarious calibration of a hyperspectral sensor that exploits shadows cast by trees and

Anthony M. Filippi; Kendall L. Carder; Curtiss O. Davis

2006-01-01

283

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images  

NASA Technical Reports Server (NTRS)

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Kiely, A.; Klimesh, M.; Xie, H.; Aranki, N.

2005-01-01

284

The Robust Classification of Hyperspectral Images Using Adaptive Wavelet Kernel Support Vector Data Description  

E-print Network

Detection of targets in hyperspectral images is a specific case of one-class classification. It is particularly relevant in the area of remote sensing and has received considerable interest in the past few years. The thesis proposes the use...

Kollegala, Revathi

2012-07-16

285

DETECTION AND IDENTIFICATION OF TOXIC AIR POLLUTANTS USING AIRBORNE LWIR HYPERSPECTRAL IMAGING  

EPA Science Inventory

Airborne longwave infrared LWIR) hyperspectral imagery was utilized to detect and identify gaseous chemical release plumes at sites in sourthern Texzas. The Airborne Hysperspectral Imager (AHI), developed by the University of Hawaii was flown over a petrochemical facility and a ...

286

Flash hyperspectral imaging of non-stellar astronomical objects James F. Scholl*1a,c  

E-print Network

galaxies and quasars with active nuclei, colliding / interacting galaxies, and globular cluster systems around our own Milky Way and other galaxies. Flash hyperspectral imaging adds coherence-time limited

Dereniak, Eustace L.

287

Full field imaging based instantaneous hyperspectral absolute refractive index measurement  

SciTech Connect

Multispectral refractometers typically measure refractive index (RI) at discrete monochromatic wavelengths via a serial process. We report on the demonstration of a white light full field imaging based refractometer capable of instantaneous multispectral measurement of absolute RI of clear liquid/gel samples across the entire visible light spectrum. The broad optical bandwidth refractometer is capable of hyperspectral measurement of RI in the range 1.30 1.70 between 400nm 700nm with a maximum error of 0.0036 units (0.24% of actual) at 414nm for a = 1.50 sample. We present system design and calibration method details as well as results from a system validation sample.

Baba, Justin S [ORNL; Boudreaux, Philip R [ORNL

2012-01-01

288

Rapidly updated hyperspectral sounding and imaging data for severe storm prediction  

NASA Astrophysics Data System (ADS)

Several studies have shown that a geostationary hyperspectral imager/sounder can provide the most significant value increase in short term, regional numerical prediction weather models over a range of other options. In 1998, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) proposal was selected by NASA as the New Millennium Earth Observation 3 program over several other geostationary instrument development proposals. After the EO3 GIFTS flight demonstration program was changed to an Engineering Development Unit (EDU) due to funding limitations by one of the partners, the EDU was subjected to flight-like thermal vacuum calibration and testing and successfully validated the breakthrough technologies needed to make a successful observatory. After several government stops and starts, only EUMETSAT's Meteosat Third Generation (MTG-S) sounder is in operational development. Recently, a commercial partnership has been formed to fill the significant data gap. AsiaSat has partnered with GeoMetWatch (GMW)1 to fund the development and launch of the Sounding and Tracking Observatory for Regional Meteorology (STORMTM) sensor, a derivative of the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) EDU that was designed, built, and tested by Utah State University (USU). STORMTM combines advanced technologies to observe surface thermal properties, atmospheric weather, and chemistry variables in four dimensions to provide high vertical resolution temperature and moisture sounding information, with the fourth dimension (time) provided by the geosynchronous satellite platform ability to measure a location as often as desired. STORMTM will enhance the polar orbiting imaging and sounding measurements by providing: (1) a direct measure of moisture flux and altitude-resolved water vapor and cloud tracer winds throughout the troposphere, (2) an observation of the time varying atmospheric thermodynamics associated with storm system development, and (3) the transport of tropospheric pollutant gases. The AsiaSat/GMW partnership will host the first STORMTM sensor on their AsiaSat 9 telecommunications satellite at 122 E over the Asia Pacific area. GMW's business plan is to sell the unique STORM data and data products to countries and companies in the satellite coverage area. GMW plans to place 6 STORMTM sensors on geostationary telecommunications satellites to provide global hyperspectral sounding and imaging data. Utah State University's Advanced Weather Systems Laboratory (AWS) will build the sensors for GMW.

Bingham, Gail; Jensen, Scott; Elwell, John; Cardon, Joel; Crain, David; Huang, Hung-Lung (Allen); Smith, William L.; Revercomb, Hank E.; Huppi, Ronald J.

2013-09-01

289

COMPARISON OF SPACEBORNE AND AIRBORNE HYPERSPECTRAL IMAGING SYSTEMS FOR ENVIRONMENTAL MAPPING  

Microsoft Academic Search

The main purpose of this study was to compare hyperspectral remotely sensed data collected by the Hyperion satellite, and the airborne Real-time Data Acquisition Camera System (RDACS-3) and the Airborne Visible\\/Infrared Imaging Spectrometer (AVIRIS) for environmental mapping and vegetation species identification. Hyperion was NASA's first hyperspectral imager aboard NASA's Earth Observing-1 (EO -1) spacecraft. The EO -1 mission had three

Haluk Cetin

290

An AOTF-based hyperspectral imaging system for field use in ecophysiological and agricultural applications  

Microsoft Academic Search

An AOTF (Acousto-Optic Tunable Filter)-based spectral imager was developed for hyperspectral measurement of plant reflectance in the field. A hyperspectral image cube for the spectral region between 450-900 nm could be acquired at 3 to 5 nm resolution intervals within a few seconds. The system was light and compact, and both the spectral wavelengths and intervals were programmable with PC

Y. Inoue; J. Peñuelas

2001-01-01

291

Regularized Feature Extractions and Support Vector Machines for Hyperspectral Image Data Classification  

Microsoft Academic Search

\\u000a In this study, the performances of using parametric\\/ nonparametric regularized feature extractions and support vector machine\\u000a for hyperspectral image classification is explored when the training sample size is small. The classification accuracies of\\u000a RBF-based SVM using two feature extractions with three regularization techniques are evaluated. The results of two hyperspectral\\u000a image classification experiments show that the performance of the combination

Bor-chen Kuo; Kuang-yu Chang

2005-01-01

292

Non–destructive Detection of Hollow Heart in Potatoes Using Hyperspectral Imaging  

Microsoft Academic Search

\\u000a We present a new method to detect the presence of the hollow heart, an internal disorder of the potato tubers, using hyperspectral imaging technology in the infrared region. A set of 468 hyperspectral\\u000a cubes of images has been acquired from Agria variety potatoes, that have been cut later to check the presence of a hollow\\u000a heart. We developed several experiments

Angel Dacal-Nieto; Arno Formella; Pilar Carrión; Esteban Vazquez-Fernandez; Manuel Fernández-Delgado

293

Mosaicing of hyperspectral images: the application of a spectrograph imaging device.  

PubMed

Hyperspectral monitoring of large areas (more than 10 km(2)) can be achieved via the use of a system employing spectrometers and CMOS cameras. A robust and efficient algorithm for automatically combining multiple, overlapping images of a scene to form a single composition (i.e., for the estimation of the point-to-point mapping between views), which uses only the information contained within the images themselves is described here. The algorithm, together with the 2D fast Fourier transform, provides an estimate of the displacement between pairs of images by accounting for rotations and changes of scale. The resulting mosaic was successively georeferenced within the WGS-84 geographic coordinate system. This paper also addresses how this information can be transferred to a push broom type spectral imaging device to build the hyperspectral cube of the area prior to land classification. The performances of the algorithm were evaluated using sample images and image sequences acquired during a proximal sensing field campaign conducted in San Teodoro (Olbia-Tempio-Sardinia). The hyperspectral cube closely corresponds to the mosaic. Mapping allows for the identification of objects within the image and agrees well with ground-truth measurements. PMID:23112597

Moroni, Monica; Dacquino, Carlo; Cenedese, Antonio

2012-01-01

294

Mosaicing of Hyperspectral Images: The Application of a Spectrograph Imaging Device  

PubMed Central

Hyperspectral monitoring of large areas (more than 10 km2) can be achieved via the use of a system employing spectrometers and CMOS cameras. A robust and efficient algorithm for automatically combining multiple, overlapping images of a scene to form a single composition (i.e., for the estimation of the point-to-point mapping between views), which uses only the information contained within the images themselves is described here. The algorithm, together with the 2D fast Fourier transform, provides an estimate of the displacement between pairs of images by accounting for rotations and changes of scale. The resulting mosaic was successively georeferenced within the WGS-84 geographic coordinate system. This paper also addresses how this information can be transferred to a push broom type spectral imaging device to build the hyperspectral cube of the area prior to land classification. The performances of the algorithm were evaluated using sample images and image sequences acquired during a proximal sensing field campaign conducted in San Teodoro (Olbia-Tempio—Sardinia). The hyperspectral cube closely corresponds to the mosaic. Mapping allows for the identification of objects within the image and agrees well with ground-truth measurements. PMID:23112597

Moroni, Monica; Dacquino, Carlo; Cenedese, Antonio

2012-01-01

295

Line-Based Registration of Dsm and Hyperspectral Images  

NASA Astrophysics Data System (ADS)

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.

Avbelj, J.; Iwaszczuk, D.; Müller, R.; Reinartz, P.; Stilla, U.

2013-04-01

296

Shearlet transform based anomaly detection for hyperspectral image  

NASA Astrophysics Data System (ADS)

Hyperspectral image (HI) contains data in hundreds of narrow contiguous spectral bands, thus it provides a powerful means to distinguish different materials on the basis of their unique spectral signatures. Anomaly detection (AD) is one key part of its application. The shearlet transform (ST) is a new two-dimensional extension of the wavelet transform using multiscale and directional filter banks, which can effectively captures smooth contours that are the dominant feature in natural image. In this paper, ST is used in AD for the HI. Firstly, the raw HI data is decomposed into several directional subband at multiple-scale via ST. Thus, the background signal would be reduced in each subband. Secondly, the fourth partial differential equation method is adopted to modify the coefficient of each sub-band, which is for background suppression and anomaly signal enhancement. Thirdly, the kernel-based RX algorithm is adopted to detect the anomaly in each sub-band. Finally, the anomaly signal image is achieved by reconstructing the image with all modified sub-band. Several experiments with a HYDICE data are fulfilled to validate the performance of the proposed method. Compared with the original RX algorithm, experimental results show that the proposed algorithm has better detection performance and lower false alarm probability.

Zhou, Huixin; Niu, Xiaoxue; Qin, Hanlin; Zhou, Jun; Lai, Rui; Wang, Bingjian

2012-10-01

297

[Harmonic analysis fusion of hyperspectral image and its spectral information fidelity evaluation].  

PubMed

Combined with the Hyperion hyperspectral image and ALI high spatial resolution band of the EO-1 satellite, the paper puts forward the harmonic analysis fusion (HAF) algorithm of hyperspectral image and the derivative spectral d-value's information entropy (DSD-IE) model of the spectral-fused information fidelity evaluation. Through calculating and evaluating some parameters such as the DSD-IE values, average gradient and standard deviation of the sample spectra meanwhile compared with the fused hyperspectral images by the traditional methods like the principal component analysis (PCA), Gram-Schmidt and wavelet, the fused hyperspectral iamge by the HAF has proved to have the higher information degree of spatial integration and spectral fidelity, and the better superiorities in the reliability, accuracy and applicability. PMID:24369660

Yang, Keming; Zhang, Tao; Wang, Li-bo; Qian, Xiao-li; Wang, Lin-wei; Liu, Shi-wen

2013-09-01

298

Interference-invariant target detection in hyperspectral images  

NASA Astrophysics Data System (ADS)

In this paper we address the problem of detecting targets in hyperspectral images when the target signature is buried in random noise and interference (from other materials in the same pixel). We assume that the hyperspectral pixel measurement is a linear combination of the target and interference signatures observed in additive noise. The linear mixing assumption leads to a linear vector space interpretation of the measurement vector, which can be decomposed into a noise-only subspace and a target-plus- interference subspace. While it is true that the target and interference subspaces are orthogonal to the noise-only subspace, the target subspace and interference subspace are, in general, not orthogonal. The non-orthogonality between the target and interference subspaces results in leakage of interference signals into the output of matched filters resulting in false detections (i.e., higher false alarm rates). In this paper, we replace the Matched Filer Detector (MFD), which is based on orthogonal projections, with a Matched Subspace Detector (MSD), which is built on non- orthogonal or oblique projections. The advantage of oblique projections is that they eliminate the leakage of interference signals into the detector, thereby making detectors based on oblique projections invariant to the amount of interference. Furthermore, under Gaussian assumptions for the additive noise, it has been shown that the MSD is Uniformly Most Powerful (higher probability of detect for a fixed probability of false alarm) among all detectors that share this invariance to interference power. In this paper we evaluate the ability of two versions of the MSD to detect targets in HYDICE data collected over sites A and B located at the U.S. Army Yuma proving grounds. We compute data derived receiver operating characteristics (ROC) curves and show that the MSD out- performs the MFD.

Nichols, Terry L.; Thomas, John K.; Kober, Wolfgang; Velten, Vincent J.

1998-07-01

299

Effect of atmospheric interference and sensor noise in retrieval of optically active materials in the ocean by hyperspectral remote sensing  

Microsoft Academic Search

We present a method to construct the best linear estimate of optically active material concentration from ocean radiance spectra measured through an arbitrary atmosphere layer by a hyperspectral sensor. The algorithm accounts for sensor noise. Optical models of seawater and maritime atmosphere were used to obtain the joint distribution of spectra and concentrations required for the algorithm. The accuracy of

Iosif M. Levin; Elizaveta Levina

2007-01-01

300

Damage and quality assessment in wheat by NIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Fusarium head blight is a fungal disease that affects the world's small grains, such as wheat and barley. Attacking the spikelets during development, the fungus causes a reduction of yield and grain of poorer processing quality. It also is a health concern because of the secondary metabolite, deoxynivalenol, which often accompanies the fungus. While chemical methods exist to measure the concentration of the mycotoxin and manual visual inspection is used to ascertain the level of Fusarium damage, research has been active in developing fast, optically based techniques that can assess this form of damage. In the current study a near-infrared (1000-1700 nm) hyperspectral image system was assembled and applied to Fusarium-damaged kernel recognition. With anticipation of an eventual multispectral imaging system design, 5 wavelengths were manually selected from a pool of 146 images as the most promising, such that when combined in pairs or triplets, Fusarium damage could be identified. We present the results of two pairs of wavelengths [(1199, 1474 nm) and (1315, 1474 nm)] whose reflectance values produced adequate separation of kernels of healthy appearance (i.e., asymptomatic condition) from kernels possessing Fusarium damage.

Delwiche, Stephen R.; Kim, Moon S.; Dong, Yanhong

2010-04-01

301

A parameter free approach for determining the intrinsic dimension of a hyperspectral image using  

E-print Network

data cube of size (m Ã? n Ã? p). This is a set of p images of size N = m Ã? n pixels, where all images1 A parameter free approach for determining the intrinsic dimension of a hyperspectral image using--Determining the intrinsic dimension of a hyper- spectral image is an important step in the spectral unmixing process

Damelin, Steven

302

Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean  

Microsoft Academic Search

Hyperspectral imaging data have been collected with different types of imaging spectrometers from aircraft and satellite platforms since the mid-1980s. Because the solar radiation on the sun-surface-sensor path in the 0.4–2.5 µm visible and near-IR spectral regions is subject to absorption and scattering by atmospheric gases and aerosols, the hyperspectral imaging data contains atmospheric effects. In order to use hyperspectral imaging

Bo-Cai Gao; Marcos J. Montes; Curtiss O. Davis; Alexander F. H. Goetz

2009-01-01

303

CCD imaging sensors  

NASA Technical Reports Server (NTRS)

A method for promoting quantum efficiency (QE) of a CCD imaging sensor for UV, far UV and low energy x-ray wavelengths by overthinning the back side beyond the interface between the substrate and the photosensitive semiconductor material, and flooding the back side with UV prior to using the sensor for imaging. This UV flooding promotes an accumulation layer of positive states in the oxide film over the thinned sensor to greatly increase QE for either frontside or backside illumination. A permanent or semipermanent image (analog information) may be stored in a frontside SiO.sub.2 layer over the photosensitive semiconductor material using implanted ions for a permanent storage and intense photon radiation for a semipermanent storage. To read out this stored information, the gate potential of the CCD is biased more negative than that used for normal imaging, and excess charge current thus produced through the oxide is integrated in the pixel wells for subsequent readout by charge transfer from well to well in the usual manner.

Janesick, James R. (Inventor); Elliott, Stythe T. (Inventor)

1989-01-01

304

Hyperspectral Imaging and Association Phenomenology of Pedestrians in a Cluttered Urban Environment  

NASA Astrophysics Data System (ADS)

Remote hyperspectral imaging (HSI) has shown promise in several applications such as object detection and tracking. Typically research has focused on large objects, such as vehicles, for tracking due to the spatial resolution of current operational HSI systems. This research seeks to extend the utility of applying HSI to human pedestrian detection using the reflective solar spectral range between 400 - 2500 nm. A phenomenological investigation of a novel scheme to differentiate between pedestrians is studied. By applying the basics of detection theory, this research focuses on being able to differentiate between pedestrians, as well as background materials. Specifically, this research explores the likelihood of detecting and differentiating pedestrians based on four defined subregions comprised of the exposed hair, skin, and the fabrics used for shirts and trousers. The scope of this work encompassed detecting a pedestrian of interest outdoors among other pedestrians in an urban environment consisting of a mixture of asphalt, concrete, grass, and trees. Two unique datasets were created during the course of this effort. One dataset was a collection of fully ground-truthed hyperspectral images of pedestrians in an urban environment. A second dataset was a synthetic rendering of the real-world ground truthed pedestrian scene developed using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Subregion separability analysis results, using spectral reflectance data, provided strong evidence that combining the observable spectral features of detectable subregions is a viable means of distinguishing between pedestrians. Further analysis using real-world HSI data demonstrated that the detection and classification of the pedestrian subregions when changes in illumination, location, and background occur within the field of view of a hyperspectral sensor is achievable with a greater than 60% accuracy. In addition to the direct detection and association analysis using the full spectral range, trade-offs in using spectral subsets of the reflectance spectrum were explored for their utility in detecting and classifying each of the pedestrian subregions. The results suggested that the clothing worn on a pedestrian's torso is the dominant feature for classification and either using a full spectral range (400 - 2500 nm) with 152 spectral bands or the visible to near-infrared spectral range (400 - 1000 nm) with 39 bands provides similar capability to the full spectral range for distinguishing among pedestrians with similar skin and clothing types.

Herweg, Jared A.

305

In vivo hyperspectral imaging of traumatic skin injuries in a porcine model  

NASA Astrophysics Data System (ADS)

Studies of immediate skin reactions are important to understand the underlying biological mechanisms involved in traumatic or chemical damage to the skin. In this study the spatial and spectral information provided by hyperspectral images was used to identify and characterize non-penetrating skin injuries in a porcine model. A hyperspectral imaging system (Hyspex, Norsk Elektro Optikk AS) was used to monitor the temporal development of minor skin injuries in an anesthetized Norwegian domestic pig. Hyperspectral data were collected in the wavelength range 400-1000 nm (VNIR), with a spectral sampling interval of 3.7 nm. The measurements were initiated immediately after inflicting the injury, and were repeated at least five times at each site with irregular frequency. The last measurement was performed 4 hours after injury. Punch biopsies (5 mm), were collected from adjacent normal skin, and at the center and the margin of each injury. The study was approved by the national animal research authority. The hyperspectral data were analyzed with respect to oxy- and deoxyhemoglobin, and erythema index. The skin biopsies were examined to determine the extent of skin damage in the bruised zones. Preliminary results show that hyperspectral imaging allows discrimination between traumatized skin and normal skin in an early phase. The extent and location of the hemorrhages can be determined from hyperspectral images. These findings might contribute to a better understanding of immediate skin reactions to minor trauma, and thereby the development of a better diagnostic modality for non-penetrating skin injuries in forensic medicine.

Randeberg, Lise L.; Winnem, Andreas M.; Larsen, Eivind L. P.; Haaverstad, Rune; Haugen, Olav A.; Svaasand, Lars O.

2007-02-01

306

Differentiation of bacterial colonies and temporal growth patterns using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Detection and identification of bacteria are important for health and safety. Hyperspectral imaging offers the potential to capture unique spectral patterns and spatial information from bacteria which can then be used to detect and differentiate bacterial species. Here, hyperspectral imaging has been used to characterize different bacterial colonies and investigate their growth over time. Six bacterial species (Pseudomonas fluorescens, Escherichia coli, Serratia marcescens, Salmonella enterica, Staphylococcus aureus, Enterobacter aerogenes) were grown on tryptic soy agar plates. Hyperspectral data were acquired immediately after, 24 hours after, and 96 hours after incubation. Spectral signatures from bacterial colonies demonstrated repeatable measurements for five out of six species. Spatial variations as well as changes in spectral signatures were observed across temporal measurements within and among species at multiple wavelengths due to strengthening or weakening reflectance signals from growing bacterial colonies based on their pigmentation. Between-class differences and within-class similarities were the most prominent in hyperspectral data collected 96 hours after incubation.

Mehrübeoglu, Mehrube; Buck, Gregory W.; Livingston, Daniel W.

2014-09-01

307

Development and characterization of a chromotomosynthetic hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

The chromotomosynthetic imaging (CTI) system can simultaneously provide usable 3-D spatial and spectral information, high-frame rate slitless 1-D spectra, and generate 2-D imagery equivalent to that collected with no prism in the optical system. With this prototype, data was collected 3--4 times faster than a Liquid Crystal Tunable Filter (LCTF) with a 100x increase in spectral bins due to the amount of data and high spectral throughput. Spectral resolution was measured to be 0.6 nm at the shortest wavelengths, degrading to over 10 nm at wavelengths approaching 800 nm and limited by chromatic aberration effect on the point spread function. A mathematical error function defining the degradation of performance in the 3-D reconstructed image cube was derived, capturing effects of systematic instrumental error caused by prism spectral dispersion, prism and mount misalignment, detector array position and tilt, and prism rotation angle. The wavelength region where prism dispersion is highest (<500 nm) is most sensitive to loss of spectral resolution in the presence of systematic error, while wavelengths >600 nm suffer mostly from a shift of the spectral peaks. The quality of the spectral resolution in the reconstructed hyperspectral imagery was degraded by as much as a factor of two in the blue spectral region with less than 1° total angular error in mount alignment in the two axes of freedom. Target classification for point sources yielded the same 5--6 target classes as a an LCTF, although there was a 25% misclassification rate possibly due to the spectral similarity in the sources. For a mosaic target, intensities for each element were within 10% of the baseline, with extracted spectral and spatial information matching that collected by the LCTF. The CTI and LCTF produced hyperspectral imagery from an open propane flame clearly capturing the sharp C2 Swan band emission lines in the 400--650 nm range. The spectral resolution of the CTI proved to be better than the LCTF as expected, resolving the CH and C2 peak I emission lines in the flame core. The LCTF was superior in capturing spatial structure and intensity in the dimmer regions of the torch where artifacts left little contrast in the CTI image.

Bostick, Randall L.

308

Thermal infrared hyperspectral imaging from vehicle-carried instrumentation  

NASA Astrophysics Data System (ADS)

Stand-off identification in the field using thermal infrared spectrometers (hyperspectral) is a maturing technique for gases and aerosols. However, capabilities to identify solid-phase materials on the surface lag substantially, particularly for identification in the field without benefit of ground truth (e.g. for "denied areas"). Spectral signatures of solid phase materials vary in complex and non-intuitive ways, including non-linear variations with surface texture, particle size, and intimate mixing. Also, in contrast to airborne or satellite measurements, reflected downwelling radiance strongly affects the signature measured by field spectrometers. These complex issues can confound interpretations or cause a misidentification in the field. Problems that remain particularly obstinate are (1) low ambiguity identification when there is no accompanying ground truth (e.g. measurements of denied areas, or Mars surface by the 2003 Mars lander spectrometer); (2) real- or near real-time identification, especially when a low ambiguity answer is critical; (3) identification of intimate mixtures (e.g. two fine powders mixed together) and targets composed of very small particles (e.g. aerosol fallout dust, some tailings); and (4) identification of non-diffuse targets (e.g. smooth coatings such as paint and desert varnish), particularly when measured at a high emission angle. In most studies that focus on gas phase targets or specific manmade targets, the solid phase background signatures are called "clutter" and are thrown out. Here we discuss our field spectrometer images measured of test targets that were selected to include a range of particle sizes, diffuse, non-diffuse, high, and low reflectance materials. This study was designed to identify and improve understanding of the issues that complicate stand-off identification in the field, with a focus on developing identification capabilities to proceed without benefit of ground truth. This information allows both improved measurement protocols and identification quality. The Aerospace Corporation has a mature program for field hyperspectral measurements using van-mounted thermal-infrared spectrometers that raster-scan images. Aerospace is a non-profit Federally Funded Research and Development Center (FFRDC), managed by the Department of Defense. The precisely controlled viewing geometery, imaging capabilities, and sensitivity of the spectrometers used are critical to identifying and studying issues that can confound interpretations or cause a misidentification. We have released a portion of this data set publicly, and encourage researchers interested in the data set to contact us. More information is at www.lpi.usra.edu/science/kirkland.

Kirkland, Laurel E.; Herr, Kenneth C.; Adams, Paul M.; McAfee, John; Salisbury, John

2002-09-01

309

Development and integration of Raman imaging capabilities to Sandia National Laboratories hyperspectral fluorescence imaging instrument.  

SciTech Connect

Raman spectroscopic imaging is a powerful technique for visualizing chemical differences within a variety of samples based on the interaction of a substance's molecular vibrations with laser light. While Raman imaging can provide a unique view of samples such as residual stress within silicon devices, chemical degradation, material aging, and sample heterogeneity, the Raman scattering process is often weak and thus requires very sensitive collection optics and detectors. Many commercial instruments (including ones owned here at Sandia National Laboratories) generate Raman images by raster scanning a point focused laser beam across a sample--a process which can expose a sample to extreme levels of laser light and requires lengthy acquisition times. Our previous research efforts have led to the development of a state-of-the-art two-dimensional hyperspectral imager for fluorescence imaging applications such as microarray scanning. This report details the design, integration, and characterization of a line-scan Raman imaging module added to this efficient hyperspectral fluorescence microscope. The original hyperspectral fluorescence instrument serves as the framework for excitation and sample manipulation for the Raman imaging system, while a more appropriate axial transmissive Raman imaging spectrometer and detector are utilized for collection of the Raman scatter. The result is a unique and flexible dual-modality fluorescence and Raman imaging system capable of high-speed imaging at high spatial and spectral resolutions. Care was taken throughout the design and integration process not to hinder any of the fluorescence imaging capabilities. For example, an operator can switch between the fluorescence and Raman modalities without need for extensive optical realignment. The instrument performance has been characterized and sample data is presented.

Timlin, Jerilyn Ann; Nieman, Linda T.

2005-11-01

310

Hyperspectral digital imagery collection experiment (HYDICE)  

Microsoft Academic Search

In order to advance the state-of-the-art in the collection of imaging spectroscopy, the U.S. Navy Space and Warfare Systems Command sponsored the development and fabrication of a new generation, well calibrated hyperspectral imaging spectrometer. Called the Hyperspectral Digital Imagery Collection Experiment (HYDICE), the sensor was built by Hughes Danbury Optical Systems, Danbury, Conn., delivered for integration into the Environmental Institute

Peter A. Mitchell

1995-01-01

311

Hyperspectral imaging applied to complex particulate solids systems  

NASA Astrophysics Data System (ADS)

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.

Bonifazi, Giuseppe; Serranti, Silvia

2008-04-01

312

Near infrared hyperspectral imaging for forensic analysis of document forgery.  

PubMed

Hyperspectral images in the near infrared range (HSI-NIR) were evaluated as a nondestructive method to detect fraud in documents. Three different types of typical forgeries were simulated by (a) obliterating text, (b) adding text and (c) approaching the crossing lines problem. The simulated samples were imaged in the range of 928-2524 nm with spectral and spatial resolutions of 6.3 nm and 10 ?m, respectively. After data pre-processing, different chemometric techniques were evaluated for each type of forgery. Principal component analysis (PCA) was performed to elucidate the first two types of adulteration, (a) and (b). Moreover, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) was used in an attempt to improve the results of the type (a) obliteration and type (b) adding text problems. Finally, MCR-ALS and Partial Least Squares-Discriminant Analysis (PLS-DA), employed as a variable selection tool, were used to study the type (c) forgeries, i.e. crossing lines problem. Type (a) forgeries (obliterating text) were successfully identified in 43% of the samples using both the chemometric methods (PCA and MCR-ALS). Type (b) forgeries (adding text) were successfully identified in 82% of the samples using both the methods (PCA and MCR-ALS). Finally, type (c) forgeries (crossing lines) were successfully identified in 85% of the samples. The results demonstrate the potential of HSI-NIR associated with chemometric tools to support document forgery identification. PMID:25118338

Silva, Carolina S; Pimentel, Maria Fernanda; Honorato, Ricardo S; Pasquini, Celio; Prats-Montalbán, José M; Ferrer, Alberto

2014-10-21

313

Wavefront image sensor chip  

PubMed Central

We report the implementation of an image sensor chip, termed wavefront image sensor chip (WIS), that can measure both intensity/amplitude and phase front variations of a light wave separately and quantitatively. By monitoring the tightly confined transmitted light spots through a circular aperture grid in a high Fresnel number regime, we can measure both intensity and phase front variations with a high sampling density (11 µm) and high sensitivity (the sensitivity of normalized phase gradient measurement is 0.1 mrad under the typical working condition). By using WIS in a standard microscope, we can collect both bright-field (transmitted light intensity) and normalized phase gradient images. Our experiments further demonstrate that the normalized phase gradient images of polystyrene microspheres, unstained and stained starfish embryos, and strongly birefringent potato starch granules are improved versions of their corresponding differential interference contrast (DIC) microscope images in that they are artifact-free and quantitative. Besides phase microscopy, WIS can benefit machine recognition, object ranging, and texture assessment for a variety of applications. PMID:20721059

Cui, Xiquan; Ren, Jian; Tearney, Guillermo J.; Yang, Changhuei

2010-01-01

314

Wavelet compression techniques for hyperspectral data  

NASA Technical Reports Server (NTRS)

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Evans, Bruce; Ringer, Brian; Yeates, Mathew

1994-01-01

315

Interactive visualization of hyperspectral images on a hyperbolic disk  

NASA Astrophysics Data System (ADS)

Visualization of the high-dimensional data set that makes up hyperspectral images necessitates a dimensionality reduction approach to make that data useful to a human analyst. The expression of spectral data as color images, individual pixel spectra plots, principal component images, and 2D/3D scatter plots of a subset of the data are a few examples of common techniques. However, these approaches leave the user with little ability to intuit knowledge of the full N-dimensional spectral data space or to directly or easily interact with that data. In this work, we look at developing an interactive, intuitive visualization and analysis tool based on using a Poincaré disk as a window into that high dimensional space. The Poincaré disk represents an infinite, two-dimensional hyperbolic space such that distances and areas increase exponentially as you move farther from the center of the disk. By projecting N-dimensional data into this space using a non-linear, yet relative distance metric preserving projection (such as the Sammon projection), we can simultaneously view the entire data set while maintaining natural clustering and spacing. The disk also provides a means to interact with the data; the user is presented with a "fish-eye" view of the space which can be navigated and manipulated with a mouse to "zoom" into clusters of data and to select spectral data points. By coupling this interaction with a synchronous view of the data as a spatial RGB image and the ability to examine individual pixel spectra, the user has full control over the data set for classification, analysis, and instructive use.

Goodenough, Adam A.; Schlamm, Ariel; Brown, Scott D.; Messinger, David

2011-06-01

316

Investigation of NIR hyperspectral imaging for discriminating melamine in milk powder  

NASA Astrophysics Data System (ADS)

Melamine (2,4,6-triamino-1,3,5-triazine) contamination of food has become an urgent and broadly recognized issue for which rapid and accurate identification methods are needed by the food industry. In this study, the feasibility and effectiveness of near-infrared (NIR) hyperspectral imaging was investigated for detecting melamine in milk powder. Hyperspectral NIR images (144 bands spanning from 990 to 1700 nm) were acquired for Petri dishes containing samples of milk powder mixed with melamine at various concentrations (0.02% to 1%). Spectral bands that showed the most significant differences between pure milk and pure melamine were selected, and two-band difference analysis was applied to the spectrum of each pixel in the sample images to identify melamine particles in milk powders. The resultant images effectively allowed visualization of melamine particle distributions in the samples. The study demonstrated that NIR hyperspectral imaging techniques can qualitatively and quantitatively identify melamine adulteration in milk powders.

Fu, Xiaping; Kim, Moon S.; Chao, Kuanglin; Qin, Jianwei; Lim, Jongguk; Lee, Hoyoung; Ying, Yibin

2013-05-01

317

New Cloud Detection Algorithm for Multispectral and Hyperspectral Images: Application to  

E-print Network

New Cloud Detection Algorithm for Multispectral and Hyperspectral Images: Application to ENVISAT that faces the problem of accurate identification of location and abundance of clouds in multispectral images inevitable that many of these images present cloud covers. The objective of this work is to develop

Camps-Valls, Gustavo

318

A novel approach to quantitative evaluation of hyperspectral image fusion techniques  

Microsoft Academic Search

In recent years, several image fusion techniques have been proposed to cater to various objectives. An appropriate visualization of the data is one of the key objectives of image fusion, particularly in case of hyperspectral images where the number of bands are far more than those can be displayed on standard tristimulus display. While a few techniques that address the

Ketan Kotwal; Subhasis Chaudhuri

319

Determining the intrinsic dimension of a hyperspectral image using Random Matrix Theory  

E-print Network

-dimensional data cube of size (m Ã? n Ã? p). This is a set of p images of size N = m Ã? n pixels, where all1 Determining the intrinsic dimension of a hyperspectral image using Random Matrix Theory Kerry dimension of a hyper- spectral image is an important step in the spectral unmixing process and under

Damelin, Steven

320

Hyperspectral datacube estimations of binary stars with the computed tomographic imaging spectrometer (CTIS)  

E-print Network

, ) image cube data (see Figure 1) by employing some form of scanning, such as pushbroom scanning (for spectrometer that optimizes and equalizes the dwell time at each (x, y, ) image-cube resolution elementHyperspectral datacube estimations of binary stars with the computed tomographic imaging

Dereniak, Eustace L.

321

Model based compression of the calibration matrix for hyperspectral imaging systems  

E-print Network

collect (x, y, ) image cube data (see Figure 1) by employing some form of scanning, such as pushbroom difference between the two arms of a Michelson interferometer before the image cube can be retrieved fromModel based compression of the calibration matrix for hyperspectral imaging systems James F. Scholl

Dereniak, Eustace L.

322

*kerekes@cis.rit.edu Hyperspectral image quality for unmixing and  

E-print Network

platform. These data are often represented visually in a cube with a natural color image on the face*kerekes@cis.rit.edu Hyperspectral image quality for unmixing and subpixel detection applications John P. Kerekes* and Daniel S. Goldberg Digital Imaging and Remote Sensing Laboratory, Chester F

Kerekes, John

323

Detection of cracks on tomatoes using a hyperspectral near-infrared reflectance imaging system.  

PubMed

The objective of this study was to evaluate the use of hyperspectral near-infrared (NIR) reflectance imaging techniques for detecting cuticle cracks on tomatoes. A hyperspectral NIR reflectance imaging system that analyzed the spectral region of 1000-1700 nm was used to obtain hyperspectral reflectance images of 224 tomatoes: 112 with and 112 without cracks along the stem-scar region. The hyperspectral images were subjected to partial least square discriminant analysis (PLS-DA) to classify and detect cracks on the tomatoes. Two morphological features, roundness (R) and minimum-maximum distance (D), were calculated from the PLS-DA images to quantify the shape of the stem scar. Linear discriminant analysis (LDA) and a support vector machine (SVM) were then used to classify R and D. The results revealed 94.6% and 96.4% accuracy for classifications made using LDA and SVM, respectively, for tomatoes with and without crack defects. These data suggest that the hyperspectral near-infrared reflectance imaging system, in addition to traditional NIR spectroscopy-based methods, could potentially be used to detect crack defects on tomatoes and perform quality assessments. PMID:25310472

Lee, Hoonsoo; Kim, Moon S; Jeong, Danhee; Delwiche, Stephen R; Chao, Kuanglin; Cho, Byoung-Kwan

2014-01-01

324

Detection of Cracks on Tomatoes Using a Hyperspectral Near-Infrared Reflectance Imaging System  

PubMed Central

The objective of this study was to evaluate the use of hyperspectral near-infrared (NIR) reflectance imaging techniques for detecting cuticle cracks on tomatoes. A hyperspectral NIR reflectance imaging system that analyzed the spectral region of 1000–1700 nm was used to obtain hyperspectral reflectance images of 224 tomatoes: 112 with and 112 without cracks along the stem-scar region. The hyperspectral images were subjected to partial least square discriminant analysis (PLS-DA) to classify and detect cracks on the tomatoes. Two morphological features, roundness (R) and minimum-maximum distance (D), were calculated from the PLS-DA images to quantify the shape of the stem scar. Linear discriminant analysis (LDA) and a support vector machine (SVM) were then used to classify R and D. The results revealed 94.6% and 96.4% accuracy for classifications made using LDA and SVM, respectively, for tomatoes with and without crack defects. These data suggest that the hyperspectral near-infrared reflectance imaging system, in addition to traditional NIR spectroscopy-based methods, could potentially be used to detect crack defects on tomatoes and perform quality assessments. PMID:25310472

Lee, Hoonsoo; Kim, Moon S.; Jeong, Danhee; Delwiche, Stephen R.; Chao, Kuanglin; Cho, Byoung-Kwan

2014-01-01

325

Demonstration of the Wide-Field Imaging Interferometer Testbed Using a Calibrated Hyperspectral Image Projector  

NASA Technical Reports Server (NTRS)

The Wide-field Imaging Interferometer testbed (WIIT) at NASA's Goddard Space Flight Center uses a dual-Michelson interferometric technique. The WIIT combines stellar interferometry with Fourier-transform interferometry to produce high-resolution spatial-spectral data over a large field-of-view. This combined technique could be employed on future NASA missions such as the Space Infrared Interferometric Telescope (SPIRIT) and the Sub-millimeter Probe of the Evolution of Cosmic Structure (SPECS). While both SPIRIT and SPECS would operate at far-infrared wavelengths, the WIIT demonstrates the dual-interferometry technique at visible wavelengths. The WIIT will produce hyperspectral image data, so a true hyperspectral object is necessary. A calibrated hyperspectral image projector (CHIP) has been constructed to provide such an object. The CHIP uses Digital Light Processing (DLP) technology to produce customized, spectrally-diverse scenes. CHIP scenes will have approximately 1.6-micron spatial resolution and the capability of . producing arbitrary spectra in the band between 380 nm and 1.6 microns, with approximately 5-nm spectral resolution. Each pixel in the scene can take on a unique spectrum. Spectral calibration is achieved with an onboard fiber-coupled spectrometer. In this paper we describe the operation of the CHIP. Results from the WIIT observations of CHIP scenes will also be presented.

Bolcar, Matthew R.; Leisawitz, David; Maher, Steve; Rinehart, Stephen

2012-01-01

326

Unsupervised constrained linear Fisher's discriminant analysis for hyperspectral image classification  

NASA Astrophysics Data System (ADS)

Fisher's linear discriminant analysis (FLDA) has been widely used in pattern classification due to its criterion, called Fisher's ratio, based on the ratio of between-class variance to within-class variance. Recently, a linear constrained discriminant analysis (LCDA) was developed for huperspectral image classification where Fisher's ratio was replaced with the ratio of inter-distance to intra-distance and the target signatures were constrained to orthogonal directions. This paper directly extends the FLDA to constrained Fisher's linear discriminant analysiss (CFLDA), which uses Fisher's ratio as a classification criterion. Since CFLDA is supervised which requires a set of training samples, this paper further extends the CFLDA to an unsupervised CFLDA (UCFLDA) by including a new unsupervised training sample generation algorithm to automatically produce a sample pool of training data to be used for CFLDA. In order to determine the number of classes, p, to be classified, a newly developed concept, called virtual dimensionality (VD) is used to estimate the p where a Neyman-Pearson-based eigen-analysis approach developed by Harsanyi, Farrand and Chang, called noise-whitened HFC (NWHFC)'s method, is implemented to find the VD. The experimental results have shown that the proposed UCFLDA perform effectively for HYDICE data and provides a promising unsupervised classification technique for hyperspectral imagery.

Ji, Bahong; Chang, Chein-I.; Jensen, Janet L.; Jensen, James O.

2004-10-01

327

Hyperspectral molecular imaging of multiple receptors using immunolabeled plasmonic nanoparticles  

NASA Astrophysics Data System (ADS)

This work presents simultaneous imaging and detection of three types of cell receptors using three types of plasmonic nanoparticles. The size, shape, and composition-dependent scattering profiles of these particles allow for a system of multiple distinct molecular markers using a single optical source. With this goal in mind, a system of tags consisting of anti-EGFR gold nanorods, anti-IGF1R silver nanospheres, and anti-HER-2 gold nanospheres was developed for monitoring the expression of three commonly overexpressed receptors in cancer cells. These labels were chosen because they each scatter strongly in a distinct spectral window. A hyperspectral dark-field microscope was developed to record the scattering spectra of cells labeled with these molecular tags. The ability to monitor multiple tags simultaneously may lead to applications such as profiling the immunophenotype of cell lines and gaining better knowledge of receptor signaling pathways. Single, dual, and triple tag experiments were performed to analyze the specificity of the nanoparticle tags as well as their effect on one another. While distinct resonance peaks in these studies show the ability to characterize cell lines using conjugated nanoparticles, shifts in these peaks also indicate changes in the cellular dielectric environment which may not be distinct from plasmon coupling between nanoparticles bound to proximal receptors.

Crow, Matthew J.; Seekell, Kevin; Marinakos, Stella; Ostrander, Julie; Chilkoti, Ashutosh; Wax, Adam P.

2011-03-01

328

Survey of hyperspectral image denoising methods based on tensor decompositions  

NASA Astrophysics Data System (ADS)

A hyperspectral image (HSI) is always modeled as a three-dimensional tensor, with the first two dimensions indicating the spatial domain and the third dimension indicating the spectral domain. The classical matrix-based denoising methods require to rearrange the tensor into a matrix, then filter noise in the column space, and finally rebuild the tensor. To avoid the rearranging and rebuilding steps, the tensor-based denoising methods can be used to process the HSI directly by employing multilinear algebra. This paper presents a survey on three newly proposed HSI denoising methods and shows their performances in reducing noise. The first method is the Multiway Wiener Filter (MWF), which is an extension of the Wiener filter to data tensors, based on the TUCKER3 decomposition. The second one is the PARAFAC filter, which removes noise by truncating the lower rank K of the PARAFAC decomposition. And the third one is the combination of multidimensional wavelet packet transform (MWPT) and MWF (MWPT-MWF), which models each coefficient set as a tensor and then filters each tensor by applying MWF. MWPT-MWF has been proposed to preserve rare signals in the denoising process, which cannot be preserved well by using the MWF or PARAFAC filters. A real-world HYDICE HSI data is used in the experiments to assess these three tensor-based denoising methods, and the performances of each method are analyzed in two aspects: signal-to-noise ratio and improvement of subsequent target detection results.

Lin, Tao; Bourennane, Salah

2013-12-01

329

Molecular Profiling of Individual Tumor Cells by Hyperspectral Microscopic Imaging  

PubMed Central

We have developed a hyperspectral microscopic imaging (HMI) platform that can precisely identify and quantify 10 molecular markers in individual cancer cells in a single pass. Exploitation of an improved separation of circulating tumor cells and the application of HMI has provided an opportunity to identify molecular changes in these cells, the recognition of co-expression of these markers, and poses an important opportunity for non-invasive diagnosis, and the use of targeted therapy. We have balanced the intensity of 10 fluorochromes bound to 10 different antibodies, each specific to a particular tumor marker, so that the intensity of each fluorochrome can be discerned from overlapping emissions. Using 2 touch preps from each primary breast cancer, the average molecular marker-intensities of 25 tumor cells gave a representative molecular signature for the tumor despite some cellular heterogeneity. The intensities determined by the HMI correlate well with the conventional 0-3+ analysis by experts in cellular pathology. Since additional multiplexes can be developed using the same fluorochromes but different antibodies, this analysis allows quantification of a large number of molecular markers on individual tumor cells. HMI can be completely automated and, eventually, could allow standardization of protein biomarkers and improve reproducibility among clinical pathology laboratories. PMID:22500509

Uhr, Jonathan W.; Huebschman, Michael L.; Frenkel, Eugene P.; Lane, Nancy L.; Ashfaq, Raheela; Liu, HuaYing; Rana, Dipen R.; Cheng, Lawrence; Lin, Alice T.; Hughes, Gareth A.; Zhang, Xiaojing J.; Garner, Harold R.

2012-01-01

330

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging  

NASA Astrophysics Data System (ADS)

As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-03-01

331

Spectral-Spatial Classification Using Tensor Modeling for Cancer Detection with Hyperspectral Imaging  

PubMed Central

As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management. PMID:25328639

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-01-01

332

Estimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean--the Azov Sea case study  

E-print Network

of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager for the Coastal Ocean infrared (NIR) spectral bands of a Hyperspectral Imager for the Coastal Ocean (HICO) in productive turbidEstimation of chlorophyll-a concentration in productive turbid waters using a Hyperspectral Imager

Gitelson, Anatoly

333

Rapid calibrated high-resolution hyperspectral imaging using tunable laser source  

NASA Astrophysics Data System (ADS)

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.

Nguyen, Lam K.; Margalith, Eli

2009-05-01

334

Validation of ocean color sensors using a profiling hyperspectral radiometer  

NASA Astrophysics Data System (ADS)

Validation measurements of satellite ocean color sensors require in situ measurements that are accurate, repeatable and traceable enough to distinguish variability between in situ measurements and variability in the signal being observed on orbit. The utility of using a Satlantic Profiler II equipped with HyperOCR radiometers (Hyperpro) for validating ocean color sensors is tested by assessing the stability of the calibration coefficients and by comparing Hyperpro in situ measurements to other instruments and between different Hyperpros in a variety of water types. Calibration and characterization of the NOAA Satlantic Hyperpro instrument is described and concurrent measurements of water-leaving radiances conducted during cruises are presented between this profiling instrument and other profiling, above-water and moored instruments. The moored optical instruments are the US operated Marine Optical BuoY (MOBY) and the French operated Boussole Buoy. In addition, Satlantic processing versions are described in terms of accuracy and consistency. A new multi-cast approach is compared to the most commonly used single cast method. Analysis comparisons are conducted in turbid and blue water conditions. Examples of validation matchups with VIIRS ocean color data are presented. With careful data collection and analysis, the Satlantic Hyperpro profiling radiometer has proven to be a reliable and consistent tool for satellite ocean color validation.

Ondrusek, M. E.; Stengel, E.; Rella, M. A.; Goode, W.; Ladner, S.; Feinholz, M.

2014-05-01

335

Airborne imaging sensors for environmental monitoring & surveillance in support of oil spills & recovery efforts  

Microsoft Academic Search

Collection of pushbroom sensor imagery from a mobile platform requires corrections using inertial measurement units (IMU's) and DGPS in order to create useable imagery for environmental monitoring and surveillance of shorelines in freshwater systems, coastal littoral zones and harbor areas. This paper describes a suite of imaging systems used during collection of hyperspectral imagery in northern Florida panhandle and Gulf

Charles R. Bostater; James Jones; Heather Frystacky; Gaelle Coppin; Florian Leavaux; Xavier Neyt

2011-01-01

336

Resolution enhancement of Hyperion hyperspectral data using Ikonos multispectral data  

NASA Astrophysics Data System (ADS)

We have developed a new and innovative technique for combining a high-spatial-resolution multispectral image with a lower-spatial-resolution hyperspectral image. The approach, called CRISP, compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of equations to approximately transform the multispectral image into a synthetic hyperspectral image. This synthetic hyperspectral image is then recombined with the original low-spatial-resolution hyperspectral image to produce a sharpened product. The result is a product that has the spectral properties of the hyperspectral image at a spatial resolution approaching that of the multispectral image. To test the accuracy of the CRISP method, we applied the method to synthetic data generated from hyperspectral images acquired with an airborne sensor. These high-spatial-resolution images were used to generate both a lower-spatial-resolution hyperspectral data set and a four-band multispectral data set. With this method, it is possible to compare the output of the CRISP process to the 'truth data' (the original scene). In all of these controlled tests, the CRISP product showed both good spectral and visual fidelity, with an RMS error less than one percent when compared to the 'truth' image. We then applied the method to real world imagery collected by the Hyperion sensor on EO-1 as part of the Hurricane Katrina support effort. In addition to multiple Hyperion data sets, both Ikonos and QuickBird data were also acquired over the New Orleans area. Following registration of the data sets, multiple high-spatial-resolution CRISP-generated hyperspectral data sets were created. In this paper, we present the results of this study that shows the utility of the CRISP-sharpened products to form material classification maps at four-meter resolution from space-based hyperspectral data. These products are compared to the equivalent products generated from the source 30m resolution Hyperion data.

Winter, Edwin M.; Winter, Michael E.; Beaven, Scott G.; Ratkowski, Anthony J.

2007-10-01

337

New technique for hyperspectral image analysis with applications to anomaly detection  

NASA Astrophysics Data System (ADS)

This paper describes a new approach to hyperspectral image analysis using spectral signature mixture models. In this new approach spectral end-member extraction and spectral unmixing are co-dependent objectives. Previous methods tended to serialize these tasks. Our approach shows that superior hyperspectral modeling can be obtained through a parallel objective approach. The new approach also implements natural constraints on the end-members and mixtures. These constraints allow us to adopt a physical interpretation of the hyperspectral image decomposition. This new modeling technique is useful for the detection of known signatures and, more significantly, for the detection of unknown, partially occluded scene anomalies. The anomaly detection algorithm is aided by the newly developed Quad-AR filter which acts as an efficient optimal adaptive clutter rejection filter. Examples are given using a 3-band color image and 210-band HYDICE forest radiance data. The results show these new techniques to be quite effective.

Denney, Bradley S.; de Figueiredo, Rui J. P.

2000-11-01

338

Combined Kernel-Based BDT-SMO Classification of Hyperspectral Fused Images  

PubMed Central

To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1) different radial basis kernel functions (RBFs) are employed for spectral and textural features, and a new combined radial basis kernel function (CRBF) is proposed by combining them in a weighted manner; (2) the binary decision tree-based multiclass SMO (BDT-SMO) is used in the classification of hyperspectral fused images; (3) experiments are carried out, where the single radial basis function- (SRBF-) based BDT-SMO classifier and the CRBF-based BDT-SMO classifier are used, respectively, to classify the land usages of hyperspectral fused images, and genetic algorithms (GA) are used to optimize the kernel parameters of the classifiers. The results show that, compared with SRBF, CRBF-based BDT-SMO classifiers display greater classification accuracy and efficiency.

Huang, Fenghua; Yan, Luming

2014-01-01

339

Different Optimal Band Selection of Hyperspectral Images Using a Continuous Genetic Algorithm  

NASA Astrophysics Data System (ADS)

In the most applications in remote sensing, there is no need to use all of available data, such as using all of bands in hyperspectral images. In this paper, a new band selection method was proposed to deal with the large number of hyperspectral images bands. We proposed a Continuous Genetic Algorithm (CGA) to achieve the best subset of hyperspectral images bands, without decreasing Overall Accuracy (OA) index in classification. In the proposed CGA, a multi-class SVM was used as a classifier. Comparing results achieved by the CGA with those achieved by the Binary GA (BGA) shows better performances in the proposed CGA method. At the end, 56 bands were selected as the best bands for classification with OA of 78.5 %.

Talebi Nahr, S.; Pahlavani, P.; Hasanlou, M.

2014-10-01

340

Spectral-spatial classification for noninvasive cancer detection using hyperspectral imaging.  

PubMed

Early detection of malignant lesions could improve both survival and quality of life of cancer patients. Hyperspectral imaging (HSI) has emerged as a powerful tool for noninvasive cancer detection and diagnosis, with the advantage of avoiding tissue biopsy and providing diagnostic signatures without the need of a contrast agent in real time. We developed a spectral-spatial classification method to distinguish cancer from normal tissue on hyperspectral images. We acquire hyperspectral reflectance images from 450 to 900 nm with a 2-nm increment from tumor-bearing mice. In our animal experiments, the HSI and classification method achieved a sensitivity of 93.7% and a specificity of 91.3%. The preliminary study demonstrated that HSI has the potential to be applied in vivo for noninvasive detection of tumors. PMID:25277147

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Qin, Xulei; Chen, Zhuo Georgia; Fei, Baowei

2014-10-01

341

Assessing band selection and image classification techniques on HYDICE hyperspectral data  

Microsoft Academic Search

Describes some preliminary results concerning the robustness and generalization capabilities of manual (parametric) methods versus machine learning methods in the band selection and subsequent classification of hyperspectral images. We specifically compare a genetic algorithm-based approach to an end-member and spectral unmixing approach in the selection of data used for classification of a HYDICE image. We then discuss and compare the

John A. Marin; John Brockhaus; James Rolf; James Shine; J. Schafer; A. Balthazor

1999-01-01

342

Remote sensing of gases by hyperspectral imaging: results of measurements in the Hamburg port area  

Microsoft Academic Search

Remote sensing by infrared spectroscopy allows detection and identification of hazardous clouds in the atmosphere from long distances. Previous work showed how imaging spectroscopy can be used to assess the location, the dimensions, and the dispersion of a potentially hazardous cloud. In this work an infrared hyperspectral imager based on a Michelson interferometer in combination with a focal plane array

Samer Sabbah; Peter Rusch; Jörn-Hinnrich Gerhard; Christian Stöckling; Jens Eichmann; Roland Harig

2011-01-01

343

Sparse Nonnegative Matrix Underapproximation and its Application to Hyperspectral Image Analysis6  

E-print Network

analysis (PCA) are powerful tools for the analysis of high-dimensional data. In hyperspectral image analysis, nonnegativity of the data can be taken into account, leading to an additive linear model called. This is experimentally demonstrated on the HYDICE images of the San Diego airport and the Urban dataset. AMS

Plemmons, Robert J.

344

Categorization of pork quality using Gabor filter-based hyperspectral imaging technology  

Microsoft Academic Search

Objective assessment of pork quality is important for meat industry application. Previous studies using spectral approaches focused on using color and exudation features for the determination of pork quality levels without considering the image texture feature. In this study, a Gabor filter-based hyperspectral imaging technique was presented to develop an accurate system for pork quality level classification. Texture features were

L. Liu; M. O. Ngadi; S. O. Prasher; C. Gariépy

2010-01-01

345

3D optical sectioning with a new hyperspectral confocal fluorescence imaging system.  

SciTech Connect

A novel hyperspectral fluorescence microscope for high-resolution 3D optical sectioning of cells and other structures has been designed, constructed, and used to investigate a number of different problems. We have significantly extended new multivariate curve resolution (MCR) data analysis methods to deconvolve the hyperspectral image data and to rapidly extract quantitative 3D concentration distribution maps of all emitting species. The imaging system has many advantages over current confocal imaging systems including simultaneous monitoring of numerous highly overlapped fluorophores, immunity to autofluorescence or impurity fluorescence, enhanced sensitivity, and dramatically improved accuracy, reliability, and dynamic range. Efficient data compression in the spectral dimension has allowed personal computers to perform quantitative analysis of hyperspectral images of large size without loss of image quality. We have also developed and tested software to perform analysis of time resolved hyperspectral images using trilinear multivariate analysis methods. The new imaging system is an enabling technology for numerous applications including (1) 3D composition mapping analysis of multicomponent processes occurring during host-pathogen interactions, (2) monitoring microfluidic processes, (3) imaging of molecular motors and (4) understanding photosynthetic processes in wild type and mutant Synechocystis cyanobacteria.

Nieman, Linda T.; Sinclair, Michael B.; Davidson, George S.; Van Benthem, Mark Hilary; Haaland, David Michael; Timlin, Jerilyn Ann; Sasaki, Darryl Yoshio; Bachand, George David; Jones, Howland D. T.

2007-02-01

346

Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system  

Microsoft Academic Search

The development of an integrated MultiSpectral Imaging (MSI) system yielding hyperspectral cubes by means of artificial neural networks is described. The MSI system is based on a CCD camera, a rotating wheel bearing a set of seven interference filters, a light source and a computer. The resulting device has been elaborated for in vivo imaging of skin lesions. It provides

Romuald Jolivot; Pierre Vabres; Franck Marzani

2011-01-01

347

Biomedical Applications of the Information-efficient Spectral Imaging Sensor (ISIS)  

SciTech Connect

The Information-efficient Spectral Imaging Sensor (ISIS) approach to spectral imaging seeks to bridge the gap between tuned multispectral and fixed hyperspectral imaging sensors. By allowing the definition of completely general spectral filter functions, truly optimal measurements can be made for a given task. These optimal measurements significantly improve signal-to-noise ratio (SNR) and speed, minimize data volume and data rate, while preserving classification accuracy. The following paper investigates the application of the ISIS sensing approach in two sample biomedical applications: prostate and colon cancer screening. It is shown that in these applications, two to three optimal measurements are sufficient to capture the majority of classification information for critical sample constituents. In the prostate cancer example, the optimal measurements allow 8% relative improvement in classification accuracy of critical cell constituents over a red, green, blue (RGB) sensor. In the colon cancer example, use of optimal measurements boost the classification accuracy of critical cell constituents by 28% relative to the RGB sensor. In both cases, optimal measurements match the performance achieved by the entire hyperspectral data set. The paper concludes that an ISIS style spectral imager can acquire these optimal spectral images directly, allowing improved classification accuracy over an RGB sensor. Compared to a hyperspectral sensor, the ISIS approach can achieve similar classification accuracy using a significantly lower number of spectral samples, thus minimizing overall sample classification time and cost.

Gentry, S.M.; Levenson, R.

1999-01-21

348

[Visualization of the chilling storage time for turbot flesh based on hyperspectral imaging technique].  

PubMed

This study proposed a new method using visible and near infrared (Vis/NIR) hyperspectral imaging for the detection and visualization of the chilling storage time for turbot flesh rapid and nondestructively. A total of 160 fish samples with 8 different storage days were collected for hyperspectral image scanning, and mean spectra were extracted from the region of interest (ROD inside each image. Partial least squares regression (PLSR) was applied as calibration method to correlate the spectral data and storage time for the 120 samples in calibration set. Then the PLSR model was used to predict the storage time for the 40 prediction samples, which achieved accurate results with determination coefficient (R2) of 0.966 2 and root mean square error of prediction (RMSEP) of 0.679 9 d. Finally, the storage time of each pixel in the hyperspectral images for all prediction samples was predicted and displayed in different colors for visualization based on pseudo-color images with the aid of an IDL program. The results indicated that hyperspectral imaging technique combined with chemometrics and image processing allows the determination and visualization of the chilling storage time for fish, displaying fish freshness status and distribution vividly and laying a foundation for the automatic processing of aquatic products. PMID:25269312

Zhu, Feng-Le; Zhang, Hai-Liang; Shao, Yong-Ni; He, Yong

2014-07-01

349

Minimum distance constrained non-negative matrix factorization for the endmember extraction of hyperspectral images  

NASA Astrophysics Data System (ADS)

Endmember extraction and spectral unmixing is a very challenging task in multispectral/hyperspectral image processing due to the incompleteness of information. In this paper, a new method for endmember extraction and spectral unmixing of hyperspectral images is proposed, which is called as minimum distance constrained nonnegative matrix factorization (MDC-NMF). After being compared with a newly developed method named MVC-NMF, MDC-NMF not only has been demonstrated more reasonable in theory but also shows promising results in the experiments.

Yu, Yue; Guo, Shan; Sun, Weidong

2007-11-01

350

Sunglint effects on the characterization of optically active substances in high spatial resolution airborne hyperspectral images  

NASA Astrophysics Data System (ADS)

Sunglint, also known as the specular reflection of light from water surfaces, is a component of sensor-received radiance that represents a confounding factor on the characterization of water bodies by remote sensing. In airborne remote sensing images, the effect of sunglint can be minimized by optimizing the flight paths, directing the sensor towards or away from the Sun, and by keeping solar zenith angles between 30° and 60°. However, these guidelines cannot always be applied, often due to the irregular spatial pattern of lakes, estuaries and coastlines. The present study assessed the impact of sunglint on the relationship between the optically active substances (OAS) concentration, in optically complex waters, and the spectral information provided by an airborne high spatial resolution hyperspectral sensor (SpecTIR). The Ibitinga reservoir, located in southeastern Brazil (state of São Paulo), was selected as the study area because of its meandering shape. As a result, there is demanding constant changes in data acquisition geometry to achieve complete coverage, therefore not allowing sunglint conditions to be minimized during image acquisition. Field data collection was carried out on October 23 and 24, 2011. During these two days, 15 water stations along the reservoir were sampled, concurrently with the SpecTIR image acquisition in 357 bands (398-2455 nm) and at 3 m spatial resolution. Chlorophyll, pheophytin, total suspended solids, organic and inorganic suspended solids and colored dissolved matter were determined in laboratory. The images were corrected for the atmospheric effects using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm and then geometrically corrected. In order to evaluate the sunglint effects on the OAS characterization, the images were corrected for such effects using the deglint algorithm from Goodman et al. (2008). The SpecTIR 662-nm band reflectance was selected to be correlated to the OAS due to its sensibility to the absorption and scattering by the water constituents. One of the sunglint effects was to increase the reflectance values of the images by a factor of ~3, masking the correlations between the OAS and the spectral reflectance. After using the deglint algorithm, the relationships were improved. The correlations coefficients (r) between the reflectance at 662 nm and the OAS improved from -0.16 to -0.38 for pheophytin; -0.12 to -0.38 for chlorophyll; and from +0.52 to +0.66 for inorganic suspended solids. Despite the low correlation coefficients, results suggested that sunglint effects were capable of affecting the relationships between the spectral reflectance and the water concentration of OAS. They emphasize the importance of removing such effects on high spatial resolution hyperspectral data collected by airborne sensors at several flight lines over meandering water bodies where variations in Sun-viewing geometry are generally observed.

Streher, A. S.; Faria Barbosa, C. Clemente; Soares Galvão, L.; Goodman, J. A.; Silva, T. S.

2013-05-01

351

Image Sensors Enhance Camera Technologies  

NASA Technical Reports Server (NTRS)

In the 1990s, a Jet Propulsion Laboratory team led by Eric Fossum researched ways of improving complementary metal-oxide semiconductor (CMOS) image sensors in order to miniaturize cameras on spacecraft while maintaining scientific image quality. Fossum s team founded a company to commercialize the resulting CMOS active pixel sensor. Now called the Aptina Imaging Corporation, based in San Jose, California, the company has shipped over 1 billion sensors for use in applications such as digital cameras, camera phones, Web cameras, and automotive cameras. Today, one of every three cell phone cameras on the planet feature Aptina s sensor technology.

2010-01-01

352

Modeling and compensating non-uniformity in push-broom NIR hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

In this paper, a novel pixel-based model for the response of push-broom near infrared (NIR) hyperspectral cameras based on focal-plane array (FPA) photo-detectors is proposed. The model focuses on practical issues affecting the system response, such as the spatial and spectral non-uniformity (NU) observed in NIR hyperspectral imaging systems, and its novelty relies on considering the operating temperature of the FPA as a signal perturbing the response of the entire system. These effects have been estimated by experimental procedures. The applicability and accuracy of the proposed model has been assessed by mitigating for the spatial and spectral non-uniform responses of a real NIR hyperspectral imaging sequence.

Parra, Francisca; Meza, Pablo; Torres, Sergio N.; Pezoa, Jorge E.; Mella, Héctor

2014-03-01

353

Investigating oyster shell thickness and strength using three imaging modalities: hyperspectral imaging, thermal imaging and digital photography  

NASA Astrophysics Data System (ADS)

A comparative study of three imaging technologies has been conducted to nondestructively assess the thickness and strength of oyster shells grown in various environmental conditions. Oyster shell thickness and strength are expected to be dependent on the harshness of the oyster's environment as well as other factors. Oysters have been grown in environments with and without predators, and within and out of tidal zones. Hyperspectral imaging has been used to detect possible differences in hyperspectral properties among oyster shells from each of the four environments. Thermal Imaging has been utilized to identify hot spots in the shells based on the principles of heat capacitance, indicating density or thickness of the shells. Finally, a visible-range digital photographic camera has been used to obtain digital images. The three technologies are compared to evaluate the effectiveness of each technology in identifying oyster shell thickness and strength. Although oyster shell thickness and strength are related, they may not be exactly correlated. The local thickness of the oyster shells have been measured with a micro caliper, and shells broken with a crush tester to establish a baseline and ground truth for average shell thickness and shell strength, respectively. The preliminary results from the three methods demonstrate that thermal imaging correlates the best with the invasive strength test results and weight measurements. Using hyperspectral data and principal component analysis, classification of the four oyster shell groups were achieved. Visible-range images mainly provided size, shape, color and texture information.

Mehrübeoglu, Mehrube; Smith, Dustin K.; Smith, Shane W.; Smee, Delbert L.; Simionescu, Petru-Aurelian

2013-09-01

354

The Narrow Band AOTF Based Hyperspectral Microscopic Imaging on the Rat Skin Stratum Configuration  

NASA Astrophysics Data System (ADS)

A noncollinear acousto-optic tunable filter (AOTF) was designed with a comprehensive treatment of the properties of TeO2 as an acoustooptic (A-O) material. The results of optical testing validated that it predicted the performance of the designed AOTF. The bandwidth of the AOTF was very narrow in the visible light range. The high spectral resolution of AOTF was useful in practical applications to the hyperspectral imaging. The experimentally observed spectral pattern of the diffracted light was nearly the same as the theoretical result. The measured tuning relationship between the diffracted central optical wavelength and acoustic frequency was in accordance with the theoretical prediction. It demonstrates the accuracy of our design theory. Furthermore, by selecting the AOTF as the spectroscopic element, a hyperspectral microscopic imaging system was designed. The hyperspectral microscopic images of the rat skin tissue under the different optical center wavelength were acquired. The experimental results indicated that the imaging performance was satisfactory. The stratums of the rat skin can be clearly distinguished. The inner details of the epidermis and the corium can be shown on the hyperspectral microscopic images. Some differences also can be found by the comparison of the hyperspectal images under the different optical wavelengths. The study indicated the applicability and the advantage of our system on biomedicine area.

Zhang, C.; Wang, H.; Huang, J.; Gao, Q.

2014-08-01

355

Estimation of skin optical parameters for real-time hyperspectral imaging applications  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging combines high spectral and spatial resolution in one modality. This imaging technique is a promising tool for objective medical diagnostics. However, to be attractive in a clinical setting, the technique needs to be fast and accurate. Hyperspectral imaging can be used to analyze tissue properties using spectroscopic methods, and is thus useful as a general purpose diagnostic tool. We combine an analytic diffusion model for photon transport with real-time analysis of the hyperspectral images. This is achieved by parallelizing the inverse photon transport model on a graphics processing unit to yield optical parameters from diffuse reflectance spectra. The validity of this approach was verified by Monte Carlo simulations. Hyperspectral images of human skin in the wavelength range 400-1000 nm, with a spectral resolution of 3.6 nm and 1600 pixels across the field of view (Hyspex VNIR-1600), were used to develop the presented approach. The implemented algorithm was found to output optical properties at a speed of 3.5 ms per line of image data. The presented method is thus capable of meeting the defined real-time requirement, which was 30 ms per line of data.The algorithm is a proof of principle, which will be further developed.

Bjorgan, Asgeir; Milanic, Matija; Randeberg, Lise Lyngsnes

2014-06-01

356

Application of hyperspectral imaging and chemometric calibrations for variety discrimination of maize seeds.  

PubMed

Hyperspectral imaging in the visible and near infrared (VIS-NIR) region was used to develop a novel method for discriminating different varieties of commodity maize seeds. Firstly, hyperspectral images of 330 samples of six varieties of maize seeds were acquired using a hyperspectral imaging system in the 380-1,030 nm wavelength range. Secondly, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of the spectral data. Thirdly, three optimal wavelengths (523, 579 and 863 nm) were selected by implementing PCA directly on each image. Then four textural variables including contrast, homogeneity, energy and correlation were extracted from gray level co-occurrence matrix (GLCM) of each monochromatic image based on the optimal wavelengths. Finally, several models for maize seeds identification were established by least squares-support vector machine (LS-SVM) and back propagation neural network (BPNN) using four different combinations of principal components (PCs), kernel principal components (KPCs) and textural features as input variables, respectively. The recognition accuracy achieved in the PCA-GLCM-LS-SVM model (98.89%) was the most satisfactory one. We conclude that hyperspectral imaging combined with texture analysis can be implemented for fast classification of different varieties of maize seeds. PMID:23235456

Zhang, Xiaolei; Liu, Fei; He, Yong; Li, Xiaoli

2012-01-01

357

Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds  

PubMed Central

Hyperspectral imaging in the visible and near infrared (VIS-NIR) region was used to develop a novel method for discriminating different varieties of commodity maize seeds. Firstly, hyperspectral images of 330 samples of six varieties of maize seeds were acquired using a hyperspectral imaging system in the 380–1,030 nm wavelength range. Secondly, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of the spectral data. Thirdly, three optimal wavelengths (523, 579 and 863 nm) were selected by implementing PCA directly on each image. Then four textural variables including contrast, homogeneity, energy and correlation were extracted from gray level co-occurrence matrix (GLCM) of each monochromatic image based on the optimal wavelengths. Finally, several models for maize seeds identification were established by least squares-support vector machine (LS-SVM) and back propagation neural network (BPNN) using four different combinations of principal components (PCs), kernel principal components (KPCs) and textural features as input variables, respectively. The recognition accuracy achieved in the PCA-GLCM-LS-SVM model (98.89%) was the most satisfactory one. We conclude that hyperspectral imaging combined with texture analysis can be implemented for fast classification of different varieties of maize seeds. PMID:23235456

Zhang, Xiaolei; Liu, Fei; He, Yong; Li, Xiaoli

2012-01-01

358

Development of an Integrated Hyperspectral Imager and 3D-Flash LADAR for Terrestrial Characterization  

Microsoft Academic Search

The characterization of terrestrial ecosystems using remote sensing technology has a long history with using multi-spectral imagers for vegetation classification indices, ecosystem health, and change detection. Traditional multi-band imagers are now being replaced with more advanced hyperspectral imagers, which offer finer spectral resolution and more specific characterization of terrestrial reflectances. Recently, 3- dimensional (3D) imaging technologies, such as radar interferometry

A. L. Swanson; S. Sandor-Leahy; J. Shepanski; C. Wong; C. Bracikowski; L. Abelson; M. Helmlinger; D. Bauer; M. Folkman

2009-01-01

359

Development of an Integrated Hyperspectral Imager and 3D-Flash Lidar for Terrestrial Characterization  

Microsoft Academic Search

The characterization of terrestrial ecosystems using remote sensing technology has a long history with using multi-spectral imagers for vegetation classification indices, ecosystem health, and change detection. Traditional multi-band imagers are now being replaced with more advanced hyperspectral imagers, which offer finer spectral resolution and more specific characterization of terrestrial reflectances. Recently, 3-dimensional (3D) imaging technologies, such as radar interferometry and

L. Abelson; A. L. Swanson; S. Sandor-Leahy; J. Shepanski; C. Wong; M. Helmlinger; M. Folkman

2009-01-01

360

Design of a concise Féry-prism hyperspectral imaging system based on multi-configuration  

NASA Astrophysics Data System (ADS)

In order to meet the needs of space borne and airborne hyperspectral imaging system for light weight, simplification and high spatial resolution, a novel design of Féry-prism hyperspectral imaging system based on Zemax multi-configuration method is presented. The novel structure is well arranged by analyzing optical monochromatic aberrations theoretically, and the optical structure of this design is concise. The fundamental of this design is Offner relay configuration, whereas the secondary mirror is replaced by Féry-prism with curved surfaces and a reflective front face. By reflection, the light beam passes through the Féry-prism twice, which promotes spectral resolution and enhances image quality at the same time. The result shows that the system can achieve light weight and simplification, compared to other hyperspectral imaging systems. Composed of merely two spherical mirrors and one achromatized Féry-prism to perform both dispersion and imaging functions, this structure is concise and compact. The average spectral resolution is 6.2nm; The MTFs for 0.45~1.00um spectral range are greater than 0.75, RMSs are less than 2.4um; The maximal smile is less than 10% pixel, while the keystones is less than 2.8% pixel; image quality approximates the diffraction limit. The design result shows that hyperspectral imaging system with one modified Féry-prism substituting the secondary mirror of Offner relay configuration is feasible from the perspective of both theory and practice, and possesses the merits of simple structure, convenient optical alignment, and good image quality, high resolution in space and spectra, adjustable dispersive nonlinearity. The system satisfies the requirements of airborne or space borne hyperspectral imaging system.

Dong, Wei; Nie, Yun-feng; Zhou, Jin-song

2013-08-01

361

Temporal analysis of emissivity values in urban areas from airborne hyperspectral thermal sensors  

NASA Astrophysics Data System (ADS)

Land Surface Temperature (LST) is one of the key parameters in the physics of land surface processes on regional and global scales, combining the results of surface - atmosphere interactions related to energy fluxes such as sensible and latent heat, and also of hydrological cycle. Accurate LST mapping has the potential to support applications in various areas and especially when referring to the urban environment, as for example the urban heat island monitoring. Spatiotemporal distributions of LST are estimated with the use of satellite remote sensing sensors. To accurately estimate LST, measured radiance should be corrected for spectral emissivity. Emissivity provides a measure of the inherent efficiency of the surface to convert heat energy into radiant energy. Surface emissivity varies largely in space and time due to the strong heterogeneity of land surface characteristics, such as the topography, the vegetation cover and the soil and its physical properties. The emissivity dependence on the surface physical condition emerges the study of temporal effects on emissivity. It is important to quantify the temporal variations of emissivity and their extend and the effect on the estimation of LST. The present work aims at contributing to a better understanding of the temporal variation of emissivity in urban environments. Thermal data acquired with the Airborne Hyperspectral Scanner (AHS) over Madrid, Spain and Athens, Greece during two ESA Campaigns (namely Desirex and Thermopolis) was used. A total of 30 and 28 images were acquired respectively for each city, covering a time period of six summer days, both day and night. Emissivity and LST were also estimated in the framework of the campaigns for seven spectral AHS bands between 7.5 - 12.0 ?m using the Temperature Emissivity Separation Algorithm. Field emissivity and LST measurements are also available from the campaign. A statistical analysis was performed to assess the variations of emissivity in time, to identify the behavior of the different surface types found in urban environments and to quantify the differences arising between day and night. Representative areas corresponding to different surface types were selected for the analysis by considering homogenous areas to avoid mixed pixels. Some temporal variations of emissivity values were observed in all cases and they were also depending on the surface type and the specific thermal bands.

Lazzarini, Michele; Mitraka, Zina; Berger, Michael; Ghedira, Hosni

2013-04-01

362

Material Classification for 3D Objects in Aerial Hyperspectral Images  

Microsoft Academic Search

Automated material classification from airborne imagery is an important capability for many applications including target recognition and geospatial database construction. Hyperspectral imagery provides a rich source of information for this purpose but utilization is complicated by the variability in a material's observed spectral signature due to the ambient conditions and the scene geometry. In this paper, we present a method

David Slater; Glenn Healey

1999-01-01

363

Thermal infrared hyperspectral imaging from vehicle-carried instrumentation  

Microsoft Academic Search

Stand-off identification in the field using thermal infrared spectrometers (hyperspectral) is a maturing technique for gases and aerosols. However, capabilities to identify solid-phase materials on the surface lag substantially, particularly for identification in the field without benefit of ground truth (e.g. for \\

Laurel E. Kirkland; Kenneth C. Herr; Paul M. Adams; John McAfee; John Salisbury

2002-01-01

364

A geosynchronous imaging Fourier transform spectrometer (GIFTS) for hyperspectral atmospheric remote sensing: instrument overview & preliminary performance results  

NASA Astrophysics Data System (ADS)

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) was developed for the NASA New Millennium Program (NMP) Earth Observing-3 (EO-3) mission. This paper discusses the GIFTS measurement requirements and the technology utilized by the GIFTS sensor to provide the required system performance. Also presented are preliminary results from the recently completed calibration of the instrument. The GIFTS NMP mission challenge was to demonstrate new and emerging sensor and data processing technologies to make revolutionary improvements in meteorological observational capability and forecasting accuracy using atmospheric imaging and hyperspectral sounding methods. The GIFTS sensor is an imaging FTS with programmable spectral resolution and spatial scene selection, allowing radiometric accuracy and atmospheric sounding precision to be traded in near-real time for area coverage. System sensitivity is achieved through the use of a cryogenic Michelson interferometer and two large-area, IR focal plane detector arrays. Due to funding limitations, the GIFTS sensor module was completed as an engineering demonstration unit, which can be upgraded for flight qualification. Capability to meet the next generation geosynchronous sounding requirements has been successfully demonstrated through thermal vacuum testing and rigorous IR calibration activities.

Elwell, J. D.; Cantwell, G. W.; Scott, D. K.; Esplin, R. W.; Hansen, G. B.; Jensen, S. M.; Jensen, M. D.; Brown, S. B.; Zollinger, L. J.; Thurgood, V. A.; Esplin, M. P.; Huppi, R. J.; Bingham, G. E.; Revercomb, H. E.; Best, F. A.; Tobin, D. C.; Taylor, J. K.; Knuteson, R. O.; Smith, W. L.; Reisse, R. A.; Hooker, R.

2006-08-01

365

Lossless compression of hyperspectral images using C-DPCM-APL with reference bands selection  

NASA Astrophysics Data System (ADS)

The availability of hyperspectral images has increased in recent years, which is used in military and civilian applications, such as target recognition, surveillance, geological mapping and environmental monitoring. Because of its abundant data quantity and special importance, now it exists lossless compression methods of hyperspectral images mainly exploiting the strong spatial or spectral correlation. C-DPCM-APL is a method that achieves highest lossless compression ratio on the CCSDS hyperspectral images acquired in 2006 but consuming longest processing time among existing lossless compression methods to determine the optimal prediction length for each band. C-DPCM-APL gets best compression performance mainly via using optimal prediction length but ignoring the correlationship between reference bands and the current band which is a crucial factor that influences the precision of prediction. Considering this, we propose a method that selects reference bands according to the atmospheric absorption characteristic of hyperspectral images. Experiments on CCSDS 2006 images data set show that the proposed reduces the computation complexity heavily without decaying its lossless compression performance when compared to C-DPCM-APL.

Wang, Keyan; Liao, Huilin; Li, Yunsong; Zhang, Shanshan; Wu, Xianyun

2014-05-01

366

Programmable matched filter and Hadamard transform hyperspectral imagers based on micro-mirror arrays  

SciTech Connect

Hyperspectral imaging (HSI), in which each pixel contains a high-resolution spectrum, is a powerful technique that can remotely detect, identify, and quantify a multitude of materials and chemicals. The advent of addressable micro-mirror arrays (MMAs) makes possible a new class of programmable hyperspectral imagers that can perform key spectral processing functions directly in the optical hardware, thus alleviating some of HSI's high computational overhead, as well as offering improved signal-to-noise in certain important regimes (e.g. when using uncooled infrared detectors). We have built and demonstrated a prototype UV-Visible micro-mirror hyperspectral imager that is capable not only of matched-filter imaging, but also of full hyperspectral imagery via the Hadamard transform technique. With this instrument, one can upload a chemical-specific spectral matched filter directly to the MMA, producing an image showing the location of that chemical without further processing. Target chemicals are changeable nearly instantaneously simply by uploading new matched-filter patterns to the MMA. Alternatively, the MMA can implement Hadamard mask functions, yielding a full-spectrum hyperspectral image upon inverting the transform. In either case, the instrument can produce the 2D spatial image either by an internal scan, using the MMA itself, or with a traditional external push-broom scan. The various modes of operation are selectable simply by varying the software driving the MMA. Here the design and performance of the prototype is discussed, along with experimental results confirming the signal-to-noise improvement produced by the Hadamard technique in the noisy-detector regime.

Love, Steven P [Los Alamos National Laboratory

2008-01-01

367

GPU implementation of target and anomaly detection algorithms for remotely sensed hyperspectral image analysis  

NASA Astrophysics Data System (ADS)

Automatic target and anomaly detection are considered very important tasks for hyperspectral data exploitation. These techniques are now routinely applied in many application domains, including defence and intelligence, public safety, precision agriculture, geology, or forestry. Many of these applications require timely responses for swift decisions which depend upon high computing performance of algorithm analysis. However, with the recent explosion in the amount and dimensionality of hyperspectral imagery, this problem calls for the incorporation of parallel computing techniques. In the past, clusters of computers have offered an attractive solution for fast anomaly and target detection in hyperspectral data sets already transmitted to Earth. However, these systems are expensive and difficult to adapt to on-board data processing scenarios, in which low-weight and low-power integrated components are essential to reduce mission payload and obtain analysis results in (near) real-time, i.e., at the same time as the data is collected by the sensor. An exciting new development in the field of commodity computing is the emergence of commodity graphics processing units (GPUs), which can now bridge the gap towards on-board processing of remotely sensed hyperspectral data. In this paper, we describe several new GPU-based implementations of target and anomaly detection algorithms for hyperspectral data exploitation. The parallel algorithms are implemented on latest-generation Tesla C1060 GPU architectures, and quantitatively evaluated using hyperspectral data collected by NASA's AVIRIS system over the World Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in the WTC complex.

Paz, Abel; Plaza, Antonio

2010-08-01

368

Remote Sensing of Vegetation Senescence and Stress using Derivative Spectroscopy Applied to Hyperspectral Images  

NASA Astrophysics Data System (ADS)

It is well established that senescence and stress affect the shape of the optical reflectance spectrum of vegetation. A prime example is the shift of the red edge inflection point (REIP) to lower wavelength as senescence or stress increases. The red edge refers to the sharp rise in vegetation reflectance between the chlorophyll well in the red (670-680 nm) and the near infrared plateau (~790-1350 nm). The REIP wavelength shift, however, can be subtle and not easily detected with hyperspectral imagers. I explore the use of derivative spectroscopy to enhance the features in the reflectance spectrum. Conventional analysis focuses on the wavelength position of the REIP as a measure of stress. In this paper, I examine the shape of the entire derivative spectrum to characterize the transition from healthy to senescent deciduous vegetation over the summer to autumn transition. While this transition occurs naturally, it causes changes in the reflectance spectrum similar to those changes due to stress such as drought or soil contamination. The experiment (carried out in southern New England) consisted of clipping leaves from maple and oak trees every two to three days from early September through late November and measuring the optical reflectance in the laboratory using an Analytical Spectral Devices (ASD) Field Spectrometer. Reflectance spectra were measured for stacks of leaves using different numbers of leaves in the stack and different backgrounds. The primary data set was measured using four-leaf stacks on a flat black background. The time series of derivative spectra clearly show the shift in the red edge inflection point as a function of date, as expected. In addition, the overall shape of the derivative spectra changes significantly as leaf senescence proceeds. The utility of derivative spectroscopy lay in whether it can be used with remote sensing data recorded by hyperspectral sensors such the NASA-JPL AVIRIS instrument. The lower spectral sampling of current remote sensing instruments (typically 10 nm) degrades the derivative spectrum compared to the 1-nm sampling of the laboratory measurements. Deployment of a new class of HSI instruments, such as NEON's airborne sensor, will go a long way to alleviating this problem. Different sampling rates were tested by resampling the derivative spectra time series. In general, current instruments with 10-nm sampling are barely adequate for this kind of analysis, with 5-nm sampling providing a significant improvement.

Cipar, J. J.

2012-12-01

369

Mapping oil spills on sea water using spectral mixture analysis of hyperspectral image data  

E-print Network

Mapping oil spills on sea water using spectral mixture analysis of hyperspectral image data Javier large spill oil events threatening coastal habitats and species. Some recent examples include the 2002 Prestige tanker oil spill in Galicia, Northern Spain, as well as repeated oil spill leaks evidenced

Plaza, Antonio J.

370

Calibration and test of a hyperspectral imaging prototype for intra-operative surgical assistance  

E-print Network

and result display on RGB screens, to assist the surgeon with tissue detection and diagnostic capabilities. This promises a great capability of hyperspectral imaging to bring efficient assistance for surgeons. Keywords of surgery1, 17, 20 . HSI and MSI systems both have undergone tremendous conception evolutions in recent

Boyer, Edmond

371

Hyperspectral imaging of cuttlefish camouflage indicates good color match in the eyes  

E-print Network

Hyperspectral imaging of cuttlefish camouflage indicates good color match in the eyes of fish, and texture. Objective assessment of color signals in the eyes of the receivers (using point source visual predators have keen color perception, and thus camouflage patterns should provide some degree

Hanlon, Roger T.

372

A 3DIMENSIONAL RADIATIVE-TRANSFER HYPERSPECTRAL IMAGE SIMULATOR FOR ALGORITHM VALIDATION  

Microsoft Academic Search

We are currently developing a high model fidelity HyperSpectral Image simulation software package. It is based on a Direct Simulation Monte Carlo approach for modeling 3D atmospheric radiative transport, as well as spatially inhomogeneous surfaces including surface BRDF effects. \\

S. C. Richtsmeier; A. Berk; L. S. Bernstein; S. M. Adler-Golden

2001-01-01

373

A compact, active hyperspectral imaging system for the detection of concealed targets  

E-print Network

conducted a series of laboratory and field tests to demonstrate the utility of combining active illumination different elements of a scene that normally, in standard three-color imagery, appear indistinguishable conditions. By collocating that source with the hyperspectral imager, we can eliminate the reflected

Kerekes, John

374

Automation of waste recycling using hyperspectral image analysis Artzai Picon1  

E-print Network

Automation of waste recycling using hyperspectral image analysis Artzai Picon1 Ovidiu Ghita2 Pedro. In this paper we present a novel methodology to automate the recycling process of non-ferrous metal Waste from process not only time consuming but also very expensive. In the standard recycling process only

Whelan, Paul F.

375

Time-lens Based Hyperspectral Stimulated Raman Scattering Imaging and Quantitative Spectral Analysis  

PubMed Central

We demonstrate a hyperspectral stimulated Raman scattering (SRS) microscope through spectral-transformed excitation. The 1064-nm Stokes pulse was from a synchronized time-lens source, generated through time-domain phase modulation of a continuous wave (CW) laser. The tunable pump pulse was from linear spectral filtering of a femtosecond laser output with an intra-pulse spectral scanning pulse shaper. By electronically modulating the time-lens source at 2.29 MHz, hyperspectral stimulated Raman loss (SRL) images were obtained on a laser-scanning microscope. Using this microscope, DMSO in aqueous solution with a concentration down to 28 mM could be detected at 2 ?s time constant. Hyper-spectral SRL images of prostate cancer cells were obtained. Multivariate curve resolution analysis was further applied to decompose the SRL images into concentration maps of CH2 and CH3 bonds. This method offers exciting potential in label-free imaging of live cells using fingerprint Raman bands. Hyperspectral SRS microscopy using a synchronized time-lens source allows mapping of different cellular contents. PMID:23840041

Wang, Ke; Zhang, Delong; Charan, Kriti; Slipchenko, Mikhail N.; Wang, Ping; Xu, Chris; Cheng, Ji-Xin

2014-01-01

376

HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE IMAGING SYSTEM FOR FOOD QUALITY AND SAFETY  

Microsoft Academic Search

This article presents a laboratory-based hyperspectral imaging system designed and developed by the Instrumentation and Sensing Laboratory, U.S. Department of Agriculture, Beltsville, Maryland. The spectral range is from 430 to 930 nm with spectral resolution of approximately 10 nm (full width at half maximum) and spatial resolution better than 1 mm. Our system is capable of reflectance and fluorescence measurements

M. S. Kim; Y. R. Chen; P. M. Mehl

377

Using elliptically contoured distributions to model hyperspectral imaging data and generate statistically similar synthetic data  

Microsoft Academic Search

Developing proper models for Hyperspectral imaging (HSI) data allows for useful and reliable algorithms for data exploitation. These models provide the foundation for development and evaluation of detection, classification, clustering, and estimation algorithms. To date, most algorithms have modeled real data as multivariate normal, however it is well known that real data often exhibits non-normal behavior. In this paper, Elliptically

David B. Marden; Dimitris G. Manolakis

2004-01-01

378

APPLICATION OF AIRBORNE HYPERSPECTRAL AND THERMAL IMAGES TO ANALYSE URBAN MICROCLIMATE  

Microsoft Academic Search

Urbanisation is a long standing problem and phenomenon all around the world. It means more and more challenges for scientists. Remote sensing techniques with high spectral and spatial resolution open novel approaches which enable the analysis of vegetated and non-vegetated urban surfaces with high heterogeneity. In this paper it is demonstrated how hyperspectral images and thermal maps can be used

ANDRÁS JUNG

379

Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis  

E-print Network

Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image. The method was tested for drought stress, applied to potted barley plants in a controlled rain-out shelter research in the understanding of plant adaptation under drought to improve management practices

Kersting, Kristian

380

Detection of microbial biofilms on food processing surfaces: hyperspectral fluorescence imaging study  

Microsoft Academic Search

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 investigation was to determine a minimal number of spectral bands suitable to differentiate microbial biofilm formation from the

Won Jun; Moon S. Kim; Kaunglin Chao; Alan M. Lefcourt; Michael S. Roberts; James L. McNaughton

2009-01-01

381

Band selection for hyperspectral remote sensing data through correlation matrix to improve image clustering  

NASA Astrophysics Data System (ADS)

Hyperspectral remote sensing is capable of providing large numbers of spectral bands. The vast amount of data volume presents challenging problems for information processing, such as heavy computational burden. In this paper, the impact of dimension reduction on hyperspectral data clustering is investigated from two viewpoints: 1) computational complexity; and 2) clustering performance. Clustering is one of the most useful tasks in data mining process. So, investigating the impact of dimension reduction on hyperspectral data clustering is justifiable. The proposed approach is based on thresholding the band correlation matrix and selecting the least correlated bands. Selected bands are then used to cluster the hyperspectral image. Experimental results on a real-world hyperspectral remote sensing data proved that the proposed approach will decrease computational complexity and lead to better clustering results. For evaluating the clustering performance, the Calinski-Harabasz, Davies-Bouldin and Krzanowski-Lai indices are used. These indices evaluate the clustering results using quantities and features inherent in the dataset. In other words, they do not need any external information.

Gholizadeh, Hamed

2013-09-01

382

Spectral change space representation for invariant material tracking in hyperspectral images  

NASA Astrophysics Data System (ADS)

An invariant material tracking algorithm requires a representation that is unaffected by environmental factors. An airborne hyperspectral sensor measures a radiance spectrum that, in general, will vary with atmospheric conditions and the scene geometry. Material tracking algorithms that directly match hyperspectral sensor measurements are therefore limited under general conditions. In this paper, we develop a low- dimensional subspace representation that can be used for material tracking over wide variation in environmental parameters. The material subspace is constructed using a single radiance spectrum from an unknown target material measured under unknown conditions. We demonstrate the subspace representation with a set of material identification experiments on HYDICE imagery from the Forest Radiance I and Desert Radiance II collections.

Slater, David; Healey, Glenn

1999-10-01

383

Real-time detection of targets in hyperspectral images using radial basis neural network filtering  

NASA Astrophysics Data System (ADS)

A spectral target recognition technique has been developed that detects targets in hyperspectral images in real time. The technique is based on the configuration of a radial basis neural network filter that is specific for a particular target spectral signature or series of target spectral signatures. Detection of targets in actual 36-band CASI, and 210-band HYDICE images is compared to existing recognition techniques and results in considerable reduction in overall image processing time and greater accuracy than existing spectral processing algorithms.

Thomas, Tom; Ozkan, M. Serkan

2007-09-01

384

An Efficient Hierarchical Hyperspectral Image Classification using Binary Quaternion-moment-preserving Thresholding Technique  

Microsoft Academic Search

In the study, we propose a novel unsupervised classification technique for hyperspectral images, which consists of two algorithms, referred to as the maximum correlation band clustering (MCBC) and hierarchical binary quaternion-moment-preserving (BQMP) thresholding technique. By the MCBC, we partition the bands into groups and transfer the high-dimensional image data into low-dimensional image features. Afterwards, the hierarchical BQMP approach partitions the

Lena Chang; Ching-Min Cheng; Yang-Lang Chang

2009-01-01

385

The Hyperspectral Imager Aboard the SSTI's Lewis Spacecraft: A Comparison with AVIRIS  

NASA Technical Reports Server (NTRS)

This paper compares the performance and operational parameters of the Hyperspectral Imager (HSI), scheduled for launch aboard the Lewis spacecraft in July 1996, with those of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The HSI is a pushbroom, imaging spectrometer with 30 meter spatial resolution, generating 384 spectral channels over the range 400 to 2500 nm at 5.0 to 6.4 nm resolution for each of its 256 crosstrack pixels.

Sokolowski, James K.; Witcher, Kern; Davis, Bruce A.; Green, Robert O.

1996-01-01

386

Terrain categorization from a linear etalon hyperspectral imager on MSTI-3  

Microsoft Academic Search

The MSTI-3 satellite payload included a wedge filter Hyperspectral Imager (HSI) system. This system provided a spectral image over a small range of wavelengths from 600 to 850 nm with a relatively coarse resolution estimated to be 70 m. The imaging system did not have either spectral or radiometric calibration during its on-orbit life cycle. Due to the orbit dawn\\/dusk

T. W. Cooley; D. Rosprim; T. Mahan; I. Thorsos

1998-01-01

387

Update on the imaging sensor for GIFTS  

NASA Astrophysics Data System (ADS)

Remote temperature sounding from the vantage point of Earth Orbit improves our weather forecasting, monitoring and analysis capability. Recent advances in the infrared hyperspectral sensor technology promise to improve the spatial and temperature resolution, while offering relatively quick re-look times to witness atmospheric dynamics. One approach takes advantage of a two-dimensional, imaging Fourier transform spectrometer to obtain a data cube with the field of view along one plane and multiple IR spectra (one for every FPA pixel) along the orthogonal axis. Only the pixel pitch in the imaging focal plane and the optics used to collect the data limit the spatial resolution. The maximum optical path difference in the Michelson FTS defines the spectral resolution and dictates the number of path-length interferogram samples (FPA frames required per cube). This paper discusses the unique challenges placed on the focal plane by the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) approach and how advanced focal plane technology is applied to satisfy these challenges. The instrument requires a midwave spectral band from 4.4 to 6.1m to capture the C02 and H20 absorption bands, and an optional VLWIR spectral band to cover from 8.85-14.6m. The paper presents performance data of Liquid Phase Epitaxy (LPE) fabricated HgCdTe detectors and design details of the advanced readout integrated circuit necessary to meet the demanding requirements of the imaging sensor for the GIFTS instrument. Point defects are removed by using a unique super-pixel approach to improve operability for the VLWIR focal plane. Finally, early focal plane performance measurements are reported, including Noise Equivalent Input, responsivity uniformity, output offset stability and 1/f noise knee.

Stobie, James A.; Tobin, Stephen P.; Norton, Peter W.; Hutchins, Mark A.; Wong, Kwok-Keung; Huppi, Ronald J.; Huppi, Ray

2004-11-01

388

Dimensionality reduction of hyperspectral imaging data using local principal components transforms  

NASA Astrophysics Data System (ADS)

The spectral exploitation of hyperspectral imaging (HSI) data is based on their representation as vectors in a high dimensional space defined by a set of orthogonal coordinate axes, where each axis corresponds to one spectral band. The larger number of bands, which varies from 100-400 in existing sensors, makes the storage, transmission, and processing of HSI data a challenging task. A practical way to facilitate these tasks is to reduce the dimensionality of HSI data without significant loss of information. The purpose of this paper is twofold. First, to provide a concise review of various approaches that have been used to reduce the dimensionality of HSI data, as a preprocessing step for compression, visualization, classification, and detection applications. Second, we show that the nonlinear and nonnormal structure of HSI data, can often be more effectively exploited by using a nonlinear dimensionality reduction technique known as local principal component analyzers. The performance of the various techniques is illustrated using HYDICE and AVIRIS HSI data.

Manolakis, Dimitris G.; Marden, David B.

2004-08-01

389

Characterization of post-consumer polyolefin wastes by hyperspectral imaging for quality control in recycling processes.  

PubMed

In this paper new analytical inspection strategies, based on hyperspectral imaging (HSI) in the VIS-NIR and NIR wavelength ranges (400-1000 and 1000-1700 nm, respectively), have been investigated and set up in order to define quality control logics that could be applied at industrial plant level for polyolefins recycling. The research was developed inside the European FP7 Project W2Plastics "Magnetic Sorting and Ultrasound Sensor Technologies for Production of High Purity Secondary Polyolefins from Waste". The main aim of the project is the separation of pure polyethylene and polypropylene adopting an innovative process, the magnetic density separation (MDS). Spectra of plastic particles and contaminants resulting from post-consumer complex wastes and of virgin polyolefins have been acquired by HSI and by Raman spectroscopy. The classification results obtained applying principal component analysis (PCA) on HSI data have been compared with those obtained by Raman spectroscopy, in order to validate the proposed innovative methodology. Results showed that HSI sensing techniques allow to identify both polyolefins and contaminants. Results also demonstrated that HSI has a great potentiality as a tool for quality control of feed (identification of contaminants in the plastic waste) and of the two different pure polypropylene and polyethylene flow streams resulting from the MDS-based recycling process. PMID:21745732

Serranti, Silvia; Gargiulo, Aldo; Bonifazi, Giuseppe

2011-11-01

390

Detection of fruit fly infestation in pickling cucumbers using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Fruit fly infestation can be a serious problem in pickling cucumber production. In the United States and many other countries, there is zero tolerance for fruit flies in pickled products. Currently, processors rely on manual inspection to detect and remove fruit fly-infested cucumbers, which is labor intensive and also prone to error due to human fatigue and the difficulty of visually detecting infestation that is hidden inside the fruit. In this research, a laboratory hyperspectral imaging system was used to detect fruit fly-infested pickling cucumbers. Hyperspectral reflectance (450-740 nm) and transmittance (740-1,000 nm) images were acquired simultaneously for 329 normal (infestation free) and fruit flyinfested pickling cucumbers of three size classes with the mean diameters of 16.8, 22.1, and 27.6 mm, respectively. Mean spectra were extracted from the hyperspectral image of each cucumber, and they were then corrected for the fruit size effect using a diameter correction equation. Partial least squares discriminant analyses for the reflectance, transmittance and their combined data were performed for differentiating normal and infested pickling cucumbers. With reflectance mode, the overall classification accuracies for the three size classes and mixed class were between 82% and 88%, whereas transmittance achieved better classification results with the overall accuracies of 88%-93%. Integration of reflectance and transmittance did not result in noticeable improvements, compared to transmittance mode. Overall, the hyperspectral imaging system performed better than manual inspection, which had an overall accuracy of 75% and decreased significantly for smaller size cucumbers. This research demonstrated that hyperspectral imaging is potentially useful for detecting fruit fly-infested pickling cucumbers.

Lu, Renfu; Ariana, Diwan P.

2011-06-01

391

In vivo snapshot hyperspectral image analysis of age-related macular degeneration  

PubMed Central

Drusen, the hallmark lesions of age related macular degeneration (AMD), are biochemically heterogeneous and the identification of their biochemical distribution is key to the understanding of AMD. Yet the challenges are to develop imaging technology and analytics, which respect the physical generation of the hyperspectral signal in the presence of noise, artifacts, and multiple mixed sources while maximally exploiting the full data dimensionality to uncover clinically relevant spectral signatures. This paper reports on the statistical analysis of hyperspectral signatures of drusen and anatomical regions of interest using snapshot hyperspectral imaging and non-negative matrix factorization (NMF). We propose physical meaningful priors as initialization schemes to NMF for finding low-rank decompositions that capture the underlying physiology of drusen and the macular pigment. Preliminary results show that snapshot hyperspectral imaging in combination with NMF is able to detect biochemically meaningful components of drusen and the macular pigment. To our knowledge, this is the first reported demonstration in vivo of the separate absorbance peaks for lutein and zeaxanthin in macular pigment. PMID:21096261

Lee, Noah; Wielaard, J.; Fawzi, A. A.; Sajda, P.; Laine, A. F.; Martin, G.; Humayun, M. S.; Smith, R. T.

2014-01-01

392

Relevance-based feature extraction for hyperspectral images.  

PubMed

Hyperspectral imagery affords researchers all discriminating details needed for fine delineation of many material classes. This delineation is essential for scientific research ranging from geologic to environmental impact studies. In a data mining scenario, one cannot blindly discard information because it can destroy discovery potential. In a supervised classification scenario, however, the preselection of classes presents one with an opportunity to extract a reduced set of meaningful features without degrading classification performance. Given the complex correlations found in hyperspectral data and the potentially large number of classes, meaningful feature extraction is a difficult task. We turn to the recent neural paradigm of generalized relevance learning vector quantization (GRLVQ) [B. Hammer and T. Villmann, Neural Networks vol. 15, pp. 1059-1068, 2002], which is based on, and substantially extends, learning vector quantization (LVQ) [T. Kohonen, Self-Organizing Maps, Berlin, Germany: Springer-Verlag, 2001] by learning relevant input dimensions while incorporating classification accuracy in the cost function. By addressing deficiencies in GRLVQ, we produce an improved version, GRLVQI, which is an effective analysis tool for high-dimensional data such as remotely sensed hyperspectral data. With an independent classifier, we show that the spectral features deemed relevant by our improved GRLVQI result in a better classification for a predefined set of surface materials than using all available spectral channels. PMID:18390311

Mendenhall, M J; Merenyi, E

2008-04-01

393

Image Sensor Application  

E-print Network

#12;#12;Toshiba ET8EK8 5MP CMOS Sensor Carl Zeiss F/2.8 5.2mm Lens Touchscreen LCD DSP USB 32GBLED Flash Shutter Button QWERTY Keyboard #12;Toshiba ET8EK8 5MP CMOS Sensor Carl Zeiss F/2.8 5.2mm Lens.9 Wh Li-Ion Battery PackLED Flash Shutter Button QWERTY Keyboard #12;Toshiba ET8EK8 5MP CMOS Sensor

Stanford University

394

Parallel implementation of linear and nonlinear spectral unmixing of remotely sensed hyperspectral images  

NASA Astrophysics Data System (ADS)

Hyperspectral unmixing is a very important task for remotely sensed hyperspectral data exploitation. It addresses the (possibly) mixed nature of pixels collected by instruments for Earth observation, which are due to several phenomena including limited spatial resolution, presence of mixing effects at different scales, etc. Spectral unmixing involves the separation of a mixed pixel spectrum into its pure component spectra (called endmembers) and the estimation of the proportion (abundance) of endmember in the pixel. Two models have been widely used in the literature in order to address the mixture problem in hyperspectral data. The linear model assumes that the endmember substances are sitting side-by-side within the field of view of the imaging instrument. On the other hand, the nonlinear mixture model assumes nonlinear interactions between endmember substances. Both techniques can be computationally expensive, in particular, for high-dimensional hyperspectral data sets. In this paper, we develop and compare parallel implementations of linear and nonlinear unmixing techniques for remotely sensed hyperspectral data. For the linear model, we adopt a parallel unsupervised processing chain made up of two steps: i) identification of pure spectral materials or endmembers, and ii) estimation of the abundance of each endmember in each pixel of the scene. For the nonlinear model, we adopt a supervised procedure based on the training of a parallel multi-layer perceptron neural network using intelligently selected training samples also derived in parallel fashion. The compared techniques are experimentally validated using hyperspectral data collected at different altitudes over a so-called Dehesa (semi-arid environment) in Extremadura, Spain, and evaluated in terms of computational performance using high performance computing systems such as commodity Beowulf clusters.

Plaza, Antonio; Plaza, Javier

2011-11-01

395

Wide-field imaging spectrometer for the Hyperspectral Infrared Imager (HyspIRI) mission  

NASA Astrophysics Data System (ADS)

We report on the design, tolerancing, and laboratory breadboard of an imaging spectrometer for the Earth Science Decadal Survey Hyperspectral and Infrared Imager (HyspIRI) mission. The spectrometer is of the Offner type but with a much longer slit than typical designs, with 1600 resolvable spatial elements along the slit for a length of 48 mm. Two such spectrometers cover more than the required swath while maintaining high throughput and signal-to-noise thanks to the large pixel size (30 ?m), relatively high speed (F/2.8) and small number of reflections. We also demonstrate a method for measuring smile using a linear array, and use the method to prove the achievement of negligible smile of less than 2% of a pixel over the entire 48 mm slit. Thus we show that this high-heritage, all-spherical mirror design can serve the requirements of the HyspIRI mission.

Bender, Holly A.; Mouroulis, Pantazis; Korniski, Ronald J.; Green, Robert O.; Wilson, Daniel W.

2014-09-01

396

Assessment of the hyperspectral sensor CASI-2 for macroalgal discrimination on the Ría de Vigo coast (NW Spain) using field spectroscopy and modelled spectral libraries  

NASA Astrophysics Data System (ADS)

Hyperspectral remote sensing from aircraft and satellite sensors is an important tool for mapping shallow benthic habitats in areas where high spectral and spatial resolutions are needed e.g. spatially heterogeneous coastal environments. However, the acquisition of hyperspectral images sometimes involves a high economic investment and there is no prior guarantee of their utility. Physics-based methods like bio-optical models are an alternative to assess sensors without purchasing the images. In this study we used a simple bio-optical model that simulates reflectance spectra for waters with variable depth and benthic macroalgal cover. The modelled spectral library was used to assess the capability of CASI-2 sensor to recognise different benthic macroalgal species. Reflectance spectra of 17 macroalgal species were used in the model simulations. Uni- and multi-variate statistical analyses were used to evaluate the spectral differences between several species. The results show that only a few species seem to be clearly differentiable: Codium tomentosum, Laminaria saccharina and Corallina officinalis. Therefore, further bio-optical modelling was applied at the level of taxonomic groups rather than species level. Emerged green, brown and red macroalgae as well as sand can be differentiated from each other when using the CASI-2 sensor. The bio-optical simulations showed that the three macroalgal groups can be separated from each other in waters shallower than 4 m when CASI-2 is used. Green and brown macroalgae can be differentiated from deep water if the water depth does not exceed 6 m whereas red macroalgae can be optically separated from deep water when the water depth is less than 5 m. Sea-beds covered with the three macroalgal groups are separable from sandy sea-beds in waters shallower than 10 m.

Casal, G.; Kutser, T.; Domínguez-Gómez, J. A.; Sánchez-Carnero, N.; Freire, J.

2013-03-01

397

Analysis of VIS-LWIR hyperspectral image data for detailed geologic mapping  

NASA Astrophysics Data System (ADS)

Research is being conducted into the usefulness of hyperspectral data for detailed geologic mapping applications. The data being analyzed were collected by the HYDICE (VIS-SWIR) and SEBASS (LWIR) airborne imaging spectrometers. Hyperspectral data provides a means of identifying surface minerology, which indicates lithology. In addition, because the data are collected in image format, photo-geologic observations can be made, such as the presence and orientation of stratification and faulting. The results of hyperspectral-based geologic mapping are summarized for an area of volcanic and sedimentary rocks in southwest Nevada. Analysis of the data revealed 11 mineral endmembers representing eight lithologic units. The hyperspectral-derived maps were directly compared to the best ground-based geologic maps available. Results indicate the ability to produce general geologic maps at scales better than 1:24,000 using 1-meter resolution airborne spectroscopy. Also, a more thorough mapping was achieved because of the increased compositional information gained by using both eht SWIR and LWIR.

Bowers, Timothy

2002-08-01

398

Aqueous Alteration Rinds in Basalt: Mineralogic Characterization from Hand Sample to Outcrop with Hyperspectral Imaging and Implications for Mars 2020  

NASA Astrophysics Data System (ADS)

Hydrothermally altered lacustrine pillow basalts show strong gradients in mineralogy, chemistry, and redox state from interior to exterior at thick section, hand sample, and outcrop scales identified with hyperspectral imaging and elemental mapping.

Greenberger, R. N.; Mustard, J. F.; Cloutis, E. A.; Mann, P.; Wilson, J. H.

2014-07-01

399

A Tool for Rapid Non-Destructive Characterization of Planetary Materials: Hyperspectral Imaging in the Visible/Near-Infrared  

NASA Astrophysics Data System (ADS)

Reflectance spectroscopy is an invaluable tool for meteorite analysis, and new developments in hyperspectral imaging allow for rapid, non-destructive, high spatial and spectral resolution mapping of meteorite samples.

Cannon, K. M.; Mustard, J. F.; Milliken, R. E.; Pieters, C. M.; Hiroi, T.; Wilson, J. H.

2014-09-01

400

Multi sensor satellite imagers for commercial remote sensing  

NASA Astrophysics Data System (ADS)

This paper will discuss and compare recent refractive and catodioptric imager designs developed and manufactured at SunSpace for Multi Sensor Satellite Imagers with Panchromatic, Multi-spectral, Area and Hyperspectral sensors on a single Focal Plane Array (FPA). These satellite optical systems were designed with applications to monitor food supplies, crop yield and disaster monitoring in mind. The aim of these imagers is to achieve medium to high resolution (2.5m to 15m) spatial sampling, wide swaths (up to 45km) and noise equivalent reflectance (NER) values of less than 0.5%. State-of-the-art FPA designs are discussed and address the choice of detectors to achieve these performances. Special attention is given to thermal robustness and compactness, the use of folding prisms to place multiple detectors in a large FPA and a specially developed process to customize the spectral selection with the need to minimize mass, power and cost. A refractive imager with up to 6 spectral bands (6.25m GSD) and a catodioptric imager with panchromatic (2.7m GSD), multi-spectral (6 bands, 4.6m GSD), hyperspectral (400nm to 2.35?m, 200 bands, 15m GSD) sensors on the same FPA will be discussed. Both of these imagers are also equipped with real time video view finding capabilities. The electronic units could be subdivided into the Front-End Electronics and Control Electronics with analogue and digital signal processing. A dedicated Analogue Front-End is used for Correlated Double Sampling (CDS), black level correction, variable gain and up to 12-bit digitizing and high speed LVDS data link to a mass memory unit.

Cronje, T.; Burger, H.; Du Plessis, J.; Du Toit, J. F.; Marais, L.; Strumpfer, F.

2005-10-01