Sample records for hyperspectral imaging sensors

  1. Sensor-informed representation of hyperspectral images

    Microsoft Academic Search

    Torbjorn Skauli

    2009-01-01

    Hyperspectral images are customarily stored and transferred as radiance values. Image analysis may benefit from additional sensor-related information such as signal-dependent noise levels. This paper discusses representations of hyperspectral image data in forms which are intermediate between raw data and radiance data. The intermediate-form data can be processed directly, or they can be readily converted into radiance values and estimates

  2. A sensor-data-based denoising framework for hyperspectral images.

    PubMed

    Deger, Ferdinand; Mansouri, Alamin; Pedersen, Marius; Hardeberg, Jon Y; Voisin, Yvon

    2015-02-01

    Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values. The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise. A spatially and spectrally adaptive total variation regularisation term accounts the structural proposition of a hyperspectral image cube. We evaluate the approach on a synthetic dataset that guarantees a noise-free ground truth, and the best results are achieved when the dark current is taken into account. PMID:25836066

  3. Real-time onboard hyperspectral-image compression system for a parallel push broom sensor

    Microsoft Academic Search

    Scott D. Briles

    1997-01-01

    For a dispersive hyperspectral imaging sensor, frames are continuously being generated with spatially continuous rows of differing spectral wavelengths. As the sensor advances in the direction of travel, a hyperspectral data cube can be constructed from adjacent frames. A hyperspectral sensor residing on a satellite would require either an extremely large bandwidth for the downlink or onboard data compression to

  4. Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

    NASA Technical Reports Server (NTRS)

    McCorkel, Joel; Kurt, Thome; Leisso, Nathan; Anderson, Nikolaus; Czapla-Myers, Jeff

    2009-01-01

    The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

  5. Methods for gas detection using stationary hyperspectral imaging sensors

    DOEpatents

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

    2012-04-24

    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.

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

    Microsoft Academic Search

    Scott D. Briles

    1996-01-01

    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

  7. Handheld hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Aallos, Ville-Veikko; Holmlund, Christer; Malinen, Jouko; Mäkynen, Jussi

    2010-04-01

    VTT Technical Research Centre of Finland has developed a new low cost hand-held staring hyperspectral imager for applications previously blocked by high cost of the instrumentation. The system is compatible with standard video and microscope lenses. The instrument can record 2D spatial images at several wavelength bands simultaneously. The concept of the hyperspectral imager has been published in SPIE Proc. 7474. The prototype fits in an envelope of 100 mm x 60 mm x 40 mm and its weight is ca. 300 g. The benefits of the new device compared to Acousto-Optic Tunable filter (AOTF) or Liquid Crystal Tunable Filter (LCTF) devices are small size and weight, speed of wavelength tuning, high optical throughput, independence of polarization state of incoming light and capability to record three wavelengths simultaneously. The operational wavelength range with Silicon-based CCD or CMOS sensors is 200 - 1100 nm and spectral resolution is 2 - 10 nm @ FWHM. Similar IR imagers can be built using InGaAs, InSb or MCT imaging sensors. The spatial resolution of the prototype is 480 x 750 pixels. It contains control system and memory for the image data acquisition. It operates either autonomously recording hyperspectral data cubes continuously or controlled by a laptop computer. The prototype was configured as a hyperspectral microscope for the spectral range 400 - 700 nm. The design of the hyperspectral imager, characterization results and sample measurement results are presented.

  8. A digital sensor simulator of the pushbroom Offner hyperspectral imaging spectrometer.

    PubMed

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

    2014-01-01

    Sensor simulators can be used in forecasting the imaging quality of a new hyperspectral imaging spectrometer, and generating simulated data for the development and validation of the data processing algorithms. This paper presents a novel digital sensor simulator for the pushbroom Offner hyperspectral imaging spectrometer, which is widely used in the hyperspectral remote sensing. Based on the imaging process, the sensor simulator consists of a spatial response module, a spectral response module, and a radiometric response module. In order to enhance the simulation accuracy, spatial interpolation-resampling, which is implemented before the spatial degradation, is developed to compromise the direction error and the extra aliasing effect. Instead of using the spectral response function (SRF), the dispersive imaging characteristics of the Offner convex grating optical system is accurately modeled by its configuration parameters. The non-uniformity characteristics, such as keystone and smile effects, are simulated in the corresponding modules. In this work, the spatial, spectral and radiometric calibration processes are simulated to provide the parameters of modulation transfer function (MTF), SRF and radiometric calibration parameters of the sensor simulator. Some uncertainty factors (the stability, band width of the monochromator for the spectral calibration, and the integrating sphere uncertainty for the radiometric calibration) are considered in the simulation of the calibration process. With the calibration parameters, several experiments were designed to validate the spatial, spectral and radiometric response of the sensor simulator, respectively. The experiment results indicate that the sensor simulator is valid. PMID:25615727

  9. A Digital Sensor Simulator of the Pushbroom Offner Hyperspectral Imaging Spectrometer

    PubMed Central

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

    2014-01-01

    Sensor simulators can be used in forecasting the imaging quality of a new hyperspectral imaging spectrometer, and generating simulated data for the development and validation of the data processing algorithms. This paper presents a novel digital sensor simulator for the pushbroom Offner hyperspectral imaging spectrometer, which is widely used in the hyperspectral remote sensing. Based on the imaging process, the sensor simulator consists of a spatial response module, a spectral response module, and a radiometric response module. In order to enhance the simulation accuracy, spatial interpolation-resampling, which is implemented before the spatial degradation, is developed to compromise the direction error and the extra aliasing effect. Instead of using the spectral response function (SRF), the dispersive imaging characteristics of the Offner convex grating optical system is accurately modeled by its configuration parameters. The non-uniformity characteristics, such as keystone and smile effects, are simulated in the corresponding modules. In this work, the spatial, spectral and radiometric calibration processes are simulated to provide the parameters of modulation transfer function (MTF), SRF and radiometric calibration parameters of the sensor simulator. Some uncertainty factors (the stability, band width of the monochromator for the spectral calibration, and the integrating sphere uncertainty for the radiometric calibration) are considered in the simulation of the calibration process. With the calibration parameters, several experiments were designed to validate the spatial, spectral and radiometric response of the sensor simulator, respectively. The experiment results indicate that the sensor simulator is valid. PMID:25615727

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

    Microsoft Academic Search

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

    2004-01-01

    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 panchromatic 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

  11. Hyperspectral image processing

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Hyperspectral Systems Increase Imaging Capabilities

    NASA Technical Reports Server (NTRS)

    2010-01-01

    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.

  13. Hyperspectral image compression with modified 3D SPECK

    Microsoft Academic Search

    Ruzelita Ngadiran; Said Boussakta; Ahmed Bouridane; Bayan Syarif

    2010-01-01

    Hyperspectral image consist of a set of contiguous images bands collected by a hyperspectral sensor. The large amount of data of hyperspectral images emphasizes the importance of efficient compression for storage and transmission. This paper proposes the simplified version of the three dimensional Set Partitioning Embedded bloCK (3D SPECK) algorithm for lossy compression of hyperspectral image. A three dimensional discrete

  14. Satellite Hyperspectral Imaging Simulation

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    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.

  15. Multipurpose hyperspectral imaging system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging system of high spectral and spatial resolution that incorporates several innovative features has been developed to incorporate a focal plane scanner (U.S. Patent 6,166,373). This feature enables the system to be used for both airborne/spaceborne and laboratory hyperspectral i...

  16. Uncooled long-wave infrared hyperspectral imaging

    NASA Technical Reports Server (NTRS)

    Lucey, Paul G. (Inventor)

    2006-01-01

    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.

  17. Hyperspectral pixels in 2D imaging FPAs?

    Microsoft Academic Search

    Paul D. Levan; Brian P. Beecken

    2009-01-01

    Dualband infrared focal plane arrays (FPA), developed for multi-spectral imaging applications, have advantages over conventional multi-FPA sensor configurations in compactness and band-to-band pixel registration. These FPAs have also enabled hyperspectral applications that employ gratings used in two orders, allowing high efficiency hyperspectral imaging over very broad wavelength regions. As time progresses, multi-waveband FPAs are expected to provide an increase in

  18. Airborne hyperspectral imaging in the visible-to-mid wave infrared spectral range by fusing three spectral sensors

    NASA Astrophysics Data System (ADS)

    Jakovels, Dainis; Filipovs, Jevgenijs; Erinš, Gatis; Taskovs, Juris

    2014-10-01

    Airborne hyperspectral imaging is widely used for remote sensing of environment. The choice of spectral region usually depends on the availability and cost of the sensor. Visible-to-near infrared (400-1100 nm) spectral range corresponds to spectral sensitivity of relatively cheap Si detectors therefore it is the most commonly used. The implementation of shortwave infrared (1100-3000 nm) requires more expensive solutions, but can provide valuable information about the composition of the substance. Mid wave infrared (3000-8000 nm) is rarely used for civilian applications, but it provides information on the thermal emission of materials. The fusion of different sensors allows spectral analysis of a wider spectral range combining and improving already existing algorithms for the analysis of chemical content and classification. Here we introduce our Airborne Surveillance and Environmental Monitoring System (ARSENAL) that was developed by fusing seven sensors. The first test results from the fusion of three hyperspectral imaging sensors in the visible-to-mid wave infrared (365-5000 nm) are demonstrated. Principal component analysis (PCA) is applied to test correlation between principal components (PCs) and common vegetation indices.

  19. Fast compression implementation for hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Hihara, Hiroki; Yoshida, Jun; Ishida, Juro; Takada, Jun; Senda, Yuzo; Suzuki, Makoto; Seki, Taeko; Ichikawa, Satoshi; Ohgi, Nagamitsu

    2010-11-01

    Fast and small foot print lossless image compressors aiming at hyper-spectral sensor for the earth observation satellite have been developed. Since more than one hundred channels are required for hyper-spectral sensors on optical observation satellites, fast compression algorithm with small foot print implementation is essential for reducing encoder size and weight resulting in realizing light-weight and small-size sensor system. The image compression method should have low complexity in order to reduce size and weight of the sensor signal processing unit, power consumption and fabrication cost. Coding efficiency and compression speed enables enlargement of the capacity of signal compression channels, which resulted in reducing signal compression channels onboard by multiplexing sensor signal channels into reduced number of compression channels. The employed method is based on FELICS1, which is hierarchical predictive coding method with resolution scaling. To improve FELICS's performance of image decorrelation and entropy coding, we applied two-dimensional interpolation prediction and adaptive Golomb-Rice coding, which enables small footprint. It supports progressive decompression using resolution scaling, whilst still delivering superior performance as measured by speed and complexity. The small footprint circuitry is embedded into the hyper-spectral sensor data formatter. In consequence, lossless compression function has been added without additional size and weight.

  20. Chemometric analysis of multi-sensor hyperspectral images of coarse mode aerosol particles for the image-based investigation on aerosol particles

    NASA Astrophysics Data System (ADS)

    Ofner, Johannes; Kamilli, Katharina A.; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

    2015-04-01

    Multi-sensor hyperspectral imaging is a novel technique, which allows the determination of composition, chemical structure and pure components of laterally resolved samples by chemometric analysis of different hyperspectral datasets. These hyperspectral datasets are obtained by different imaging methods, analysing the same sample spot and superimposing the hyperspectral data to create a single multi-sensor dataset. Within this study, scanning electron microscopy (SEM), Raman and energy-dispersive X-ray spectroscopy (EDX) images were obtained from size-segregated aerosol particles, sampled above Western Australian salt lakes. The particles were collected on aluminum foils inside a 2350 L Teflon chamber using a Sioutas impactor, sampling aerosol particles of sizes between 250 nm and 10 µm. The complex composition of the coarse-mode particles can be linked to primary emissions of inorganic species as well as to oxidized volatile organic carbon (VOC) emissions. The oxidation products of VOC emissions are supposed to form an ultra-fine nucleation mode, which was observed during several field campaigns between 2006 and 2013. The aluminum foils were analysed using chemical imaging and electron microscopy. A Horiba LabRam 800HR Raman microscope was used for vibrational mapping of an area of about 100 µm x 100 µm of the foils at a resolution of about 1 µm. The same area was analysed using a Quanta FEI 200 electron microscope (about 250 nm resolution). In addition to the high-resolution image, the elemental composition could be investigated using energy-dispersive X-ray spectroscopy. The obtained hyperspectral images were combined into a multi-sensor dataset using the software package Imagelab (Epina Software Labs, www.imagelab.at). After pre-processing of the images, the multi-sensor hyperspectral dataset was analysed using several chemometric methods such as principal component analysis (PCA), hierarchical cluster analysis (HCA) and other multivariate methods. Vertex component analysis (VCA) allowed the extraction of single spectra of pure components such as gypsum, NaNO3 and oxidized VOC). Different aerosol species related to the salt lakes (e.g. inorganic salts) and the surrounding land (e.g. silica particles) could be uncovered. Furthermore, the interaction of primary particles with volatile organic species, released from remains of the former eucalyptus forests and crop plants, could be identified. The application of multi-sensor imaging to size-segregated laterally resolved aerosol particles deepens the understanding of composition, linkage, interfaces and single components of complex mixtures of atmospheric aerosol particles, and therefore gives access to an intrinsic understanding of the nature of these particles.

  1. The Hyperspectral Airborne Tactical Instrument (HATI): a low-cost compact airborne hyperspectral imager

    Microsoft Academic Search

    S. Sandor-Leahy; S. Thordarson; B. Baldauf; M. Figueroa; M. Helmlinger; H. Miller; T. Reynolds; J. Shepanski

    2009-01-01

    Northrop Grumman Aerospace Systems (NGAS) has developed the Hyperspectral Airborne Tactical Instrument (HATI), a compact airborne hyperspectral imager designed to fly on a variety of platforms and to be integrated with other sensors in the NGAS instrument suite. HATI has taken part in a variety of missions and flown in conjunction with other NGAS airborne sensors including the recently-developed NGAS

  2. Infrared upconversion hyperspectral imaging.

    PubMed

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

    2015-03-15

    In this Letter, hyperspectral imaging in the mid-IR spectral region is demonstrated based on nonlinear frequency upconversion and subsequent imaging using a standard Si-based CCD camera. A series of upconverted images are acquired with different phase match conditions for the nonlinear frequency conversion process. From this, a sequence of monochromatic images in the 3.2-3.4 ?m range is generated. The imaged object consists of a standard United States Air Force resolution target combined with a polystyrene film, resulting in the presence of both spatial and spectral information in the infrared image. PMID:25768151

  3. Compression technique for plume hyperspectral images

    NASA Astrophysics Data System (ADS)

    Feather, B. K.; Fulkerson, S. A.; Jones, J. H.; Reed, R. A.; Simmons, M. A.; Swann, D. G.; Taylor, W. E.; Bernstein, L. S.

    2005-06-01

    The authors recently developed a hyperspectral image output option for a standardized government code designed to predict missile exhaust plume infrared signatures. Typical predictions cover the 2- to 5-m wavelength range (2000 to 5000 cm-1) at 5 cm-1 spectral resolution, and as a result the hyperspectral images have several hundred frequency channels. Several hundred hyperspectral plume images are needed to span the full operational envelope of missile altitude, Mach number, and aspect angle. Since the net disk storage space can be as large as 100 GB, a Principal Components Analysis is used to compress the spectral dimension, reducing the volume of data to just a few gigabytes. The principal challenge was to specify a robust default setting for the data compression routine suitable for general users, who are not necessarily specialists in data compression. Specifically, the objective was to provide reasonable data compression efficiency of the hyperspectral imagery while at the same time retaining sufficient accuracy for infrared scene generation and hardware-in-the-loop test applications over a range of sensor bandpasses and scenarios. In addition, although the end users of the code do not usually access the detailed spectral information contained in these hyperspectral images, this information must nevertheless be of sufficient fidelity so that atmospheric transmission losses between the missile plume and the sensor could be reliably computed as a function of range. Several metrics were used to determine how far the plume signature hyperspectral data could be safely compressed while still meeting these end-user requirements.

  4. Hyperspectral imaging applied to forensic medicine

    Microsoft Academic Search

    Donald B. Malkoff; William R. Oliver

    2000-01-01

    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

  5. Scalable Hyperspectral Image Coding

    Microsoft Academic Search

    Xiaoli Tang; William A. Pearlman

    2005-01-01

    Here we propose scalable Three-Dimensional Set Partitioned Embedded bloCK (3D-SPECK)–an embedded, block-based, wavelet transform coding algorithm of low complexity for hyperspectral image compression. Scalable 3D-SPECK supports both SNR and resolution progressive coding. After wavelet transform, 3D-SPECK treats each subband as a coding block. To generate SNR scalable bitstream, the stream is organized so that the same indexed bit planes are

  6. Novel hyperspectral imager for lightweight UAVs

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

    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.

  7. Hyperspectral image projector applications

    NASA Astrophysics Data System (ADS)

    Rice, Joseph P.; Brown, Steven W.; Allen, David W.; Yoon, Howard W.; Litorja, Maritoni; Hwang, Jeeseong C.

    2012-03-01

    For the past several years NIST has been developing, along with several collaborators, a Hyperspectral Image Projector (HIP). This scene projector produces high-resolution programmable spectra and projects them into dynamic two-dimensional images. The current digital micromirror device (DMD) based HIP prototype has a spatial resolution of 1024 x 768 pixels and a spectral range of 450 nm to 2400 nm, with spectral resolution from 2 nm in the visible to 5 nm in the short-wave infrared. It disperses light from a supercontinuum fiber source across two DMDs to produce the programmable spectra, which then globally-illuminate a third DMD to form the spatial images. The HIP can simulate top-of-the atmosphere spectral radiance over a 10 mm x 14 mm, f/3 image, and this can be collimated to stimulate remote sensing instruments. Also, the spectral radiance of the projected scenes can be measured with a NIST-calibrated spectroradiometer, such that the spectral radiance projected into each pixel can be accurately known. The HIP was originally developed for applications in multi-spectral and hyperspectral imager testing, calibration, and performance validation, and examples of this application will be reviewed. Conceivable applications for the HIP in photovoltaic device characterization and optical medical imaging will also be discussed.

  8. Band Selection of Hyperspectral Images Based on Bhattacharyya Distance

    Microsoft Academic Search

    CAI SIMIN; ZHANG RONGQUN; CHENG WENLING; YUAN HUI

    With the development of sensor technology, the spectral resolution of remote sensing image is continuously improved. The appearance of the hyperspectral remote sensing is a tremendous leap in the field of remote sensing. The increasing availability of hyperspectral data and image has enriched us with better and finer data and it also enable us a much stronger ability to identify

  9. Comparison of Hadamard imaging and compressed sensing for low resolution hyperspectral imaging

    Microsoft Academic Search

    L. Streeter; G. R. Burling-Claridge; M. J. Cree; R. Kunnemeyer

    2008-01-01

    Image multiplexing is the technique of using combination patterns to measure multiple pixels with one sensor. Hyperspectral imaging is acquiring images with full spectra at each pixel. Using a single point spectrometer and light modulation we perform multiplexed hyperspectral imaging. We compare two forms of multiplexing, namely Hadamard imaging and compressed sensing, at low resolution. We show that Hadamard imaging

  10. Perceptual-based image fusion for hyperspectral data

    Microsoft Academic Search

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

    1997-01-01

    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

  11. Hyperspectral Imager-Tracker

    NASA Technical Reports Server (NTRS)

    Agurok, Llya

    2013-01-01

    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.

  12. Hyperspectral imaging of coastal regions from the ISS

    Microsoft Academic Search

    Todd J. Mosher; Megan L. Mitchell; Paul G. Lucey; Eric Hochberg

    2005-01-01

    The Hyperspectral Imager for Coastal Oceans (HICO) sensor system, integrated in the International Space Station (ISS) Window Observational Research Facility (WORF), will collect visible and short-wave infrared hyperspectral data that will provide the following characterization of coastal regions: - Determine water clarity and visibility, shallow water bathymetry, and bottom type composition. - Detect underwater obstructions and characterize beaches and coastal

  13. Hyperspectral imaging of coastal regions from the ISS

    NASA Astrophysics Data System (ADS)

    Mosher, Todd J.; Mitchell, Megan L.; Lucey, Paul G.; Hochberg, Eric

    2005-01-01

    The Hyperspectral Imager for Coastal Oceans (HICO) sensor system, integrated in the International Space Station (ISS) Window Observational Research Facility (WORF), will collect visible and short-wave infrared hyperspectral data that will provide the following characterization of coastal regions: - Determine water clarity and visibility, shallow water bathymetry, and bottom type composition. - Detect underwater obstructions and characterize beaches and coastal areas. - Research global properties of coral reefs, the maritime atmosphere and determine global distribution of fires and active volcanoes in the context of mitigating natural hazards. It will achieve these objectives by collecting hyperspectral imaging data for over 70% of the Earth's surface, the portion flown over by ISS, at a spatial resolution of 25 meters. The desired data will be obtained using the Naval Research Lab (NRL) Portable Hyperspectral Imager for Low Light Spectroscopy (PHILLS-3) sensor with a pointing and stabilization system and then later integrating it with a short-wave infrared hyperspectral imager.

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

    E-print Network

    Kerekes, John

    and to provide new prediction tools to assist with hyperspectral imaging sensor design and operation. Keywords*kerekes@cis.rit.edu Hyperspectral image quality for unmixing and subpixel detection applications, NY, USA 14623 ABSTRACT The quality of remotely sensed hyperspectral images is not easily assessed

  15. Medical hyperspectral imaging: a review

    PubMed Central

    Lu, Guolan; Fei, Baowei

    2014-01-01

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

  16. Miniaturization of a SWIR hyperspectral imager

    Microsoft Academic Search

    Christopher P. Warren; William Pfister; Detlev Even; Arleen Velasco; Selwyn Yee; David Breitwieser; Joseph Naungayan

    2011-01-01

    A new approach for the design and fabrication of a miniaturized SWIR Hyperspectral imager is described. Previously, good results were obtained with a VNIR Hyperspectral imager, by use of light propagation within bonded solid blocks of fused silica. These designs use the Offner design form, providing excellent, low distortion imaging. The same idea is applied to the SWIR Hyperspectral imager

  17. Deblurring and Sparse Unmixing For Hyperspectral Images

    E-print Network

    Plemmons, Robert J.

    Deblurring and Sparse Unmixing For Hyperspectral Images Xi-Le Zhao, Fan Wang, Ting-Zhu Huang for hyperspectral imaging whose PSFs are generally system dependent and result from axial optical aberrations

  18. Satellite Hyperspectral Imaging Simulation

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

    Simulations of generic pushbroom satellite hyperspetral 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 simulaitons start with a generation of synthetic scenes form material maps of studied terrain. Scene-reflected radiance is corrected for atmospheric effects and convolved with sensor spectral response uwing MODTRAN 4 radiance and transmission calculations. Scene images are further convolved with point spread functions derived from Optical Transfer Functions (OTF's) of the sensor system. Photon noise and detector/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 ratos and expected performance are estimated for typica satellite system specifications and are discussed for all the scenes.

  19. Hyperspectral Imaging or Imaging Spectroscopy

    E-print Network

    Gilbes, Fernando

    scan procedure to increase FOV. #12;Linear Array CCD Area Array CCD #12;Landsat ETM Focal Plane Array, is obtained in time as sensor is moved across the scene. y x #12;2D Array Usage in Imaging Spectrometer Focal Plane Array Diffraction Grating x Slit Focusing Optics Scene FOV Focusing Optics #12;Pushbroom Sensor

  20. On-orbit characterization of hyperspectral imagers

    NASA Astrophysics Data System (ADS)

    McCorkel, Joel

    Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne- and satellite-based sensors. Often, ground-truth measurements at these tests sites are not always successful due to weather and funding availability. Therefore, RSG has also employed automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor. This dissertation presents a method for determining the radiometric calibration of a hyperspectral imager using multispectral imagery. The work relies on a multispectral sensor, Moderate-resolution Imaging Spectroradiometer (MODIS), as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. A method to predict hyperspectral surface reflectance using a combination of MODIS data and spectral shape information is developed and applied for the characterization of Hyperion. Spectral shape information is based on RSG's historical in situ data for the Railroad Valley test site and spectral library data for the Libyan test site. Average atmospheric parameters, also based on historical measurements, are used in reflectance prediction and transfer to space. Results of several cross-calibration scenarios that differ in image acquisition coincidence, test site, and reference sensor are found for the characterization of Hyperion. These are compared with results from the reflectance-based approach of vicarious calibration, a well-documented method developed by the RSG that serves as a baseline for calibration performance for the cross-calibration method developed here. Cross-calibration provides results that are within 2% of those of reflectance-based results in most spectral regions. Larger disagreements exist for shorter wavelengths studied in this work as well as in spectral areas that experience absorption by the atmosphere.

  1. Vicarious calibration of airborne hyperspectral sensors in operational environments

    Microsoft Academic Search

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

    2001-01-01

    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

  2. Curvelet based hyperspectral image fusion

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    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.

  3. Synergetics Framework for Hyperspectral Image Classification

    NASA Astrophysics Data System (ADS)

    Müller, R.; Cerra, D.; Reinartz, P.

    2013-05-01

    In this paper a new classification technique for hyperspectral data based on synergetics theory is presented. Synergetics - originally introduced by the physicist H. Haken - is an interdisciplinary theory to find general rules for pattern formation through selforganization and has been successfully applied in fields ranging from biology to ecology, chemistry, cosmology, and thermodynamics up to sociology. Although this theory describes general rules for pattern formation it was linked also to pattern recognition. Pattern recognition algorithms based on synergetics theory have been applied to images in the spatial domain with limited success in the past, given their dependence on the rotation, shifting, and scaling of the images. These drawbacks can be discarded if such methods are applied to data acquired by a hyperspectral sensor in the spectral domain, as each single spectrum, related to an image element in the hyperspectral scene, can be analysed independently. The classification scheme based on synergetics introduces also methods for spatial regularization to get rid of "salt and pepper" classification results and for iterative parameter tuning to optimize class weights. The paper reports an experiment on a benchmark data set frequently used for method comparisons. This data set consists of a hyperspectral scene acquired by the Airborne Visible Infrared Imaging Spectrometer AVIRIS sensor of the Jet Propulsion Laboratory acquired over the Salinas Valley in CA, USA, with 15 vegetation classes. The results are compared to state-of-the-art methodologies like Support Vector Machines (SVM), Spectral Information Divergence (SID), Neural Networks, Logistic Regression, Factor Graphs or Spectral Angle Mapper (SAM). The outcomes are promising and often outperform state-of-the-art classification methodologies.

  4. Fusion of Hyperspectral and Multispectral Image Data for Enhancement of Spectral and Spatial Resolution

    NASA Astrophysics Data System (ADS)

    Chakravortty, S.; Subramaniam, P.

    2014-11-01

    Hyperspectral image enhancement has been a concern for the remote sensing society for detailed end member detection. Hyperspectral remote sensor collects images in hundreds of narrow, continuous spectral channels, whereas multispectral remote sensor collects images in relatively broader wavelength bands. However, the spatial resolution of the hyperspectral sensor image is comparatively lower than that of the multispectral. As a result, spectral signatures from different end members originate within a pixel, known as mixed pixels. This paper presents an approach for obtaining an image which has the spatial resolution of the multispectral image and spectral resolution of the hyperspectral image, by fusion of hyperspectral and multispectral image. The proposed methodology also addresses the band remapping problem, which arises due to different regions of spectral coverage by multispectral and hyperspectral images. Therefore we apply algorithms to restore the spatial information of the hyperspectral image by fusing hyperspectral bands with only those bands which come under each multispectral band range. The proposed methodology is applied over Henry Island, of the Sunderban eco-geographic province. The data is collected by the Hyperion hyperspectral sensor and LISS IV multispectral sensor.

  5. A MATLAB toolbox for Hyperspectral Image Analysis

    Microsoft Academic Search

    Emmanuel Arzuaga-Cruz; Luis O. Jimenez-Rodriguez; Miguel Velez-Reyes; David Kaeli; Eladio Rodriguez-Diaz; Hector T. Velazquez-Santana; Alexey Castrodad-Carrau; Laura E. Santos-Campis; Cesar Santiago

    2004-01-01

    The Hyperspectral Image Analysis (HIA) toolbox 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 of the HIA Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. The HIA toolbox has been developed as

  6. Modification of the ocean PHILLS hyperspectral imager for the International Space Station and the HyGEIA program

    Microsoft Academic Search

    Michael R. Corson; Jeffrey H. Bowles; Wei Chen; Curtiss O. Davis; Clinton E. Dorris; Kiera H. Gallelli; Daniel R. Korwan; Lisa A. Policastri

    2003-01-01

    The Naval Research Laboratory and the Boeing Company have teamed to fly the NRL ocean Portable Hyperspectral Imager for Low Light Spectroscopy (ocean PHILLS) on board the International Space Station (ISS). This joint program is named the Hyperspectral Sensor for Global Environmental Imaging and Analysis (HyGEIA). Hyperspectral images spanning the wavelength range 400 to 1000 nm will be collected at

  7. Modification of the ocean PHILLS hyperspectral imager for the International Space Station and the HyGEIA program

    Microsoft Academic Search

    Michael R. Corson; Jeffrey H. Bowles; Wei Chen; Curtiss O. Davis; Clinton E. Dorris; Kiera H. Gallelli; Daniel R. Korwan; Lisa A. Policastri

    2004-01-01

    The Naval Research Laboratory and the Boeing Company have teamed to fly the NRL ocean Portable Hyperspectral Imager for Low Light Spectroscopy (ocean PHILLS) on board the International Space Station (ISS). This joint program is named the Hyperspectral Sensor for Global Environmental Imaging and Analysis (HyGEIA). Hyperspectral images spanning the wavelength range 400 to 1000 nm will be collected at

  8. Development of a new airborne hyperspectral imager for volcano observations

    Microsoft Academic Search

    Tetsuya Jitsufuchi

    2010-01-01

    We developed a new airborne hyperspectral sensor, the Airborne Radiative Transfer Spectral Scanner (ARTS), for hyperspectral volcano observations. ARTS is a push-broom imaging spectrometer covering wavelengths from 380 to 2,450nm and 8,000 to 11,500nm with 421 bands. This study describes the ARTS system specifications and presents some in-flight performance test results obtained from the ARTS instrument overflight of the NIED

  9. Hyperspectral imaging of ischemic wounds

    NASA Astrophysics Data System (ADS)

    Gnyawali, Surya C.; Elgharably, Haytham; Melvin, James; Huang, Kun; Bergdall, Valerie; Allen, David W.; Hwang, Jeeseong; Litorja, Maritoni; Shirley, Eric; Sen, Chandan K.; Xu, Ronald

    2012-03-01

    Optical imaging has the potential to achieve high spatial resolution and high functional sensitivity in wound assessment. However, clinical acceptance of many optical imaging devices is hampered by poor reproducibility, low accuracy, and lack of biological interpretation. We developed an in vivo model of ischemic flap for non-contact assessment of wound tissue functional parameters and spectral characteristics. The model was created by elevating the bipedicle skin flaps of a domestic pig from the underlying vascular bed and inhibiting graft bed reperfusion by a silastic sheet. Hyperspectral imaging was carried out on the ischemic flap model and compared with transcutaneous oxygen tension and perfusion measurements at different positions of the wound. Hyperspectral images have also been captured continuously during a post-occlusive reactive hyperemia (PORH) procedure. Tissue spectral characteristics obtained by hyperspectral imaging correlated well with cutaneous tissue oxygen tension, blood perfusion, and microscopic changes of tissue morphology. Our experiments not only demonstrated the technical feasibility for quantitative assessment of chronic wound but also provided a potential digital phantom platform for quantitative characterization and calibration of medical optical devices.

  10. Information-theoretic assessment of sampled hyperspectral imagers

    Microsoft Academic Search

    Bruno Aiazzi; Luciano Alparone; Alessandro Barducci; Stefano Baronti; Ivan Pippi

    2001-01-01

    This work focuses on estimating the information conveyed to a user by hyperspectral image data. The goal is establishing the extent to which an increase in spectral resolution enhances the amount of usable information. Indeed, a tradeoff exists between spatial and spectral resolution due to physical constraints of multi-band sensors imaging with a prefixed SNR. After describing an original method

  11. Quality assessment for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    Image quality assessment is an essential value judgement approach for many applications. Multi & hyper spectral imaging has more judging essentials than grey scale or RGB imaging and its image quality assessment job has to cover up all-around evaluating factors. This paper presents an integrating spectral imaging quality assessment project, in which spectral-based, radiometric-based and spatial-based statistical behavior for three hyperspectral imagers are jointly executed. Spectral response function is worked out based on discrete illumination images and its spectral performance is deduced according to its FWHM and spectral excursion value. Radiometric response ability of different spectral channel under both on-ground and airborne imaging condition is judged by SNR computing based upon local RMS extraction and statistics method. Spatial response evaluation of the spectral imaging instrument is worked out by MTF computing with slanted edge analysis method. Reported pioneering systemic work in hyperspectral imaging quality assessment is carried out with the help of several domestic dominating work units, which not only has significance in the development of on-ground and in-orbit instrument performance evaluation technique but also takes on reference value for index demonstration and design optimization for instrument development.

  12. SPATIALLY-COHERENT NON-LINEAR DIMENSIONALITY REDUCTION AND SEGMENTATION OF HYPER-SPECTRAL IMAGES

    E-print Network

    Minnesota, University of

    by sensors such as AVIRIS (Airborne Visible/Infrared Imaging Spectrometer, a NASA/Jet Propulsion LaboratorySPATIALLY-COHERENT NON-LINEAR DIMENSIONALITY REDUCTION AND SEGMENTATION OF HYPER-SPECTRAL IMAGES-Coherent Non-Linear Dimensionality Reduction and Segmentation of Hyper-Spectral Images Anish Mohan,1 Guillermo

  13. Landmine detection using passive hyperspectral imaging

    Microsoft Academic Search

    John E. McFee; Cliff Anger; Steve Achal; Tyler Ivanco

    2007-01-01

    Airborne hyperspectral imaging has been studied since the late 1980s as a tool to detect minefields for military countermine operations and for level I clearance for humanitarian demining. Hyperspectral imaging employed on unmanned ground vehicles may also be used to augment or replace broadband imagers to detect individual mines. This paper will discuss the ability of different optical wavebands -

  14. Supervised hyperspectral image segmentation using active learning

    Microsoft Academic Search

    Jun Li; J. M. Bioucas-Dias; Antonio Plaza

    2010-01-01

    This paper introduces a new supervised Bayesian approach to hyper-spectral image segmentation. The algorithm mainly consists of two steps: (a) learning, for each class label, the posterior probability distributions, based on a multinomial logistic regression model; (b) segmenting the hyperspectral image, based on the posterior probability distribution of the image of class labels built on the learned pixel-wise class distributions

  15. Contribute 1 Segmentation of hyperspectral images

    E-print Network

    Louchet, Cecile - Le Laboratoire de Mathématiques

    acquire whole spectra (224 values for each spectrum for the AVIRIS images from the NASA for instanceContribute 1 Segmentation of hyperspectral images from functional kernel density estima- tion Laurent Delsol, C´ecile Louchet Abstract The processing of hyperspectral images, seen as functions

  16. The civil air patrol ARCHER hyperspectral sensor system

    NASA Astrophysics Data System (ADS)

    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

    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.

  17. Hyperspectral imaging applied to forensic medicine

    NASA Astrophysics Data System (ADS)

    Malkoff, Donald B.; Oliver, William R.

    2000-03-01

    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.

  18. Hyperspectral Image Analysis Program

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Information on imaging spectrometry is given in the forms of outlines, graphs, and charts. Topics covered include impacts on science users, program objectives, expert systems for imaging spectrometry, and imaging spectrometer data analysis methods.

  19. Detection of landmines using hyperspectral imaging

    Microsoft Academic Search

    Nicola Playle

    2006-01-01

    There is a need for the stand-off detection of landmines either from a land or air based platform. Hyperspectral imaging technology has great potential for stand-off landmine detection. This paper will detail work undertaken by the UK Defence Science and Technology laboratory (Dstl) investigating the use of hyperspectral imaging for the detection of landmines. Both land and air based imagery

  20. Multiband Lossless Compression of Hyperspectral Images

    Microsoft Academic Search

    Enrico Magli

    2009-01-01

    Hyperspectral images exhibit significant spectral correlation, whose exploitation is crucial for compression. In this paper, we investigate the problem of predicting a given band of a hyperspectral image using more than one previous band. We present an information-theoretic analysis based on the concept of conditional entropy, which is used to assess the available amount of correlation and the potential compression

  1. Interest Points for Hyperspectral Image Data

    Microsoft Academic Search

    Amit Mukherjee; Miguel Velez-Reyes; Badrinath Roysam

    2009-01-01

    Interest points are widely used as point-features for image matching. This paper describes robust and efficient algorithms to extract multiscale interest points in hyperspectral images in which structural information is distributed across several spectral bands. The formulation is based on a Gaussian scale-space representation of the hyperspectral data cube, and the use of a principal components decomposition to combine information

  2. Novel miniaturized hyperspectral sensor for UAV and space applications

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Aallos, Ville-Veikko; Akujärvi, Altti; Antila, Tapani; Holmlund, Christer; Kantojärvi, Uula; Mäkynen, Jussi; Ollila, Jyrki

    2009-09-01

    In many hyperspectral applications it is beneficial to produce 2D spatial images with a single exposure at a few selected wavelength bands instead of 1D spatial and all spectral band images like in push-broom instruments. VTT has developed a new concept based on the Piezo actuated Fabry-Perot Interferometer to enable recording of 2D spatial images at the selected wavelength bands simultaneously. The sensor size is compatible with light weight UAV platforms. In our spectrometer the multiple orders of the Fabry-Perot Interferometer are used at the same time matched to the sensitivities of a multispectral RGB-type image sensor channels. We have built prototypes of the new spectrograph fitting inside of a 40 mm x 40 mm x 20 mm envelope and with a mass less than 50 g. The operational wavelength range of built prototypes can be tuned in the range 400 - 1100 nm and the spectral resolution is in the range 5 - 10 nm @ FWHM. Presently the spatial resolution is 480 x 750 pixels but it can be increased simply by changing the image sensor. The hyperspectral imager records simultaneously a 2D image of the scenery at three narrow wavelength bands determined by the selected three orders of the Fabry-Perot Interferometer which depend on the air gap between the mirrors of the Fabry-Perot Cavity. The new sensor can be applied on UAV, aircraft, and other platforms requiring small volume, mass and power consumption. The new low cost hyperspectral imager can be used also in many industrial and medical applications.

  3. Eigen wavelet: hyperspectral image compression algorithm

    Microsoft Academic Search

    S. Srinivasan; L. N. Kanal

    1999-01-01

    Summary form only given. The increased information content of hyperspectral imagery over multispectral data has attracted significant interest from the defense and remote sensing communities. We develop a mechanism for compressing hyperspectral imagery with no loss of information. The challenge of hyperspectral image compression lies in the non-isotropy and non-stationarity that is displayed across the spectral channels. Short-range dependence is

  4. Hyperspectral Imaging of human arm

    NASA Technical Reports Server (NTRS)

    2003-01-01

    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.

  5. Common hyperspectral image database design

    NASA Astrophysics Data System (ADS)

    Tian, Lixun; Liao, Ningfang; Chai, Ali

    2009-11-01

    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.

  6. Vessel contrast enhancement in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Bjorgan, Asgeir; Denstedt, Martin; Milani?, Matija; Paluchowski, Lukasz A.; Randeberg, Lise L.

    2015-03-01

    Imaging of vessel structures can be useful for investigation of endothelial function, angiogenesis and hyper-vascularization. This can be challenging for hyperspectral tissue imaging due to photon scattering and absorption in other parts of the tissue. Real-time processing techniques for enhancement of vessel contrast in hyperspectral tissue images were investigated. Wavelet processing and an inverse diffusion model were employed, and compared to band ratio metrics and statistical methods. A multiscale vesselness filter was applied for further enhancement. The results show that vessel structures in hyperspectral images can be enhanced and characterized using a combination of statistical, numerical and more physics informed models.

  7. A Compact Visible\\/Near Infrared Hyperspectral Imager

    Microsoft Academic Search

    James E. Murguia; Toby D. Reeves; Jonathan M. Mooney; William S. Ewing; Freeman D. Shepherd; Andrzej Brodzik; Hanscom AFB; Bedford MA

    2000-01-01

    This paper reports on the design, performance and signal processing of a visible\\/near infrared (VIS-NIR) chromotomographic hyperspectral imaging sensor. The sensor consists of a telescope, a direct vision prism, and a framing video camera. The direct vision prism is a two-prism set, arranged such that one wavelength passes undeviated, while the other wavelengths are dispersed along a line. The prism

  8. Hyperspectral Imaging and Related Field Methods: Building the Science

    NASA Technical Reports Server (NTRS)

    Goetz, Alexander F. H.; Steffen, Konrad; Wessman, Carol

    1999-01-01

    The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

  9. Combining hyperspectral imaging and Raman spectroscopy for remote chemical sensing

    NASA Astrophysics Data System (ADS)

    Ingram, John M.; Lo, Edsanter

    2008-04-01

    The Photonics Research Center at the United States Military Academy is conducting research to demonstrate the feasibility of combining hyperspectral imaging and Raman spectroscopy for remote chemical detection over a broad area of interest. One limitation of future trace detection systems is their ability to analyze large areas of view. Hyperspectral imaging provides a balance between fast spectral analysis and scanning area. Integration of a hyperspectral system capable of remote chemical detection will greatly enhance our soldiers' ability to see the battlefield to make threat related decisions. It can also queue the trace detection systems onto the correct interrogation area saving time and reconnaissance/surveillance resources. This research develops both the sensor design and the detection/discrimination algorithms. The one meter remote detection without background radiation is a simple proof of concept.

  10. Development of a handheld widefield hyperspectral imaging (HSI) sensor for standoff detection of explosive, chemical, and narcotic residues

    NASA Astrophysics Data System (ADS)

    Nelson, Matthew P.; Basta, Andrew; Patil, Raju; Klueva, Oksana; Treado, Patrick J.

    2013-05-01

    The utility of Hyper Spectral Imaging (HSI) passive chemical detection employing wide field, standoff imaging continues to be advanced in detection applications. With a drive for reduced SWaP (Size, Weight, and Power), increased speed of detection and sensitivity, developing a handheld platform that is robust and user-friendly increases the detection capabilities of the end user. In addition, easy to use handheld detectors could improve the effectiveness of locating and identifying threats while reducing risks to the individual. ChemImage Sensor Systems (CISS) has developed the HSI Aperio™ sensor for real time, wide area surveillance and standoff detection of explosives, chemical threats, and narcotics for use in both government and commercial contexts. Employing liquid crystal tunable filter technology, the HSI system has an intuitive user interface that produces automated detections and real-time display of threats with an end user created library of threat signatures that is easily updated allowing for new hazardous materials. Unlike existing detection technologies that often require close proximity for sensing and so endanger operators and costly equipment, the handheld sensor allows the individual operator to detect threats from a safe distance. Uses of the sensor include locating production facilities of illegal drugs or IEDs by identification of materials on surfaces such as walls, floors, doors, deposits on production tools and residue on individuals. In addition, the sensor can be used for longer-range standoff applications such as hasty checkpoint or vehicle inspection of residue materials on surfaces or bulk material identification. The CISS Aperio™ sensor has faster data collection, faster image processing, and increased detection capability compared to previous sensors.

  11. Hyperspectral imaging of atherosclerotic plaques in vitro

    NASA Astrophysics Data System (ADS)

    Larsen, Eivind L. P.; Randeberg, Lise L.; Olstad, Elisabeth; Haugen, Olav A.; Aksnes, Astrid; Svaasand, Lars O.

    2011-02-01

    Vulnerable plaques constitute a risk for serious heart problems, and are difficult to identify using existing methods. Hyperspectral imaging combines spectral- and spatial information, providing new possibilities for precise optical characterization of atherosclerotic lesions. Hyperspectral data were collected from excised aorta samples (n = 11) using both white-light and ultraviolet illumination. Single lesions (n = 42) were chosen for further investigation, and classified according to histological findings. The corresponding hyperspectral images were characterized using statistical image analysis tools (minimum noise fraction, K-means clustering, principal component analysis) and evaluation of reflectance/fluorescence spectra. Image analysis combined with histology revealed the complexity and heterogeneity of aortic plaques. Plaque features such as lipids and calcifications could be identified from the hyperspectral images. Most of the advanced lesions had a central region surrounded by an outer rim or shoulder-region of the plaque, which is considered a weak spot in vulnerable lesions. These features could be identified in both the white-light and fluorescence data. Hyperspectral imaging was shown to be a promising tool for detection and characterization of advanced atherosclerotic plaques in vitro. Hyperspectral imaging provides more diagnostic information about the heterogeneity of the lesions than conventional single point spectroscopic measurements.

  12. Parallel Implementation of Hyperspectral Image Processing Algorithms

    Microsoft Academic Search

    Antonio Plaza; David Valencia; Javier Plaza; Juan S ´ anchez-Testal; Sergio Mu; Soraya Bl

    2006-01-01

    High computing performance of algorithm analysis is essential in many hyperspectral imaging applications, including automatic target recognition for homeland defense and security, risk\\/hazard prevention and monitoring, wild-land fire tracking and biological threat detection. Despite the growing interest in hyperspectral imaging research, only a few efforts devoted to designing and implementing well-conformed parallel processing solutions currently exist in the open literature.

  13. Anomaly-Based Hyperspectral Image Compression

    Microsoft Academic Search

    Qian Du; Wei Zhu; James E. Fowler

    2008-01-01

    We propose a new lossy compression algorithm for hyperspectral images, which is based on spectral principal component analysis (PCA), followed by JPEG2000 (JP2K). The approach employs an anomaly-removal model in the compression process to preserve anomalous pixels. Results on two different hyperspectral image scenes show that the new algorithm not only provides good post-compression anomaly-detection performance but also improves rate-distortion

  14. ANOMALY-BASED HYPERSPECTRAL IMAGE COMPRESSION

    Microsoft Academic Search

    Qian Du; Wei Zhu; James E. Fowler

    2009-01-01

    We propose a new lossy compression algorithm for hyperspectral images, which is based on spectral principal component analysis (PCA), followed by JPEG2000 (JP2K). The approach employs an anomaly-removal model in the compression process to preserve anomalous pixels. Results on two different hyperspectral image scenes show that the new algorithm not only provides good post-compression anomaly-detection performance but also improves rate-

  15. Evaluation of copyright protection schemes for hyperspectral imaging

    Microsoft Academic Search

    Julia Minguillon; Jordi Herrera-Joancomarti; David Megias; Joan Serra-Sagrista

    2004-01-01

    In this paper we evaluate the performance of several image watermarking schemes applied to hyperspectral imaging. An image watermarking scheme based on JPEG2000 which can be also used to store and manipulate hyperspectral images is also described. Different watermarking schemes are tested in order to determine the suitability of each one for a specific hyperspectral image environment. The impact of

  16. Hyperspectral imaging for food processing automation

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Smith, Doug P.; Feldner, Peggy W.

    2002-11-01

    This paper presents the research results that demonstrates hyperspectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses, and potential application for real-time, on-line processing of poultry for automatic safety inspection. The hyperspectral imaging system included a line scan camera with prism-grating-prism spectrograph, fiber optic line lighting, motorized lens control, and hyperspectral image processing software. Hyperspectral image processing algorithms, specifically band ratio of dual-wavelength (565/517) images and thresholding were effective on the identification of fecal and ingesta contamination of poultry carcasses. A multispectral imaging system including a common aperture camera with three optical trim filters (515.4 nm with 8.6- nm FWHM), 566.4 nm with 8.8-nm FWHM, and 631 nm with 10.2-nm FWHM), which were selected and validated by a hyperspectral imaging system, was developed for a real-time, on-line application. A total image processing time required to perform the current multispectral images captured by a common aperture camera was approximately 251 msec or 3.99 frames/sec. A preliminary test shows that the accuracy of real-time multispectral imaging system to detect feces and ingesta on corn/soybean fed poultry carcasses was 96%. However, many false positive spots that cause system errors were also detected.

  17. Airborne Radiative Transfer Spectral Scanner: A new airborne hyperspectral imager for hyperspectral volcano observations

    Microsoft Academic Search

    T. Jitsufuchi

    2007-01-01

    In 2006, a new airborne hyperspectral imager, the Airborne Radiative Transfer Spectral Scanner (ARTS), was developed for hyperspectral volcano observations. ARTS provides hyperspectral images to support developing algorithms for the remote sensing of the geothermal distribution, the ash fall areas, and the volcanic gasses columnar content from the air. ARTS will be used mainly to assess volcanic activity and to

  18. Portable Hyperspectral Imaging Broadens Sensing Horizons

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Broadband multispectral imaging can be very helpful in showing differences in energy being radiated and is often employed by NASA satellites to monitor temperature and climate changes. In addition, hyperspectral imaging is ideal for advanced laboratory uses, biomedical imaging, forensics, counter-terrorism, skin health, food safety, and Earth imaging. Lextel Intelligence Systems, LLC, of Jackson, Mississippi purchased Photon Industries Inc., a spinoff company of NASA's Stennis Space Center and the Institute for Technology Development dedicated to developing new hyperspectral imaging technologies. Lextel has added new features to and expanded the applicability of the hyperspectral imaging systems. It has made advances in the size, usability, and cost of the instruments. The company now offers a suite of turnkey hyperspectral imaging systems based on the original NASA groundwork. It currently has four lines of hyperspectral imaging products: the EagleEye VNIR 100E, the EagleEye SWIR 100E, the EagleEye SWIR 200E, and the EagleEye UV 100E. These Lextel instruments are used worldwide for a wide variety of applications including medical, military, forensics, and food safety.

  19. Radiometric sensitivity contrast metrics for hyperspectral remote sensors

    NASA Astrophysics Data System (ADS)

    Silny, John F.; Zellinger, Lou

    2014-09-01

    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.

  20. Low-Complexity Principal Component Analysis for Hyperspectral Image Compression

    E-print Network

    Fowler, James E.

    Low-Complexity Principal Component Analysis for Hyperspectral Image Compression Qian Du and James E-detection task. Index Terms-- principal component analysis, hyperspectral image compression, JPEG2000, spectral with JPEG2000 for hyperspectral-image com- pression. However, the computational cost of determining the data

  1. Lossless Hyperspectral Image Compression Using Context-Based Conditional Averages

    Microsoft Academic Search

    Hongqiang Wang; S. Derin Babacan; Khalid Sayood

    2005-01-01

    In this paper, a new algorithm for lossless compres- sion of hyperspectral images is proposed. The spectral redundancy in hyperspectral images is exploited using a context-match method driven by the correlation between adjacent bands. This method is suitable for hyperspectral images in the band-sequential format. Moreover, this method compares favorably with the recent pro- posed lossless compression algorithms in terms

  2. Complexity-aware algorithm architecture for real-time enhancement of local anomalies in hyperspectral images

    Microsoft Academic Search

    N. Acito; S. Matteoli; M. Diani; G. Corsini

    Anomaly detection (AD) from remotely sensed multi-hyperspectral images is a powerful tool in many applications, such as strategic\\u000a surveillance and search and rescue operations. In a typical operational scenario, an airborne hyperspectral sensor searches\\u000a a wide area to identify regions that may contain potential targets. These regions typically cue higher spatial-resolution\\u000a sensors to provide target recognition and identification. While this

  3. Data system design for a hyperspectral imaging mission concept

    Microsoft Academic Search

    Christine M. Hartzell; L. C. Graham; T. S. Tao; H. R. Goldberg; J. Carpena-Nunez; D. M. Racek; C. E. Taylor; Charles D. Norton

    2009-01-01

    Global ecosystem observations are important for Earth-system studies. The National Research Council's report entitled Earth Science and Applications from Space is currently guiding NASA's Earth science missions. It calls for a global land and coastal area mapping mission. The mission, scheduled to launch in the 2013-2016 timeframe, includes a hyperspectral imager and a multi-spectral thermal-infrared sensor. These instruments will enable

  4. [Design of hyperspectral imaging system based on LCTF].

    PubMed

    Zhang, Dong-ying; Hong, Jin; Tang, Wei-ping; Yang, Wei-feng; Luo, Jun; Qiao, Yan-li; Zhang, Xie

    2008-10-01

    A new compact lightweight imaging system for hyperspectral imaging is described. The system can be thought of as the substitute for traditional mechanical filter-wheel sensor. The system is based on different techniques. It uses an electronic controlled LCTF(liquid crystal tunable filter) which provided rapid and vibrationless selection of any wavelength in the visible to IR range. The imaging system consisted of an optic lens, a CRI VariSpec LCTF and a Dalsa 1M30 camera. First the outline of this system setup is presented, then the optics designed is introduced, next the working principle of LCTF is described in details. A field experiment with the imaging system loaded on an airship was carried out and collected hyperspectral solid image. The images obtained had higher spectral and spatial resolution. Some parts of the 540-600 nm components of the 16-band image cube were also shown. Finally, the data acquired were rough processed to get reflection spectrum(from 420 to 720 nm) of three targets. It is concluded that the experiment has proved that the imaging system is effective in obtaining hyperspectral data. The image captured by the system can be applied to spectral estimation, spectra based classification and spectral based analysis. PMID:19123429

  5. Hyperspectral imager for the coastal ocean (HICO)

    Microsoft Academic Search

    T. Mosher; M. Mitchell

    2004-01-01

    The HICO sensor system, integrated in the International Space Station (ISS) Window Observational Research Facility (WORF), will collect visible and shortwave infrared hyperspectral data that will provide the following characterization of coastal regions: determine water clarity and visibility, shallow water bathymetry, and bottom type composition; detect underwater obstructions and characterize beaches and coastal areas; research global properties of coral reefs,

  6. Lossless Hyperspectral Image Compression via Linear Prediction

    Microsoft Academic Search

    Jarno Mielikainen; Pekka Toivanen

    2002-01-01

    This paper proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing residuals and entropy coding of the residuals. Our method achieved a compression ratio in

  7. Unsupervised linear unmixing of hyperspectral image for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery are often used for estimating crop yield. This paper describes an unsupervised unmixing scheme of hyperspectral images to estimate crop yield. From the hyperspectral images, the endmembers and their abundance maps are computed by unsupervised unmixing. The abu...

  8. Hyperspectral imaging of melanocytic lesions.

    PubMed

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

    2014-02-01

    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

  9. Biometric study using hyperspectral imaging during stress

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

    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.

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

    E-print Network

    Kerekes, John

    imaging and detection systems. Keywords: Hyperspectral imaging, laser illumination, landmine detection with compact hyperspectral imagers for a variety of applications, including landmine detection. By providingA compact, active hyperspectral imaging system for the detection of concealed targets Bernadette

  11. Automatic Denoising and Unmixing in Hyperspectral Image Processing

    NASA Astrophysics Data System (ADS)

    Peng, Honghong

    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.

  12. The enhanced MODIS airborne simulator hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Guerin, Daniel C.; Fisher, John; Graham, Edward R.

    2011-06-01

    The EMAS-HS or Enhanced MODIS Airborne Simulator is an upgrade to the solar reflected and thermal infrared channels of NASA's MODIS Airborne Simulator (MAS). In the solar reflected bands, the MAS scanner functionality will be augmented with the addition of this separate pushbroom hyperspectral instrument. As well as increasing the spectral resolution of MAS beyond 10 nm, this spectrometer is designed to maintain a stable calibration that can be transferred to the existing MAS sensor. The design emphasizes environmental control and on-board radiometric stability monitoring. The system is designed for high-altitude missions on the ER-2 and the Global Hawk platforms. System trades optimize performance in MODIS spectral bands that support land, cloud, aerosol, and atmospheric water studies. The primary science mission driving the development is high altitude cloud imaging, with secondary missions possible for ocean color. The sensor uses two Offner spectrometers to cover the 380-2400 nm spectral range. It features an all-reflective telescope with a 50° full field-of-view. A dichroic cold mirror will split the image from the telescope, with longer radiation transmitted to the SWIR spectrometer. The VNIR spectrometer uses a TE-cooled Si CCD detector that samples the spectrum at 2.5 nm intervals, while the SWIR spectrometer uses a Stirling-cooled hybrid HgCdTe detector to sample the spectrum at 10 nm per band. Both spectrometers will feature 1.05 mRad instantaneous fields-of-view registered to the MAS scanner IFOV's.

  13. Advanced Microslice Technologies for Hyperspectral Imaging

    E-print Network

    snapshot hyperspectral imager based on the use of advanced micro-optics technology. The system simultaneously combines high spatial multiplex (~6000 spatial pixels) with good spectral sampling (R~100) over a wavelength range 400-700nm without the need for pushbroom or wavelength scanning. We show results from

  14. Compression technique for compressed sensing hyperspectral images

    Microsoft Academic Search

    Chengfu Huo; Rong Zhang; Dong Yin

    2011-01-01

    The compressed sensing (CS) theorem is a novel sampling approach that breaks through the conventional Nyquist sampling limit and brings a revolution in the field of signal processing. This article investigates the compression technique for CS hyperspectral images so as to illustrate the superiority provided by this new theorem. First, several comparative experiments are used to reveal that the drawback

  15. Prior important band hyperspectral image compression

    Microsoft Academic Search

    Feipeng Li; Haimai Shao; Guorui Ma; Qianqing Qin; Deren Li

    2003-01-01

    This paper presents a Prior Important Band (PIB) algorithm for the compression of hyper-spectral images. The PIB method endows some of the bands with high priority so that the quality of these bands after compression is better than other bands. The rationale behind this approach is that, the bands of a data cube have different amount of information. Some bands

  16. Compression technique for compressed sensing hyperspectral images

    Microsoft Academic Search

    Chengfu Huo; Rong Zhang; Dong Yin

    2012-01-01

    The compressed sensing (CS) theorem is a novel sampling approach that breaks through the conventional Nyquist sampling limit and brings a revolution in the field of signal processing. This article investigates the compression technique for CS hyperspectral images so as to illustrate the superiority provided by this new theorem. First, several comparative experiments are used to reveal that the drawback

  17. Hyperspectral image compression through spectral clustering

    Microsoft Academic Search

    K. Siala; A. Benazza-Benyahia

    2004-01-01

    In this paper, we are interested in coding exactly and gradually hyperspectral image data. To this purpose, vector lifting schemes (VLS) are retained since they take into account the spatial and spectral redundancies in a multiresolution way. However, the high value of the number of components (some hundreds) prevents us applying directly the VLS, due to the tremendous operational complexity.

  18. Efficient Regularized LDA for Hyperspectral Image Classification

    E-print Network

    Camps-Valls, Gustavo

    rain forest tree species classification using hyperspectral data at different scales. Also exploitation in remote sensing applications, mainly focused on image classification and band selection. In Ref explanatory capabilities of LDA were exploited for profile analysis. In Ref. 12, classical LDA was used

  19. Information efficiency in hyperspectral imaging systems

    E-print Network

    Reichenbach, Stephen E.

    Information efficiency in hyperspectral imaging systems Stephen E. Reichenbach University systems, it is typically important to deliver as much information as possible about the scene radiance containing important information about a scene; however, in a system design, there are practical limitations

  20. Unsupervised hyperspectral image analysis with projection pursuit

    Microsoft Academic Search

    Agustin Ifarraguerri; Chein-I Chang

    2000-01-01

    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 \\

  1. Unsupervised data fusion for hyperspectral imaging

    Microsoft Academic Search

    Luis O. Jimenez-Rodriguez; Miguel Velez-Reyes; Jorge Rivera-Medina; Hector Velasquez

    2002-01-01

    Hyperspectral images contain a great amount of information in terms of hundreds of narrowband channels. This should lead to better parameter estimation and to more accurate classifications. However, traditional classification methods based on multispectral analysis fail to work properly on this type of data. High dimensional space poses a difficulty in obtaining accurate parameter estimates and as a consequence this

  2. Surface emissivity and temperature retrieval for a hyperspectral sensor

    SciTech Connect

    Borel, C.C.

    1998-12-01

    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.

  3. Hyperspectral Imaging of fecal contamination on chickens

    NASA Technical Reports Server (NTRS)

    2003-01-01

    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 scanning chickens during processing to help prevent contaminated food from getting to the table. ProVision is working with Sanderson Farms of Mississippi and the U.S. Department of Agriculture. ProVision has a record in its spectral library of the unique spectral signature of fecal contamination, so chickens can be scanned and those with a positive reading can be separated. HSI sensors can also determine the quantity of surface contamination. Research in this application is quite advanced, and ProVision is working on a licensing agreement for the technology. The potential for future use of this equipment in food processing and food safety is enormous.

  4. Metric Learning to Enhance Hyperspectral Image Segmentation

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    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.

  5. Unsupervised Segmentation of Hyperspectral Images Using Modified Phase Correlation

    Microsoft Academic Search

    A. Erturkerturk; S. Erturkerturk

    2006-01-01

    This letter presents hyperspectral image segmentation based on the phase-correlation measure of subsampled hyperspectral data, which is referred to as modified phase correlation. The hyperspectral spectrum of each pixel is initially subsampled to gain robustness against noise and spatial variability, and phase correlation is applied to determine spectral similarity. Similar and dissimilar pixels are decided according to the peak value

  6. Hyperspectral imaging using RGB color for foodborne pathogen detection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper reports the latest development of a color vision technique for detecting colonies of foodborne pathogens grown on agar plates with a hyperspectral image classification model that was developed using full hyperspectral data. The hyperspectral classification model depended on reflectance sp...

  7. An update on the MATLAB hyperspectral image analysis toolbox

    Microsoft Academic Search

    Samuel Rosario-Torres; Emmanuel Arzuaga-Cruz; Miguel Velez-Reyes; Luis O. Jimenez-Rodriguez

    2005-01-01

    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 of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. HIAT has been developed as part of

  8. SUPER-RESOLUTION: AN EFFICIENT METHOD TO IMPROVE SPATIAL RESOLUTION OF HYPERSPECTRAL IMAGES

    E-print Network

    Boyer, Edmond

    SUPER-RESOLUTION: AN EFFICIENT METHOD TO IMPROVE SPATIAL RESOLUTION OF HYPERSPECTRAL IMAGES A effects and sensor noise cause a degradation of the acquired image quality, making the spatial resolution to improve the spatial resolution of hypersepc- tral images [1,2]. The main drawback of all these approaches

  9. SPARSE SUPERPIXEL UNMIXING FOR EXPLORATORY ANALYSIS OF CRISM HYPERSPECTRAL IMAGES

    E-print Network

    SPARSE SUPERPIXEL UNMIXING FOR EXPLORATORY ANALYSIS OF CRISM HYPERSPECTRAL IMAGES David R. Thompson unmixing drafts mineral abundance maps with Compact Re- connaissance Imaging Spectrometer (CRISM) images. Index Terms-- Sparse Bayesian Unmixing, CRISM, Hy- perspectral Images, Superpixels, Image Segmentation 1

  10. HYPERSPECTRAL SUPER-RESOLUTION OF LOCALLY LOW RANK IMAGES FROM

    E-print Network

    Paris-Sud XI, Université de

    HYPERSPECTRAL SUPER-RESOLUTION OF LOCALLY LOW RANK IMAGES FROM COMPLEMENTARY MULTISOURCE DATA M spatial resolution multispectral images (MSI) in order to ob- tain super-resolution HSI. Most approaches techniques that fuse high spectral resolution images, such as hyperspectral images (HSI), with high spatial

  11. Infrared hyperspectral imaging for chemical vapour detection

    NASA Astrophysics Data System (ADS)

    Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.; Howle, C. R.

    2012-10-01

    Active hyperspectral imaging is a valuable tool in a wide range of applications. One such area is the detection and identification of chemicals, especially toxic chemical warfare agents, through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype midwave infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light at a range of wavelengths. While there are a number of illumination methods, the chosen configuration illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around an IR optical parametric oscillator (OPO) source with broad tunability, operating in the 2.6 to 3.7 ?m (MWIR) and 1.5 to 1.8 ?m (shortwave IR, SWIR) spectral regions. The MWIR beam was primarily used as it addressed the fundamental absorption features of the target compounds compared to the overtone and combination bands in the SWIR region, which can be less intense by more than an order of magnitude. We show that a prototype NCI instrument was able to locate hydrocarbon materials at distances up to 15 metres.

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

    PubMed Central

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

    2014-01-01

    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

  13. Research progress and perspective of hyperspectral image projectors

    NASA Astrophysics Data System (ADS)

    Kang, Li; Tang, Xiu-zhang; Xiang, Yi-huai; Huang, Yong-sheng

    2015-04-01

    As a new hyperspectral image projection technology developed in recent years, hyperspectral image projectors(HIP) provides an economical, practical and effective solution for the detection, evaluation and nonlinear calibration of hyperspectral imager. HIP, based on the spatial light modulation technology used in DMD and LCD, is capable of projecting an arbitrary spectrum into each spatial pixel to simulate a realistic scenes. We describes the concept of a generic hyperspectral image projector, and presents an overview of its applications in a number of areas. The possibilities of development direction in the future are proposed.

  14. Software for Simulation of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

    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.

  15. Wideband Hyperspectral Imaging for Space Situational Awareness

    Microsoft Academic Search

    Ian S. Robinson; A. Klier

    2006-01-01

    Wideband hyperspectral imaging (WHSI) systems collect simultaneous spectral and spatial imagery across a broad spectrum that includes the visible\\/near infrared (VNIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) regimes. These passive optical systems capture reflected sunlight and thermal emissions from targets enabling the characterization of surface material, thermal properties, propellants, and gaseous emissions when targets are sunlit

  16. Hyper-Cam automated calibration method for continuous hyperspectral imaging measurements

    NASA Astrophysics Data System (ADS)

    Gagnon, Jean-Philippe; Habte, Zewdu; George, Jacks; Farley, Vincent; Tremblay, Pierre; Chamberland, Martin; Romano, Joao; Rosario, Dalton

    2010-04-01

    The midwave and longwave infrared regions of the electromagnetic spectrum contain rich information which can be captured by hyperspectral sensors thus enabling enhanced detection of targets of interest. A continuous hyperspectral imaging measurement capability operated 24/7 over varying seasons and weather conditions permits the evaluation of hyperspectral imaging for detection of different types of targets in real world environments. Such a measurement site was built at Picatinny Arsenal under the Spectral and Polarimetric Imagery Collection Experiment (SPICE), where two Hyper-Cam hyperspectral imagers are installed at the Precision Armament Laboratory (PAL) and are operated autonomously since Fall of 2009. The Hyper-Cam are currently collecting a complete hyperspectral database that contains the MWIR and LWIR hyperspectral measurements of several targets under day, night, sunny, cloudy, foggy, rainy and snowy conditions. The Telops Hyper-Cam sensor is an imaging spectrometer that enables the spatial and spectral analysis capabilities using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320x256 pixels at spectral resolutions of up to 0.25 cm-1. The MWIR version covers the 3 to 5 ?m spectral range and the LWIR version covers the 8 to 12 ?m spectral range. This paper describes the automated operation of the two Hyper-Cam sensors being used in the SPICE data collection. The Reveal Automation Control Software (RACS) developed collaboratively between Telops, ARDEC, and ARL enables flexible operating parameters and autonomous calibration. Under the RACS software, the Hyper-Cam sensors can autonomously calibrate itself using their internal blackbody targets, and the calibration events are initiated by user defined time intervals and on internal beamsplitter temperature monitoring. The RACS software is the first software developed for COTS hyperspectal sensors that allows for full autonomous data collection capability for the user. The accuracy of the automatic calibration was characterized and is presented in this paper.

  17. Hyperspectral Image Analysis in Planetary Science and Astronomy

    NASA Astrophysics Data System (ADS)

    Merenyi, Erzsebet

    2014-01-01

    Hyperspectral images (spectral signatures acquired in hundreds of narrow, contiguous band passes on a regular spatial grid over a target area) have long been utilized in planetary astronomy for remote geochemical analyses. Typical hyperspectral imagery spans the visible to near-and-thermal-infrared wavelengths with 5-20 nm (?/?? > 100) resolution, sufficient to resolve the discriminating spectral features of (near-)surface compounds. Compared with broad-band, multi-spectral imagery, hyperspectral data brings a phase change in the complexity of spectral patterns and the cluster structure and richness of the data space, and consequently in the analysis challenges for tasks like clustering, classification, regression, and parameter inference. Many traditional favorite techniques do not meet these challenges if one’s aim is to fully exploit the rich, intricate information captured by the sensor, ensure discovery of surprising small anomalies, and more. In stellar astronomy, where Ångström resolution is typical, the data complexity can grow even higher. With the advent of 21st century observatories such as ALMA, high spatial and spectral resolution image cubes with thousands of bands are extending into new and wider wavelength domains, adding impetus to develop and deploy increasingly powerful and efficient knowledge extraction techniques. In this talk I will highlight applications of brain-like machine learning, specifically advanced forms of neural maps that mimic analogous behaviors in natural neural maps in brains (for example, preferential attention to rare signals, to enhance discovery of small clusters). I will present examples of information extraction from hyperspectral data in planetary astronomy, and point out advantages over more traditional techniques, for “precision” data mining, discovery of small anomalies in the face of highly irregular cluster structure, accurate inference of non-linearly entangled latent parameters, or non-linear dimension reduction. These works were done in close collaboration with colleagues in planetary science and astronomy, supported in part by the Applied Information Systems Research Program.

  18. Absolute Calibration Accuracy for Hyperspectral Imagers in the Solar Reflective

    NASA Technical Reports Server (NTRS)

    Thome, Kurtis

    2009-01-01

    The characterization and calibration of hyperspectral imagers is a challenging one that is expected to become even more challenging as needs increase for highly-accurate radiometric data from such systems. The preflight calibration of the Advanced Responsive Tactically Effective Military Imaging Spectrometer (ARTEMIS) is used as an example of the difficulties to calibrate hyperspectrally. Results from a preflight solar radiation-based calibration are presented with a discussion of the uncertainties in such a method including the NISI-traceable and SItraceable aspects. Expansion on the concept of solar-based calibration is given with descriptions of methods that view the solar disk directly, illuminate a solar diffuser that is part of the sensor's inflight calibration, and illuminate an external diffuser that is imaged by the sensor. The results of error analysis show that it is feasible to achieve preflight calibration using the sun as a source at the same level of uncertainty as those of lamp-based approaches. The error analysis is evaluated and verified through the solar-radiation-based calibration of several of laboratory grade radiometers. Application of these approaches to NASA's upcoming CLARREO mission are discussed including proposed methods for significantly reducing the uncertainties to allow CLARREO data to be used for climate data records.

  19. Hyperspectral and multispectral imaging for evaluating food safety and quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spectral imaging technologies have been developed rapidly during the past decade. This paper presents hyperspectral and multispectral imaging technologies in the area of food safety and quality evaluation, with an introduction, demonstration, and summarization of the spectral imaging techniques avai...

  20. Nonparametric Framework for Detecting Spectral Anomalies in Hyperspectral Images

    Microsoft Academic Search

    Tiziana Veracini; Stefania Matteoli; Marco Diani; Giovanni Corsini

    2011-01-01

    Over the past few years, hyperspectral data exploita- tion aimed at detecting spectral anomalies within remotely sensed images has been of growing interest in many applications. In this letter, we are interested in an anomaly detection (AD) scheme for hyperspectral images in which spectral anomalies are defined with respect to a statistical model of the background probability density function (PDF).

  1. Multiscale windowed denoising and segmentation of hyperspectral images

    Microsoft Academic Search

    Gökhan Bilgin; Sarp Ertürk; T. Yildirim

    2008-01-01

    This paper presents the effects of multiscale windowed denoising of spectral signatures before segmentation of hyperspectral images. In the proposed denoising approach it is intended to exploit both spectral and spatial information of the hyperspectral images by using wavelets and principal component analysis. The windowed structure incorporated for this method exploits spatial information by making use of possibly highly correlated

  2. Detection of hatching and table egg defects using hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging system was developed to detect problem hatching eggs (non-fertile or dead embryos) prior to or during early incubation and to detect table eggs with blood spots and cracked shells. All eggs were imaged using a hyperspectral camera system (wavelengths detected from 400-900mm) ...

  3. Principal component analysis for compression of hyperspectral images

    Microsoft Academic Search

    Sunghyun Lim; Kwang Hoon Sohn; Chulhee Lee

    2001-01-01

    In this paper, we explore the possibility to use the principal component analysis for compression of hyperspectral images. When the principal component analysis is applied to AVIRIS data that has 220 channels, we found that most energy is concentrated on a few eigenvalues, indicating that it may be possible to compress hyperspectral images significantly. The performance of the proposed algorithm

  4. Segmented PCA-based compression for hyperspectral image analysis

    Microsoft Academic Search

    Qian Du; Chein-I. Chang

    2004-01-01

    Hyperspectral images have high spectral resolution that helps to improve object classification. But its vast data volume also causes problems in data transmission and data storage. Since there is high correlation among spectral bands in a hyperspectral image, how to reduce the data redundancy while keeping the important information for the following data analysis is a challenging task. In this

  5. Using spectral distances for speedup in hyperspectral image processing

    Microsoft Academic Search

    S. A. Robila

    2005-01-01

    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

  6. A Hyperspectral Imaging System for Quality Detection of Pickles

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging system in simultaneous reflectance (400-675 nm) and transmittance (675-1000 nm) modes was developed for detection of hollow or bloater damage on whole pickles. Hyperspectral reflectance and transmittance images were acquired from normal and bloated whole pickle samples collec...

  7. Hyperspectral sensor calibration extrapolated from multi-spectral measurements

    Microsoft Academic Search

    James L. Keef

    2008-01-01

    Hyper-spectral (HS) sensors are the instruments of choice for remote sensing applications involving environmental monitoring, littoral survey, and military assessment. Accurate band-to-band sensor radiometric calibration is critical for successful data mining of such HS spectral sets. Current calibration is often performed with methods not necessarily developed for HS applications. This work describes two advances which facilitate laboratory source calibrations. First,

  8. MANOLAKIS, MARDEN, AND SHAW Hyperspectral Image Processing for Automatic Target Detection Applications

    E-print Network

    Salvaggio, Carl

    or activity such as a military vehicle or vehicle tracks. Hyperspectral imaging sensors, such as those illus the electromagnetic spectrum, is known as the solar spectrum. The solar energy propagates through the atmosphere of the solar spectrum affect the relationship between the observed radiance spectra and the associated

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

    Microsoft Academic Search

    Ahmed F. Elaksher

    2008-01-01

    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

  10. A way to realize the wide field of view pushbroom hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Hu, Peixin; Lu, Qimin; Cheng, Yuwei; Shu, Rong; Wang, Jianyu

    2006-01-01

    Because of long integral time and simple structure, pushbroom hyperspectal imager was paid more attentions in remote sensing field. But its field of view (FOV) is affected by the sensor so that pushbroom hyperspectral imager's work efficiency is not high. This paper describes a simple mention to enlarge FOV specially the way to mosaic two imagers. An imager with 42° FOV mosaic two imagers with 22° is introduced including the electronic system's designs and realizations. The design was introduced distribute network to solve the critical problems such as storage of huge data, the synchronization and mosaic of two sensors. The wide FOV pushbroom hyperspectral imager has a 42° FOV, 1304 spatial pixels and 124 spectral pixels. The imager has a bandwidth ranging from 400~900nm. It has been applied in the digital city plan of shanghai for water inspection and target classification.

  11. Stable Scene-based Non-uniformity Correction Coefficients for Hyperspectral SWIR Sensors

    Microsoft Academic Search

    Amber D. Fischer; Tyson J. Thomas; Robert A. Leathers; Trijntje Valerie Downes

    2007-01-01

    Scene-based non-uniformity correction (NUC) methods commonly produce artifacts as a result of NUC coefficient biasing by the specific scene content (e.g., streaking at high-contrast boundaries). We propose and evaluate a new scene-based method for computing stable non-uniformity correction coefficients for short-wavelength infrared (SWIR) scanning hyperspectral sensors relying on the spatial ratio of spectral ratios to eliminate bias from the image

  12. Reconfigurable Hardware for Compressing Hyperspectral Image Data

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    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.

  13. Hyperspectral imaging from space: Warfighter-1

    NASA Astrophysics Data System (ADS)

    Cooley, Thomas; Seigel, Gary; Thorsos, Ivan

    1999-01-01

    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.

  14. Data collection with a dual-band infrared hyperspectral imager

    Microsoft Academic Search

    Dale J. Smith; Neelam Gupta

    2005-01-01

    A novel dual-band hyperspectral imaging system has been used to collect field test data for robotics vision applications. The imaging system can collect full scene hyperspectral images in both the long wave infrared (LWIR) band (8-10.5 mum) and the mid-wave infrare (MWIR) band (4-5.25 mum) simultaneously. The imager uses a specially designed Ge diffractive lens with a dual-band 320×240 HgCdTe

  15. Differentiating Biological Colours with Few and Many Sensors: Spectral Reconstruction with RGB and Hyperspectral Cameras

    PubMed Central

    Garcia, Jair E.; Girard, Madeline B.; Kasumovic, Michael; Petersen, Phred; Wilksch, Philip A.; Dyer, Adrian G.

    2015-01-01

    Background The ability to discriminate between two similar or progressively dissimilar colours is important for many animals as it allows for accurately interpreting visual signals produced by key target stimuli or distractor information. Spectrophotometry objectively measures the spectral characteristics of these signals, but is often limited to point samples that could underestimate spectral variability within a single sample. Algorithms for RGB images and digital imaging devices with many more than three channels, hyperspectral cameras, have been recently developed to produce image spectrophotometers to recover reflectance spectra at individual pixel locations. We compare a linearised RGB and a hyperspectral camera in terms of their individual capacities to discriminate between colour targets of varying perceptual similarity for a human observer. Main Findings (1) The colour discrimination power of the RGB device is dependent on colour similarity between the samples whilst the hyperspectral device enables the reconstruction of a unique spectrum for each sampled pixel location independently from their chromatic appearance. (2) Uncertainty associated with spectral reconstruction from RGB responses results from the joint effect of metamerism and spectral variability within a single sample. Conclusion (1) RGB devices give a valuable insight into the limitations of colour discrimination with a low number of photoreceptors, as the principles involved in the interpretation of photoreceptor signals in trichromatic animals also apply to RGB camera responses. (2) The hyperspectral camera architecture provides means to explore other important aspects of colour vision like the perception of certain types of camouflage and colour constancy where multiple, narrow-band sensors increase resolution. PMID:25965264

  16. Restoration of images from an airborne unstabilized hyperspectral line scanner

    Microsoft Academic Search

    Gregory J. Power; Thomas F. Rathbun; Steven W. Worrell

    1999-01-01

    An airborne hyperspectral line scanner is used to image the ground as the aircraft moves on a single trajectory. In reality, it may be difficult for the aircraft to maintain a perfectly steady course causing distortions in the imagery. So, special subsystems including stabilizers are used to maintain the hyperspectral line scanner on the proper course. If the subsystems of

  17. Spectral Similarity Measure Edge Detection Algorithm in Hyperspectral Image

    Microsoft Academic Search

    Wenfei Luo; Liang Zhong

    2009-01-01

    Hyperspectral remote sensing is a new and fast growing remote sensing technology that currently being widely investigated by researchers and scientists. Much of hyperspectral image analysis is focused on information extraction within a single pixel. However, information about the geometrical shape can improve the capability of recognizing ground truth as different kinds of targets with similar spectral. This paper focused

  18. Classification of coastal areas by airborne hyperspectral image

    Microsoft Academic Search

    Hongjie Zhou; Zhihua Mao; Difeng Wang

    2005-01-01

    In recent years hyperspectral remote sensing has been widely used in the applications of geology agriculture forest ocean etc. This work assessed the feasibility of hyperspectral technique in coastal zone remote sensing. Data was acquired by Operational Modular Imaging Spectrometer (OMIS). Field spectrum of each class was measured and analyzed to extract certain spectral feature. We proffer a hybrid decision

  19. Sparse representation based band selection for hyperspectral images

    Microsoft Academic Search

    Shuangjiang Li; Hairong Qi

    2011-01-01

    Hyperspectral images consist of large number of spectral bands but many of which contain redundant information. Therefore, band selection has been a common practice to reduce the dimensionality of the data space for cutting down the computational cost and alleviating from the Hughes phenomenon. This paper presents a new technique for band selection where a sparse representation of the hyperspectral

  20. Compression of Hyperspectral Images with LVQ-SPECK

    Microsoft Academic Search

    Alessandro J. S. Dutra; William A. Pearlman; Eduardo A. B. Da Silva

    2008-01-01

    We discuss the use of lattice vector quantizers in conjunction with a quadtree-based sorting algorithm for the compression of multidimensional data sets, as encountered, for example, when dealing with hyperspectral imagery. An extension of the SPECK algorithm is presented that deals with vector samples and is used to encode a group of successive spectral bands extracted from the hyperspectral image

  1. Image visualization of hyperspectral spectrum for LWIR

    NASA Astrophysics Data System (ADS)

    Chong, Eugene; Jeong, Young-Su; Lee, Jai-Hoon; Park, Dong Jo; Kim, Ju Hyun

    2015-07-01

    The image visualization of a real-time hyperspectral spectrum in the long-wave infrared (LWIR) range of 900-1450 cm-1 by a color-matching function is addressed. It is well known that the absorption spectra of main toxic industrial chemical (TIC) and chemical warfare agent (CWA) clouds are detected in this spectral region. Furthermore, a significant spectral peak due to various background species and unknown targets are also present. However, those are dismissed as noise, resulting in utilization limit. Herein, we applied a color-matching function that uses the information from hyperspectral data, which is emitted from the materials and surfaces of artificial or natural backgrounds in the LWIR region. This information was used to classify and differentiate the background signals from the targeted substances, and the results were visualized as image data without additional visual equipment. The tristimulus value based visualization information can quickly identify the background species and target in real-time detection in LWIR.

  2. Multi-Channel Morphological Profiles for Classification of Hyperspectral Images Using Support Vector Machines

    PubMed Central

    Plaza, Javier; Plaza, Antonio J.; Barra, Cristina

    2009-01-01

    Hyperspectral imaging is a new remote sensing technique that generates hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. Supervised classification of hyperspectral image data sets is a challenging problem due to the limited availability of training samples (which are very difficult and costly to obtain in practice) and the extremely high dimensionality of the data. In this paper, we explore the use of multi-channel morphological profiles for feature extraction prior to classification of remotely sensed hyperspectral data sets using support vector machines (SVMs). In order to introduce multi-channel morphological transformations, which rely on ordering of pixel vectors in multidimensional space, several vector ordering strategies are investigated. A reduced implementation which builds the multi-channel morphological profile based on the first components resulting from a dimensional reduction transformation applied to the input data is also proposed. Our experimental results, conducted using three representative hyperspectral data sets collected by NASA's Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) sensor and the German Digital Airborne Imaging Spectrometer (DAIS 7915), reveal that multi-channel morphological profiles can improve single-channel morphological profiles in the task of extracting relevant features for classification of hyperspectral data using small training sets. PMID:22389595

  3. High-performance hyperspectral imaging using virtual slit optics

    NASA Astrophysics Data System (ADS)

    Behr, Bradford B.; Meade, Jeffrey T.; Hajian, Arsen R.; Cenko, Andrew T.

    2013-05-01

    The High Throughput Virtual Slit (or HTVS) is a new optical technology which can significantly increase the throughput and resolution of a dispersive spectrometer. The HTVS is able to preserve spectrometer étendue, mitigating photon losses normally associated with a slit. Originally implemented in multimode fiber-input spectrometers, HTVS has now been shown to be broadly applicable to a wide variety of spatially scanning hyperspectral imagers and standoff sensors, enhancing their performance and unlocking new application areas. In essence, the anamorphic elements of the HTVS optical system provide a means to decouple the spatial (iFOV) and spectral resolution of nearly any HSI system. In some scenarios, HTVS can be used to achieve better spectral resolution with the same input slit width. Alternatively, the slit can be widened (to increase the collected signal) while maintaining the same spectral resolution. This newfound flexibility in optimizing critical performance parameters not only improves the performance of HSI systems in existing remote sensing contexts, but also opens up numerous new application areas which were previously inaccessible to hyperspectral techniques. This method adds substantial value to existing HSI designs, particularly in applications involving targets with large spatial extent and requiring high spectral resolution (e.g. standoff Raman spectroscopy). We present recent experimental results from our prototype HTVS pushbroom imager and discuss case studies of standoff Raman detection of hazardous materials, passive detection of faint narrowband and monochromatic sources, and optimal disentangling of target spectral signatures from the solar spectrum under daytime illumination.

  4. Hyperspectral image reconstruction for diffuse optical tomography

    PubMed Central

    Larusson, Fridrik; Fantini, Sergio; Miller, Eric L.

    2011-01-01

    We explore the development and performance of algorithms for hyperspectral diffuse optical tomography (DOT) for which data from hundreds of wavelengths are collected and used to determine the concentration distribution of chromophores in the medium under investigation. An efficient method is detailed for forming the images using iterative algorithms applied to a linearized Born approximation model assuming the scattering coefficient is spatially constant and known. The L-surface framework is employed to select optimal regularization parameters for the inverse problem. We report image reconstructions using 126 wavelengths with estimation error in simulations as low as 0.05 and mean square error of experimental data of 0.18 and 0.29 for ink and dye concentrations, respectively, an improvement over reconstructions using fewer specifically chosen wavelengths. PMID:21483616

  5. Monitoring Phosphorus Content in a Tropical Estuary Lagoon using an Hyperspectral Sensor and its Application to Water Quality Modeling

    E-print Network

    Gilbes, Fernando

    1 Monitoring Phosphorus Content in a Tropical Estuary Lagoon using an Hyperspectral Sensor and its Remote Sensing, Total Phosphorus Contamination, Non-Point Source Pollution Problem and Research pollution with satellite imaging could provide important information related to the total phosphorus (TP

  6. Development of the second generation Hyperspectral Airborne Terrestrial Imager (HATI): HATI - 2500

    NASA Astrophysics Data System (ADS)

    Sandor-Leahy, S.; Thordarson, S.; Baldauf, B.; Figueroa, M.; Helmlinger, M.; Miller, H.; Reynolds, T.; Shepanski, J.

    2010-08-01

    Northrop Grumman Aerospace Systems (NGAS) has a long legacy developing and fielding hyperspectral sensors, including airborne and space based systems covering the visible through Long Wave Infrared (LWIR) wavelength ranges. Most recently NGAS has developed the Hyperspectral Airborne Terrestrial Instrument (HATI) family of hyperspectral sensors, which are compact airborne hyperspectral imagers designed to fly on a variety of platforms and be integrated with other sensors in NGAS's instrument suite. The current sensor under development is the HATI-2500, a full range Visible Near Infrared (VNIR) through Short Wave Infrared (SWIR) instrument covering the 0.4 - 2.5 micron wavelength range with high spectral resolution (3nm). The system includes a framing camera integrated with a GPS/INS to provide high-resolution multispectral imagery and precision geolocation. Its compact size and flexible acquisition parameters allow HATI-2500 to be integrated on a large variety of aerial platforms. This paper describes the HATI-2500 sensor and subsystems and its expected performance specifications.

  7. Hyperspectral imaging in diabetic foot wound care.

    PubMed

    Yudovsky, Dmitry; Nouvong, Aksone; Pilon, Laurent

    2010-09-01

    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

  8. Hyperspectral Imaging in Diabetic Foot Wound Care

    PubMed Central

    Yudovsky, Dmitry; Nouvong, Aksone; Pilon, Laurent

    2010-01-01

    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

  9. Linear mixture analysis-based compression for hyperspectral image analysis

    Microsoft Academic Search

    Qian Du; Chein-I Chang

    2004-01-01

    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,

  10. Low-bit rate exploitation-based lossy hyperspectral image compression

    Microsoft Academic Search

    Chein-I. Chang; Bharath Ramakrishna; Jing Wang; Antonio Plaza

    2010-01-01

    Hyperspectral image compression has become increasingly important in data exploitation because of enormous data volumes and high redundancy provided by hundreds of contiguous spectral channels. Since a hyperspectral image can be viewed as a 3-dimensional (3D) image cube, many efforts have been devoted to extending 2D image compression techniques to perform 3D image compression on hyperspectral image cubes. Unfortunately, some

  11. Stray light characterization of an InGaAs anamorphic hyperspectral imager.

    PubMed

    Lin, Mike; Swanson, Rand; Moon, Thomas; Smith, Casey; Kehoe, Michael; Brown, Steven W; Lykke, Keith R

    2010-08-01

    Compact hyperspectral sensors potentially have a wide range of applications, including machine vision, quality control, and surveillance from small Unmanned Aerial Vehicles (UAVs). With the development of Indium Gallium Arsenide (InGaAs) focal plane arrays, much of the Short Wave Infra-Red (SWIR) spectral regime can be accessed with a small hyperspectral imaging system, thereby substantially expanding hyperspectral sensing capabilities. To fully realize this potential, system performance must be well-understood. Here, stray light characterization of a recently-developed push-broom hyperspectral sensor sensitive in the 1 microm -1.7 microm spectral regime is described. The sensor utilizes anamorphic fore-optics that partially decouple image formation along the spatial and spectral axes of the instrument. This design benefits from a reduction in complexity over standard high-performance spectrometer optical designs while maintaining excellent aberration control and spatial and spectral distortion characteristics. The stray light performance characteristics of the anamorphic imaging spectrometer were measured using the spectral irradiance and radiance responsivity calibrations using uniform sources (SIRCUS) facility at the National Institute of Standards and Technology (NIST). A description of the measurements and results are presented. Additionally, a stray-light matrix was assembled for the instrument to improve the instrument's spectral accuracy. Transmittance of a silicon wafer was measured to validate this approach. PMID:20721136

  12. Hyperspectral imaging for safety inspection of food and agricultural products

    NASA Astrophysics Data System (ADS)

    Lu, Renfu; Chen, Yud-Ren

    1999-01-01

    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.

  13. Natural and artificial target recognition by hyperspectral remote sensing data

    Microsoft Academic Search

    Bing Zhang; Liangyun Liu; Yongchao Zhao; Genxing Xu; Lanfen Zheng; Qingxi Tong

    2002-01-01

    Recent advances in remote sensing have led the way for the development of hyperspectral sensors and the applications of the hyperspectral data. Hyperspectral remote sensing is a relatively new technology, which is currently being investigated by researchers and scientists with regard to the detection and identification of minerals, terrestrial vegetation, and man-made materials and backgrounds. The airborne hyperspectral imaging data

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

    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.

  15. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

    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.

  16. GPU implementation of JPEG2000 for hyperspectral image compression

    NASA Astrophysics Data System (ADS)

    Ciznicki, Milosz; Kurowski, Krzysztof; Plaza, Antonio

    2011-11-01

    Hyperspectral image compression has received considerable interest in recent years due to the enormous data volumes collected by imaging spectrometers for Earth Observation. JPEG2000 is an important technique for data compression which has been successfully used in the context of hyperspectral image compression, either in lossless and lossy fashion. Due to the increasing spatial, spectral and temporal resolution of remotely sensed hyperspectral data sets, fast (onboard) compression of hyperspectral data is becoming a very important and challenging objective, with the potential to reduce the limitations in the downlink connection between the Earth Observation platform and the receiving ground stations on Earth. For this purpose, implementation of hyperspectral image compression algorithms on specialized hardware devices are currently being investigated. In this paper, we develop an implementation of the JPEG2000 compression standard in commodity graphics processing units (GPUs). These hardware accelerators are characterized by their low cost and weight, and can bridge the gap towards on-board processing of remotely sensed hyperspectral data. Specifically, we develop GPU implementations of the lossless and lossy modes of JPEG2000. For the lossy mode, we investigate the utility of the compressed hyperspectral images for different compression ratios, using a standard technique for hyperspectral data exploitation such as spectral unmixing. In all cases, we investigate the speedups that can be gained by using the GPU implementations with regards to the serial implementations. Our study reveals that GPUs represent a source of computational power that is both accessible and applicable to obtaining compression results in valid response times in information extraction applications from remotely sensed hyperspectral imagery.

  17. A hyperspectral imaging prototype for online quality evaluation of pickling cucumbers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging prototype was developed for online evaluation of external and internal quality of pickling cucumbers. The prototype had several new, unique features including simultaneous reflectance and transmittance imaging and inline, real time calibration of hyperspectral images of each ...

  18. Underwater monitoring experiment using hyperspectral sensor, LiDAR and high resolution satellite imagery

    NASA Astrophysics Data System (ADS)

    Yang, Chan-Su; Kim, Sun-Hwa

    2014-10-01

    In general, hyper-spectral sensor, LiDAR and high spatial resolution satellite imagery for underwater monitoring are dependent on water clarity or water transparency that can be measured using a Secchi disk or satellite ocean color data. Optical properties in the sea waters of South Korea are influenced mainly by a strong tide and oceanic currents, diurnal, daily and seasonal variations of water transparency. The satellite-based Secchi depth (ZSD) analysis showed the applicability of hyper-spectral sensor, LiDAR and optical satellite, determined by the location connected with the local distribution of Case 1 and 2 waters. The southeast coastal areas of Jeju Island are selected as test sites for a combined underwater experiment, because those areas represent Case 1 water. Study area is a small port (<15m) in the southeast area of the island and linear underwater target used by sewage pipe is located in this area. Our experiments are as follows: 1. atmospheric and sun-glint correction methods to improve the underwater monitoring ability; 2. intercomparison of water depths obtained from three different sensors. Three sensors used here are the CASI-1500 (Wide-Array Airborne Hyperspectral VNIR Imager (0.38-1.05 microns), the Coastal Zone Mapping and Imaging Lidar (CZMIL) and Korean Multi-purpose Satellite-3 (KOMPSAT-3) with 2.8 meter multi-spectral resolution. The experimental results were affected by water clarity and surface condition, and the bathymetric results of three sensors show some differences caused by sensor-itself, bathymetric algorithm and tide level. It is shown that CASI-1500 was applicable for bathymetry and underwater target detection in this area, but KOMPSAT-3 should be improved for Case 1 water. Although this experiment was designed to compare underwater monitoring ability of LIDAR, CASI-1500, KOMPSAT-3 data, this paper was based on initial results and suggested only results about the bathymetry and underwater target detection.

  19. Exploiting spatiospectral correlation for impulse denoising in hyperspectral images

    NASA Astrophysics Data System (ADS)

    Aggarwal, Hemant Kumar; Majumdar, Angshul

    2015-01-01

    This paper proposes a technique for reducing impulse noise from corrupted hyperspectral images. We exploit the spatiospectral correlation present in hyperspectral images to sparsify the datacube. Since impulse noise is sparse, denoising is framed as an ?1-norm regularized ?1-norm data fidelity minimization problem. We derive an efficient split Bregman-based algorithm to solve the same. Experiments on real datasets show that our proposed technique, when compared with state-of-the-art denoising algorithms, yields better results.

  20. Compost quality control by hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Serranti, Silvia; D'Aniello, Laura

    2008-04-01

    Compost obtained from different organic waste sources (municipal solid waste, biomass, etc.) is more and more utilized as a relatively low-cost product suitable for agricultural purposes reducing at the same time land filling of wastes. Compost product should comply with specific characteristics in order to be competitive with other fertilizer and amendment products. Main aim of the study was to investigate the possibility offered by hyperspectral imaging to evaluate the compost quality in order to develop control strategies to be implemented at plant scale. Reflectance spectra of selected compost samples have been acquired in the visible-near infrared field (VIS-NIR): 400-1000 nm. Correlations have been established between physical-chemical characteristics of the compost products and contaminants (glass and plastic particles) and their detected reflectance spectral signature.

  1. Development of practical thermal infrared hyperspectral imaging system

    NASA Astrophysics Data System (ADS)

    Wang, Jianyu; Li, Chunlai; Lv, Gang; Yuan, Liyin; Liu, Enguang; Jin, Jian; Ji, Hongzhen

    2014-11-01

    As an optical remote sensing equipment, the thermal infrared hyperspectral imager operates in the thermal infrared spectral band and acquires about 180 wavebands in range of 8.0~12.5?m. The field of view of this imager is 13° and the spatial resolution is better than 1mrad. Its noise equivalent temperature difference (NETD) is less than 0.2K@300K(average). 1 The influence of background radiation of the thermal infrared hyperspectral imager,and a simulation model of simplified background radiation is builded. 2 The design and implementationof the Cryogenic Optics. 3 Thermal infrared focal plane array (FPA) and special dewar component for the thermal infrared hyperspectral imager. 4 Parts of test results of the thermal infrared hyperspectral imager.The hyperspectral imaging system is China's first success in developing this type of instrument, whose flight validation experiments have already been embarked on. The thermal infrared hyperspectral data acquired will play an important role in fields such as geological exploration and air pollutant identification.

  2. Detection of single graves by airborne hyperspectral imaging.

    PubMed

    Leblanc, G; Kalacska, M; Soffer, R

    2014-08-29

    Airborne hyperspectral imaging (HSI) was assessed as a potential tool to locate single grave sites. While airborne HSI has shown to be useful to locate mass graves, it is expected the location of single graves would be an order of magnitude more difficult due to the smaller size and reduced mass of the targets. Two clearings were evaluated (through a blind test) as potential sites for containing at least one set of buried remains. At no time prior to submitting the locations of the potential burial sites from the HSI were the actual locations of the sites released or shared with anyone from the analysis team. The two HSI sensors onboard the aircraft span the range of 408-2524nm. A range of indicators that exploit the narrow spectral and spatial resolutions of the two complimentary HSI sensors onboard the aircraft were calculated. Based on the co-occurrence of anomalous pixels within the expected range of the indicators three potential areas conforming to our underlying assumptions of the expected spectral responses (and spatial area) were determined. After submission of the predicted burial locations it was revealed that two of the targets were located within GPS error (10m) of the true burial locations. Furthermore, due to the history of the TPOF site for burial work, investigation of the third target is being considered in the near future. The results clearly demonstrate promise for hyperspectral imaging to aid in the detection of buried remains, however further work is required before these results can justifiably be used in routine scenarios. PMID:25447169

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

    E-print Network

    Plaza, Antonio J.

    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

  4. Directly Estimating Endmembers for Compressive Hyperspectral Images

    PubMed Central

    Xu, Hongwei; Fu, Ning; Qiao, Liyan; Peng, Xiyuan

    2015-01-01

    The large volume of hyperspectral images (HSI) generated creates huge challenges for transmission and storage, making data compression more and more important. Compressive Sensing (CS) is an effective data compression technology that shows that when a signal is sparse in some basis, only a small number of measurements are needed for exact signal recovery. Distributed CS (DCS) takes advantage of both intra- and inter- signal correlations to reduce the number of measurements needed for multichannel-signal recovery. HSI can be observed by the DCS framework to reduce the volume of data significantly. The traditional method for estimating endmembers (spectral information) first recovers the images from the compressive HSI and then estimates endmembers via the recovered images. The recovery step takes considerable time and introduces errors into the estimation step. In this paper, we propose a novel method, by designing a type of coherent measurement matrix, to estimate endmembers directly from the compressively observed HSI data via convex geometry (CG) approaches without recovering the images. Numerical simulations show that the proposed method outperforms the traditional method with better estimation speed and better (or comparable) accuracy in both noisy and noiseless cases. PMID:25905699

  5. Morphological analysis of vibrational hyperspectral imaging data.

    PubMed

    Filik, Jacob; Rutter, Abigail V; Sulé-Suso, Josep; Cinque, Gianfelice

    2012-12-21

    This study demonstrates the use of standard morphological image processing techniques to reduce the hyperspectral image data of samples, containing discrete particles or domains, to a single average spectrum per particle. The processing is automated and successful even when the particles are in contact. Focal Plane Array, Fourier transform infrared (FTIR) absorbance images of biological cells are used as an example dataset. The large number of spectra in the image (~40,000) can be intelligently averaged to ~100 mean spectra, approximately one per cell, greatly simplifying further analysis. As well as reducing the data, the morphological analysis provides useful information, such as the size of each cell, and allows every spectrum associated with each cell to be identified and analysed independently of the full dataset. Using these methods, combined with principal components analysis, consistent spectral differences are found between the spectra of the whole cells and a cell region approximately corresponding to the nucleus. These spectral differences compare well with previous IR measurements on whole CALU-1 cells and their isolated nuclei, but with a simpler sample preparation. The algorithm created to analyse the CALU-1 cells has been applied to a second cell line (NL20), which has a very different growth morphology, to demonstrate that this processing method is applicable to varied samples with little or no modification. PMID:23001149

  6. Unmixing hyperspectral images using Markov random fields

    SciTech Connect

    Eches, Olivier; Dobigeon, Nicolas; Tourneret, Jean-Yves [University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, 31071 Toulouse cedex 7 (France)

    2011-03-14

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

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

    Microsoft Academic Search

    Sam uel Rosario-Torres; Miguel Vélez-Reyes

    2009-01-01

    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

  8. Mapping coral reef benthic substrates using hyperspectral space-borne images and spectral libraries

    NASA Astrophysics Data System (ADS)

    Kutser, Tiit; Miller, Ian; Jupp, David L. B.

    2006-11-01

    The suitability of Hyperion, the first civilian hyperspectral sensor in space, for mapping coral reef benthic substrates has been investigated in this study. An image of Cairns Reef, in the northern section of the Australian Great Barrier Reef (GBR), was acquired during Hyperion Calibration and Validation activities. A field experiment was carried out on Cairns Reef to collect information about the optical properties of the water in the area and to map benthic cover by means of video transects. An approach was used to classify the Hyperion image that allows convenient mapping of benthic substrate type and water depth simultaneously. A hyperspectral library of radiance at Hyperion altitude was simulated using a spectral library of GBR benthic substrates, a Hydrolight 4.1 radiative transfer model, and an in-house atmospheric model similar to Modtran-3.7. The image was then classified using the Hyperion at-sensor radiance data and the Spectral Angle Mapper metric using the simulated at-sensor spectral library. The results suggest that using spectral libraries created with forward modelling from the sea bottom to top of the atmosphere are useful tools for interpretation of reefs and can give better results in image classification than classifying the image after removing atmospheric and water column effects. The results also suggest that bottom type and water depth can be separated and mapped simultaneously provided hyperspectral data is available.

  9. Raman Hyperspectral Imaging of Microfossils: Potential Pitfalls

    PubMed Central

    Olcott Marshall, Alison

    2013-01-01

    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

  10. Meat quality evaluation by hyperspectral imaging technique: an overview.

    PubMed

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

    2012-01-01

    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 products. The main inducement for developing the hyperspectral imaging system is to integrate both spectroscopy and imaging techniques in one system to make direct identification of different components and their spatial distribution in the tested product. By combining spatial and spectral details together, hyperspectral imaging has proved to be a promising technology for objective meat quality evaluation. The literature presented in this paper clearly reveals that hyperspectral imaging approaches have a huge potential for gaining rapid information about the chemical structure and related physical properties of all types of meat. In addition to its ability for effectively quantifying and characterizing quality attributes of some important visual features of meat such as color, quality grade, marbling, maturity, and texture, it is able to measure multiple chemical constituents simultaneously without monotonous sample preparation. Although this technology has not yet been sufficiently exploited in meat process and quality assessment, its potential is promising. Developing a quality evaluation system based on hyperspectral imaging technology to assess the meat quality parameters and to ensure its authentication would bring economical benefits to the meat industry by increasing consumer confidence in the quality of the meat products. This paper provides a detailed overview of the recently developed approaches and latest research efforts exerted in hyperspectral imaging technology developed for evaluating the quality of different meat products and the possibility of its widespread deployment. PMID:22591341

  11. Hyperspectral image unmixing over benthic habitats

    Microsoft Academic Search

    Miguel Vélez-Reyes; Samuel Rosario-Torres; James A. Goodman; Enid M. Alvira; Alexey Castrodad

    2007-01-01

    Benthic habitats are the different bottom environments as defined by distinct physical, geochemical, and biological characteristics. Hyperspectral remote sensing has great potential to map and monitor the complex dynamics associated with estuarine and nearshore benthic habitats. However, utilizing hyperspectral unmixing to map these areas requires compensating for variable bathymetry and water optical properties. In this paper, we compare two methods

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

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

    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.

  13. Low-Complexity Principal Component Analysis for Hyperspectral Image Compression

    Microsoft Academic Search

    Qian Du; James E. Fowler

    2008-01-01

    Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in conjunction with JPEG2000 for hyperspectral-image com- pression. However, the computational cost of determining the data-dependent PCA transform is high due to its traditional eigendecomposition implementation which requires calculation of a covariance matrix across the data. Several strategies

  14. Kernel Nonparametric Weighted Feature Extraction for Hyperspectral Image Classification

    Microsoft Academic Search

    Bor-Chen Kuo; Cheng-Hsuan Li; Jinn-Min Yang

    2009-01-01

    In recent years, many studies show that kernel methods are computationally efficient, robust, and stable for pattern analysis. Many kernel-based classifiers were designed and applied to classify remote-sensed data, and some results show that kernel-based classifiers have satisfying performances. Many studies about hyperspectral image classification also show that nonparametric weighted feature extraction (NWFE) is a powerful tool for extracting hyperspectral

  15. Hyperspectral image analysis using artificial color

    NASA Astrophysics Data System (ADS)

    Fu, Jian; Caulfield, H. John; Wu, Dongsheng; Tadesse, Wubishet

    2010-03-01

    By definition, HSC (HyperSpectral Camera) images are much richer in spectral data than, say, a COTS (Commercial-Off-The-Shelf) color camera. But data are not information. If we do the task right, useful information can be derived from the data in HSC images. Nature faced essentially the identical problem. The incident light is so complex spectrally that measuring it with high resolution would provide far more data than animals can handle in real time. Nature's solution was to do irreversible POCS (Projections Onto Convex Sets) to achieve huge reductions in data with minimal reduction in information. Thus we can arrange for our manmade systems to do what nature did - project the HSC image onto two or more broad, overlapping curves. The task we have undertaken in the last few years is to develop this idea that we call Artificial Color. What we report here is the use of the measured HSC image data projected onto two or three convex, overlapping, broad curves in analogy with the sensitivity curves of human cone cells. Testing two quite different HSC images in that manner produced the desired result: good discrimination or segmentation that can be done very simply and hence are likely to be doable in real time with specialized computers. Using POCS on the HSC data to reduce the processing complexity produced excellent discrimination in those two cases. For technical reasons discussed here, the figures of merit for the kind of pattern recognition we use is incommensurate with the figures of merit of conventional pattern recognition. We used some force fitting to make a comparison nevertheless, because it shows what is also obvious qualitatively. In our tasks our method works better.

  16. D Hyperspectral Frame Imager Camera Data in Photogrammetric Mosaicking

    NASA Astrophysics Data System (ADS)

    Mäkeläinen, A.; Saari, H.; Hippi, I.; Sarkeala, J.; Soukkamäki, J.

    2013-08-01

    A new 2D hyperspectral frame camera system has been developed by VTT (Technical Research Center of Finland) and Rikola Ltd. It contains frame based and very light camera with RGB-NIR sensor and it is suitable for light weight and cost effective UAV planes. MosaicMill Ltd. has converted the camera data into proper format for photogrammetric processing, and camera's geometrical accuracy and stability are evaluated to guarantee required accuracies for end user applications. MosaicMill Ltd. has also applied its' EnsoMOSAIC technology to process hyperspectral data into orthomosaics. This article describes the main steps and results on applying hyperspectral sensor in orthomosaicking. The most promising results as well as challenges in agriculture and forestry are also described.

  17. Airborne infrared hyperspectral imager for intelligence, surveillance and reconnaissance applications

    NASA Astrophysics Data System (ADS)

    Lagueux, Philippe; Puckrin, Eldon; Turcotte, Caroline S.; Gagnon, Marc-André; Bastedo, John; Farley, Vincent; Chamberland, Martin

    2012-09-01

    Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in today's warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 ?m spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a bellymounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

  18. Airborne infrared hyperspectral imager for intelligence, surveillance, and reconnaissance applications

    NASA Astrophysics Data System (ADS)

    Puckrin, Eldon; Turcotte, Caroline S.; Gagnon, Marc-André; Bastedo, John; Farley, Vincent; Chamberland, Martin

    2012-06-01

    Persistent surveillance and collection of airborne intelligence, surveillance and reconnaissance information is critical in today's warfare against terrorism. High resolution imagery in visible and infrared bands provides valuable detection capabilities based on target shapes and temperatures. However, the spectral resolution provided by a hyperspectral imager adds a spectral dimension to the measurements, leading to additional tools for detection and identification of targets, based on their spectral signature. The Telops Hyper-Cam sensor is an interferometer-based imaging system that enables the spatial and spectral analysis of targets using a single sensor. It is based on the Fourier-transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. It provides datacubes of up to 320×256 pixels at spectral resolutions as fine as 0.25 cm-1. The LWIR version covers the 8.0 to 11.8 ?m spectral range. The Hyper-Cam has been recently used for the first time in two compact airborne platforms: a belly-mounted gyro-stabilized platform and a gyro-stabilized gimbal ball. Both platforms are described in this paper, and successful results of high-altitude detection and identification of targets, including industrial plumes, and chemical spills are presented.

  19. Visible-Infrared Hyperspectral Image Projector

    NASA Technical Reports Server (NTRS)

    Bolcar, Matthew

    2013-01-01

    The VisIR HIP generates spatially-spectrally complex scenes. The generated scenes simulate real-world targets viewed by various remote sensing instruments. The VisIR HIP consists of two subsystems: a spectral engine and a spatial engine. The spectral engine generates spectrally complex uniform illumination that spans the wavelength range between 380 nm and 1,600 nm. The spatial engine generates two-dimensional gray-scale scenes. When combined, the two engines are capable of producing two-dimensional scenes with a unique spectrum at each pixel. The VisIR HIP can be used to calibrate any spectrally sensitive remote-sensing instrument. Tests were conducted on the Wide-field Imaging Interferometer Testbed at NASA s Goddard Space Flight Center. The device is a variation of the calibrated hyperspectral image projector developed by the National Institute of Standards and Technology in Gaithersburg, MD. It uses Gooch & Housego Visible and Infrared OL490 Agile Light Sources to generate arbitrary spectra. The two light sources are coupled to a digital light processing (DLP(TradeMark)) digital mirror device (DMD) that serves as the spatial engine. Scenes are displayed on the DMD synchronously with desired spectrum. Scene/spectrum combinations are displayed in rapid succession, over time intervals that are short compared to the integration time of the system under test.

  20. Lossless Hyperspectral-Image Compression Using Context-Based Conditional Average

    Microsoft Academic Search

    Hongqiang Wang; S. Derin Babacan; Khalid Sayood

    2007-01-01

    In this paper, a new algorithm for lossless compression of hyperspectral images is proposed. The spectral redundancy in hyperspectral images is exploited using a context-match method driven by the correlation between adjacent bands. This method is suitable for hyperspectral images in the band-sequential format. Moreover, this method compares favorably with the recent proposed lossless compression algorithms in terms of compression,

  1. Hyperspectral Image Compression Using Three-Dimensional Wavelet Embedded Zeroblock Coding

    Microsoft Academic Search

    WU Jia-Ji; WU Zhen-Sen; WU Cheng-Ke

    2007-01-01

    As 3D images, hyperspectral images result in large sized data sets. The storage and transmission of large volumes of hyperspectral data have become significant concerns. Therefore efficient compression is required for storage and transmission. In this paper, a new hyperspectral remote sensing image compression method based on asymmetric 3D wavelet transform and 3D set partitioning scheme is proposed. Because most

  2. Lossless compression of hyperspectral images based on 3D context prediction

    Microsoft Academic Search

    Lin Bai; Mingyi He; Yuchao Dai

    2008-01-01

    Prediction algorithms play an important role in lossless compression of hyperspectral images. However, conventional lossless compression algorithms based on prediction are usually inefficient in exploiting correlation in hyperspectral images. In this paper, a new algorithm for lossless compression of hyperspectral images based on 3D context prediction is proposed. The proposed algorithm consists of three parts to exploit the high spectral

  3. AN OPERATIONAL APPROACH FOR HYPERSPECTRAL IMAGE COMPRESSION Qian Du, Nam Ly, James E Fowler

    E-print Network

    Fowler, James E.

    AN OPERATIONAL APPROACH FOR HYPERSPECTRAL IMAGE COMPRESSION Qian Du, Nam Ly, James E Fowler. Index Terms -- hyperspectral image, compression, classification, anomaly detection. 1. INTRODUCTION superior rate-distortion performance for hyperspectral image compression. In such PCA+JPEG2000 coding, PCA

  4. Atmospheric correction of hyperspectral images based on approximate solution of transmittance equation

    NASA Astrophysics Data System (ADS)

    Belov, A. M.; Myasnikov, V. V.

    2015-02-01

    The paper presents a method of atmospheric correction of remote sensing hyperspectral images. The method based on approximate solution of MODTRAN transmittance equation using simultaneous analysis of remote sensing hyperspectral image and "ideal" hyperspectral image which is free from atmospheric distortions. Experimental results show that proposed method is applicable to perform atmospheric correction.

  5. Random projection and SVD methods in hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Jiani

    Hyperspectral imaging provides researchers with abundant information with which to study the characteristics of objects in a scene. Processing the massive hyperspectral imagery datasets in a way that efficiently provides useful information becomes an important issue. In this thesis, we consider methods which reduce the dimension of hyperspectral data while retaining as much useful information as possible. Traditional deterministic methods for low-rank approximation are not always adaptable to process huge datasets in an effective way, and therefore probabilistic methods are useful in dimension reduction of hyperspectral images. In this thesis, we begin by generally introducing the background and motivations of this work. Next, we summarize the preliminary knowledge and the applications of SVD and PCA. After these descriptions, we present a probabilistic method, randomized Singular Value Decomposition (rSVD), for the purposes of dimension reduction, compression, reconstruction, and classification of hyperspectral data. We discuss some variations of this method. These variations offer the opportunity to obtain a more accurate reconstruction of the matrix whose singular values decay gradually, to process matrices without target rank, and to obtain the rSVD with only one single pass over the original data. Moreover, we compare the method with Compressive-Projection Principle Component Analysis (CPPCA). From the numerical results, we can see that rSVD has better performance in compression and reconstruction than truncated SVD and CPPCA. We also apply rSVD to classification methods for the hyperspectral data provided by the National Geospatial-Intelligence Agency (NGA).

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

    Microsoft Academic Search

    Alessandro Barducci; Paolo Marcoionni; Ivan Pippi; Marco Poggesi

    2003-01-01

    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

  7. A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

    Microsoft Academic Search

    Miran Bürmen; Franjo Pernus; Bostjan Likar

    2010-01-01

    Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the

  8. Validation and robustness of an atmospheric correction algorithm for hyperspectral images

    Microsoft Academic Search

    Yannick Boucher; Laurent Poutier; Veronique Achard; Xavier Lenot; Christophe Miesch

    2002-01-01

    The Optics Department of ONERA has developed and implemented an inverse algorithm, COSHISE, to correct hyperspectral images of the atmosphere effects in the visible-NIR-SWIR domain (0,4-2,5 micrometers ). This algorithm automatically determine the integrated water-vapor content for each pixel, from the radiance at sensor level by using a LIRR-type (Linear Regression Ratio) technique. It then retrieves the spectral reflectance at

  9. Local Signal-Dependent Noise Variance Estimation From Hyperspectral Textural Images

    Microsoft Academic Search

    Mikhail L. Uss; Benoît Vozel; Vladimir V. Lukin; Kacem Chehdi

    2011-01-01

    A maximum-likelihood method for estimating hyper- spectral sensors random noise components, both dependent and independent from the signal, is proposed. A hyperspectral image is locally jointly processed in the spatial and spectral dimensions within a multicomponent scanning window (MSW), as small as spatial-spectral pixels. Each MSW is regarded as an additive mixture of spectrally correlated fractal Brownian motion (fBm)-samples and

  10. In vivo and in vitro hyperspectral imaging of cervical neoplasia

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Wu, Aisheng; Xiong, Xiaoxiong; Wenny, Brian

    2013-09-01

    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.

  12. An airborne pushbroom hyperspectral imager with wide field of view

    NASA Astrophysics Data System (ADS)

    Hu, Peixin; Lu, Qimin; Shu, Rong; Wang, Jianyu

    2005-12-01

    An airborne pushbroom hyperspectral imager (APHI) with wide field (42 deg. field of view) is presented. It is composed of two 22 deg. field of view (FOV) imagers and can provide 1304 pixels in spatial dimension, 124 bands in spectral dimension in one frame. APHI has a bandwidth ranging from 400 to 900 nm. The spectral resolution is 5 nm and the spatial resolution is 0.6 m at 1000-m height. The implementation of this system is helpful to overcome the restriction of FOV in pushbroom hyperspectral imaging in a more feasible way. The electronic and optical designs are also introduced in detail.

  13. Resolving Mixed Algal Species in Hyperspectral Images

    PubMed Central

    Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

    2014-01-01

    We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

  14. A fluorescence LIDAR sensor for hyper-spectral time-resolved remote sensing and mapping.

    PubMed

    Palombi, Lorenzo; Alderighi, Daniele; Cecchi, Giovanna; Raimondi, Valentina; Toci, Guido; Lognoli, David

    2013-06-17

    In this work we present a LIDAR sensor devised for the acquisition of time resolved laser induced fluorescence spectra. The gating time for the acquisition of the fluorescence spectra can be sequentially delayed in order to achieve fluorescence data that are resolved both in the spectral and temporal domains. The sensor can provide sub-nanometric spectral resolution and nanosecond time resolution. The sensor has also imaging capabilities by means of a computer-controlled motorized steering mirror featuring a biaxial angular scanning with 200 ?radiant angular resolution. The measurement can be repeated for each point of a geometric grid in order to collect a hyper-spectral time-resolved map of an extended target. PMID:23787661

  15. MULTISCALE STOCHASTIC WATERSHED FOR UNSUPERVISED HYPERSPECTRAL IMAGE SEGMENTATION

    E-print Network

    Angulo,Jesús

    MULTISCALE STOCHASTIC WATERSHED FOR UNSUPERVISED HYPERSPECTRAL IMAGE SEGMENTATION J. Angulo, S on the stochastic watershed, an approach to estimate a probability density function (pdf) of contours of an image time a multiscale framework for the computation of the pdf of contours using the stochastic watershed

  16. Textural Analysis of Hyperspectral Images for Improving Detection Accuracy

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Detection of fecal contamination is crucial for food safety to protect consumers from food pathogens. Previous studies demonstrated a hyperspectral imaging system has a potential for poultry fecal contaminant detection by measuring reflectance intensity. The simple image ratio with optimal thresho...

  17. GPU Implementation of JPEG2000 for Hyperspectral Image Compression

    E-print Network

    Plaza, Antonio J.

    GPU Implementation of JPEG2000 for Hyperspectral Image Compression Milosz Ciznickia, Krzysztof compression has received considerable interest in recent years due to the enormous data volumes collected by imaging spectrometers for Earth Observation. JPEG2000 is an important technique for data compression which

  18. Hyperspectral Imaging with Stimulated Raman Scattering by Chirped Femtosecond Lasers

    E-print Network

    Xie, Xiaoliang Sunney

    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

  19. LED lighting for use in multispectral and hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lighting for machine vision and hyperspectral imaging is an important component for collecting high quality imagery. However, it is often given minimal consideration in the overall design of an imaging system. Tungsten-halogens lamps are the most common source of illumination for broad spectrum appl...

  20. Recent Advances in Techniques for Hyperspectral Image Processing

    Microsoft Academic Search

    A. Plaza; J. A. Benediktsson; J. Boardman; J. Brazile; L. Bruzzone; G. Camps-Valls; J. Chanussot; M. Fauvel; P. Gamba; A. Gualtieri; M. Marconcini; J. C. Tilton; G. Trianni

    2007-01-01

    Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal

  1. Improved hyperspectral imaging system for fecal detection on poultry carcasses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Agricultural Research Service (ARS) has developed imaging technology to detect fecal contaminants on poultry carcasses. The hyperspectral imaging system operates from about 400 to 1000 nm, but only a few wavelengths are used in a real-time multispectral system. Recently, the upgraded system, inc...

  2. Supplemental Blue LED Lighting Array to Improve the Signal Quality in Hyperspectral Imaging of Plants

    PubMed Central

    Mahlein, Anne-Katrin; Hammersley, Simon; Oerke, Erich-Christian; Dehne, Heinz-Wilhelm; Goldbach, Heiner; Grieve, Bruce

    2015-01-01

    Hyperspectral imaging systems used in plant science or agriculture often have suboptimal signal-to-noise ratio in the blue region (400–500 nm) of the electromagnetic spectrum. Typically there are two principal reasons for this effect, the low sensitivity of the imaging sensor and the low amount of light available from the illuminating source. In plant science, the blue region contains relevant information about the physiology and the health status of a plant. We report on the improvement in sensitivity of a hyperspectral imaging system in the blue region of the spectrum by using supplemental illumination provided by an array of high brightness light emitting diodes (LEDs) with an emission peak at 470 nm. PMID:26039423

  3. Supplemental Blue LED Lighting Array to Improve the Signal Quality in Hyperspectral Imaging of Plants.

    PubMed

    Mahlein, Anne-Katrin; Hammersley, Simon; Oerke, Erich-Christian; Dehne, Heinz-Wilhelm; Goldbach, Heiner; Grieve, Bruce

    2015-01-01

    Hyperspectral imaging systems used in plant science or agriculture often have suboptimal signal-to-noise ratio in the blue region (400-500 nm) of the electromagnetic spectrum. Typically there are two principal reasons for this effect, the low sensitivity of the imaging sensor and the low amount of light available from the illuminating source. In plant science, the blue region contains relevant information about the physiology and the health status of a plant. We report on the improvement in sensitivity of a hyperspectral imaging system in the blue region of the spectrum by using supplemental illumination provided by an array of high brightness light emitting diodes (LEDs) with an emission peak at 470 nm. PMID:26039423

  4. Range-gated intensified spectrographic imager: an instrument for active hyperspectral imaging

    Microsoft Academic Search

    Jean-Robert Simard; Pierre Mathieu; Georges R. Fournier; Vincent Larochelle; Stephen K. Babey

    2000-01-01

    Hyperspectral imaging has demonstrated impressive capabilities in airborne surveys, particularly for mineral and biomass characterizations. Based on this success, it is believed that other applications like search and rescue operations, and detection\\/identification of various ground military targets could greatly benefit from this technology. The strength of hyperspectral imaging comes from the access to another dimension of information: the spectral content

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

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio

    2011-10-01

    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.

  6. High-Performance Computing in Remotely Sensed Hyperspectral Imaging: The Pixel Purity Index Algorithm as a Case Study

    Microsoft Academic Search

    Antonio Plaza; David Valencia; Javier Plaza

    2006-01-01

    The incorporation of last-generation sensors to airborne and satellite platforms is currently producing a nearly continual stream of high-dimensional data, and this explosion in the amount of collected information has rapidly created new processing challenges. For instance, hyperspectral imaging is a new technique in remote sensing that generates hundreds of spectral bands at different wavelength channels for the same area

  7. Sparse Superpixel Unmixing for Exploratory Analysis of CRISM Hyperspectral Images

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

    Fast automated analysis of hyperspectral imagery can inform observation planning and tactical decisions during planetary exploration. Products such as mineralogical maps can focus analysts' attention on areas of interest and assist data mining in large hyperspectral catalogs. In this work, sparse spectral unmixing drafts mineral abundance maps with Compact Reconnaissance Imaging Spectrometer (CRISM) images from the Mars Reconnaissance Orbiter. We demonstrate a novel "superpixel" segmentation strategy enabling efficient unmixing in an interactive session. Tests correlate automatic unmixing results based on redundant spectral libraries against hand-tuned summary products currently in use by CRISM researchers.

  8. Applying region growing algorithm to hyperspectral image for oil segmentation

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  9. Spatial-spectral method for classification of hyperspectral images.

    PubMed

    Bian, Xiaoyong; Zhang, Tianxu; Yan, Luxin; Zhang, Xiaolong; Fang, Houzhang; Liu, Hai

    2013-03-15

    Spatial-spectral approach with spatially adaptive classification of hyperspectral images is proposed. The rotation-invariant spatial texture information for each object is exploited and incorporated into the classifier by using the modified local Gabor binary pattern to distinguish different types of classes of interest. The proposed method can effectively suppress anisotropic texture in spatially separate classes as well as improve the discrimination among classes. Moreover, it becomes more robust with the within-class variation. Experimental results on the classification of three real hyperspectral remote sensing images demonstrate the effectiveness of the proposed approach. PMID:23503225

  10. [Comparison of performances in retrieving impervious surface between hyperspectral (Hyperion) and multispectral (TM/ETM+) images].

    PubMed

    Tang, Fei; Xu, Han-Qiu

    2014-04-01

    The retrieval of impervious surface is a hot topic in the remote sensing field in the past decade. Nevertheless, studies on retrieving impervious surface from hyperspectral image and the comparison of the performances in retrieving impervious surface between hyperspectral and multispectral images are rarely reported. Therefore, The present paper focuses on the characteristics of hyperspectral (EO-1 Hyperion) and multispectral (Landsat TM/ETM+) images and implements a complementary study on the comparison based on the retrieved impervious surface information between Hyperion and TM/ETM+ data. For up to 242 bands of Hyperion image, a further study was carried out to select feature bands for impervious surface retrieving using stepwise discriminant analysis. As a result, 11 feature bands were selected and a new image named Hyperion' was thus composed. The new Hyperion' image was used to investigate whether this band-reduced image could obtain higher accuracy in retrieving impervious surface. The three test regions were selected from Fuzhou, Guangzhou and Hangzhou of China, with date-coincident or nearly coincident image pairs of the used sensors. The linear spectral mixture analysis (LSMA) was employed to retrieve impervious surface and the results were accessed for their accuracy. The comparison shows that the Hyperion image has higher accuracy than TM/ETM+, and the Hyperion' composed of the selected 11 feature bands has the highest accuracy. The advantages of Hyperion in spectral and radiometric resolutions over TM/ETM+ are believed to be the main factors contributing to the higher accuracy. The high spectral and radiometric resolutions of Hyperion image allow the sensor to have higher sensitivity in distinguishing subtle spectral changes of ground objects. While, the highest accuracy the 11-band Hyperion' image achieved is owing to the significant reduction of the band dimension of the image and thus the band redundancy. PMID:25007632

  11. Development of a compressive sampling hyperspectral imager prototype

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    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".

  12. Hyperspectral imaging and quantitative analysis for prostate cancer detection

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Halig, Luma V.; Schuster, David M.; Osunkoya, Adeboye; Master, Viraj; Nieh, Peter T.; Chen, Georgia Z.; Fei, Baowei

    2012-07-01

    Hyperspectral imaging (HSI) is an emerging modality for various medical applications. Its spectroscopic data might be able to be used to noninvasively detect cancer. Quantitative analysis is often necessary in order to differentiate healthy from diseased tissue. We propose the use of an advanced image processing and classification method in order to analyze hyperspectral image data for prostate cancer detection. The spectral signatures were extracted and evaluated in both cancerous and normal tissue. Least squares support vector machines were developed and evaluated for classifying hyperspectral data in order to enhance the detection of cancer tissue. This method was used to detect prostate cancer in tumor-bearing mice and on pathology slides. Spatially resolved images were created to highlight the differences of the reflectance properties of cancer versus those of normal tissue. Preliminary results with 11 mice showed that the sensitivity and specificity of the hyperspectral image classification method are 92.8% to 2.0% and 96.9% to 1.3%, respectively. Therefore, this imaging method may be able to help physicians to dissect malignant regions with a safe margin and to evaluate the tumor bed after resection. This pilot study may lead to advances in the optical diagnosis of prostate cancer using HSI technology.

  13. Hyperspectral image classification based on volumetric texture and dimensionality reduction

    NASA Astrophysics Data System (ADS)

    Su, Hongjun; Sheng, Yehua; Du, Peijun; Chen, Chen; Liu, Kui

    2015-06-01

    A novel approach using volumetric texture and reduced-spectral features is presented for hyperspectral image classification. Using this approach, the volumetric textural features were extracted by volumetric gray-level co-occurrence matrices (VGLCM). The spectral features were extracted by minimum estimated abundance covariance (MEAC) and linear prediction (LP)-based band selection, and a semi-supervised k-means (SKM) clustering method with deleting the worst cluster (SKMd) bandclustering algorithms. Moreover, four feature combination schemes were designed for hyperspectral image classification by using spectral and textural features. It has been proven that the proposed method using VGLCM outperforms the gray-level co-occurrence matrices (GLCM) method, and the experimental results indicate that the combination of spectral information with volumetric textural features leads to an improved classification performance in hyperspectral imagery.

  14. Fast, electrically tunable filters for hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Liberman, V.; Parameswaran, L.; Gear, C.; Cabral, A.; Rothschild, M.

    2014-06-01

    Tunable, narrow-wavelength spectral filters with a ms response in the mid-wave/long-wave infrared (MW/LWIR) are an enabling technology for hyperspectral imaging systems. Few commercial off-the-shelf (COTS) components for this application exist, including filter wheels, movable gratings, and Fabry-Perot (FP) etalon-based devices. These devices can be bulky, fragile and often do not have the required response speed. Here, we present a fundamentally different approach for tunable reflective IR filters, based on coupling subwavelength plasmonic antenna arrays with liquid crystals (LCs). Our device operates in reflective mode and derives its narrow bandwidth from diffractive coupling of individual antenna elements. The wavelength tunability of the device arises from electrically-induced re-orientation of the LC material in intimate contact with antenna array. This re-orientation, in turn, induces a change in the local dielectric environment of the antenna array, leading to a wavelength shift. We will first present results of full-field optimization of micron-size antenna geometries to account for complex 3D LC anisotropy. We have fabricated these antenna arrays on IR-transparent CaF2 substrates utilizing electron beam lithography, and have demonstrated tunability using 5CB, a commercially available LC. However, the design can be extended to high-birefringence liquid crystals for an increased tuning range. Our initial results demonstrate <60% peak reflectance in the 4- 6 ?m wavelength range with a tunability of 0.2 ?m with re-orientation of the surface alignment layers. Preliminary electrical switching has been demonstrated and is being optimized.

  15. Restoration of images from an airborne unstabilized hyperspectral line scanner

    NASA Astrophysics Data System (ADS)

    Power, Gregory J.; Rathbun, Thomas F.; Worrell, Steven W.

    1999-07-01

    An airborne hyperspectral line scanner is used to image the ground as the aircraft moves on a single trajectory. In reality, it may be difficult for the aircraft to maintain a perfectly steady course causing distortions in the imagery. So, special subsystems including stabilizers are used to maintain the hyperspectral line scanner on the proper course. If the subsystems of an airborne hyperspectral line scanner are malfunctioning or if the proper stabilizers are not available, then a technique is needed to restore the imagery. It no stabilizers are used on the airborne line scanner, but if aircraft navigation information is available including yaw, pitch and roll, then the restoration may be automated. However, if the stabilizers are malfunctioning or if the navigation information is corrupted or unavailable, then a technique is needed to restore the imagery. This paper introduces an automated technique for restoring hyperspectral images that was used on some images obtained for the Dynamic Data Base program sponsored by the Defense Advanced Research Projects Agency. The automated approach is based on image flow vectors obtained from the unstable image. The approach is introduced along with results that demonstrate how successful the restoration is at the feature level.

  16. Signal processing algorithms for staring single pixel hyperspectral sensors

    NASA Astrophysics Data System (ADS)

    Manolakis, Dimitris; Rossacci, Michael; O'Donnell, Erin; D'Amico, Francis M.

    2006-08-01

    Remote sensing of chemical warfare agents (CWA) with stand-off hyperspectral sensors has a wide range of civilian and military applications. These sensors exploit the spectral changes in the ambient photon flux produced thermal emission or absorption after passage through a region containing the CWA cloud. In this work we focus on (a) staring single-pixel sensors that sample their field of view at regular intervals of time to produce a time series of spectra and (b) scanning single or multiple pixel sensors that sample their FOV as they scan. The main objective of signal processing algorithms is to determine if and when a CWA enters the FOV of the sensor. We shall first develop and evaluate algorithms for staring sensors following two different approaches. First, we will assume that no threat information is available and we design an adaptive anomaly detection algorithm to detect a statistically-significant change in the observed spectrum. The algorithm processes the observed spectra sequentially-in-time, estimates adaptively the background, and checks whether the next spectrum differs significantly from the background based on the Mahalanobis distance or the distance from the background subspace. In the second approach, we will assume that we know the spectral signature of the CWA and develop sequential-in-time adaptive matched filter detectors. In both cases, we assume that the sensor starts its operation before the release of the CWA; otherwise, staring at a nearby CWA-free area is required for background estimation. Experimental evaluation and comparison of the proposed algorithms is accomplished using data from a long-wave infrared (LWIR) Fourier transform spectrometer.

  17. Hyperspectral image analysis for plant stress detection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abiotic and disease-induced stress significantly reduces plant productivity. Automated on-the-go mapping of plant stress allows timely intervention and mitigating of the problem before critical thresholds are exceeded, thereby, maximizing productivity. A hyperspectral camera analyzed the spectral ...

  18. A Multiobjective Evolutionary Algorithm for Hyperspectral Image Watermarking

    Microsoft Academic Search

    D. Sal; M. Graña

    With the increasing availability of internet access to remote sensing imagery, the concern with image authentication and ownership\\u000a issues is growing in the remote sensing community. Watermarking techniques help to solve the problems raised by this issue.\\u000a In this paper we elaborate on the proposition of an optimal placement of the watermark image in a hyperspectral image. We\\u000a propose an

  19. A short wave infrared hyperspectral imager for landmine detection

    Microsoft Academic Search

    John E. McFee; Steve Achal; Tyler Ivanco; Cliff Anger

    2005-01-01

    DRDC Suffield and Itres Research have jointly investigated the use of visible and infrared hyperspectral imaging for landmine detection since 1988. There has been considerable success detecting surface-laid landmines by classification of their visible\\/near infrared (VNIR - 400 to 1000 nm wavelength) spectral signatures, but it has not been possible to find VNIR spectral characteristics that would generically distinguish anthropogenic

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral fluorescence imaging system was developed and used to obtain several two-waveband spectral ratios on leafy green vegetables, represented by romaine lettuce and baby spinach in this study. The ratios were analyzed to determine the proper one for detecting bovine fecal contamination on...

  1. Classification of Fecal Contamination on Leafy Greens by Hyperspectral Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral fluorescence imaging system was developed and used to obtain several two-waveband spectral ratios on leafy green vegetables, represented by romaine lettuce and baby spinach in this study. The ratios were analyzed to determine the proper one for detecting bovine fecal contamination on...

  2. Distributive segmented PCA: A novel approach to hyperspectral image compression

    Microsoft Academic Search

    Syeda Narjis Fatima; Naveed Ahmed Abbasi

    2012-01-01

    We propose a segmented PCA based distributed framework exploiting the high correlation and dimensionality reduction properties of PCA in conjugation with the distributed source coding paradigm for onboard hyperspectral image compression. The hybrid scheme deploying Lossy Wyner Ziv coding in conjunction with statistically segmented PCA strategy exploits the two fold intra group and inter group correlation for establishment of multiple

  3. Distributive segmented PCA: A novel approach to hyperspectral image compression

    Microsoft Academic Search

    Abbasi Naveed Ahmed; Fatima Syeda Narjis

    2011-01-01

    We propose a segmented PCA based distributed framework exploiting the high correlation and dimensionality reduction properties of PCA in conjugation with the distributed source coding paradigm for onboard hyperspectral image compression. The hybrid scheme deploying Lossy Wyner Ziv coding in conjunction with statistically segmented PCA strategy exploits the two fold intra group and inter group correlation for establishment of multiple

  4. AOTF hyperspectral microscope imaging for foodborne pathogenic bacteria detection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral information, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmonella enteritidi...

  5. Hyperspectral Imaging for Detecting Pathogens Grown on Agar Plates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  6. Noise Removal From Hyperspectral Images by Multidimensional Filtering

    Microsoft Academic Search

    Damien Letexier; Salah Bourennane

    2008-01-01

    A generalized multidimensional Wiener filter for denoising is adapted to hyperspectral images (HSIs). Commonly, multidimensional data filtering is based on data vectorization or matricization. Few new approaches have been proposed to deal with multidimensional data. Multidimensional Wiener filtering (MWF) is one of these techniques. It considers a multidimensional data set as a third-order tensor. It also relies on the separability

  7. Hyperspectral image cube compression combining JPEG2000 and spectral decorrelation

    Microsoft Academic Search

    H. S. Lee; N. H. Younan; R. L. King

    2002-01-01

    In this paper, a combined JPEG-2000 and spectral correlation method for hyperspectral image compression is presented. This compression scheme shows promising results. Also, various spectral decorrelation techniques are compared. The decorrelation using Karhunen-Loeve transform performs the best in terms of PSNR gain. But, since it is computationally expensive, there is no much gain over discrete cosine transform.

  8. Design of spectral channels for hyperspectral image classification

    Microsoft Academic Search

    Sebastiano B. Serpico; M. D'Inca; G. Moser

    2004-01-01

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

  9. Hyperspectral Imaging Technologies for Nondestructive Agro-Food Evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the past decade, researchers at the Agricultural Research Service (ARS), United States Department of Agriculture (USDA), have developed several versions of line-scan-based hyperspectral imaging systems capable of both visible to near-infrared reflectance and fluorescence methods. These line-s...

  10. Recent Advances in Techniques for Hyperspectral Image Processing

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; Benediktsson, Jon Atli; Boardman, Joseph W.; Brazile, Jason; Bruzzone, Lorenzo; Camps-Valls, Gustavo; Chanussot, Jocelyn; Fauvel, Mathieu; Gamba, Paolo; Gualtieri, Anthony; Marconcini, Mattia; Tilton, James C.; Trianni, Giovanna

    2009-01-01

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

  11. Methodology for hyperspectral image classification using novel neural network

    SciTech Connect

    Subramanian, S., Gat, N., Sheffield, M., [Opto-Knowledge, Systems, Inc., Manhattan Beach, CA (United States); Barhen, J. [Oak Ridge National Lab., TN (United States); Toomarian, N. [Jet Propulsion Laboratory, Pasadena, CA (United States)

    1997-04-01

    A novel feed forward neural network is used to classify hyperspectral data from the AVIRIS sector. The network applies an alternating direction singular value decomposition technique to achieve rapid training times (few seconds per class). Very few samples (10-12) are required for training. 100% accurate classification is obtained using test data sets. The methodology combines this rapid training neural network together with data reduction and maximal feature separation techniques such as principal component analysis and simultaneous diagonalization of covariance matrices, for rapid and accurate classification of large hyperspectral images. The results are compared to those of standard statistical classifiers. 21 refs., 3 figs., 5 tabs.

  12. Detecting leafy spurge in native grassland using hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Kloppenburg, Catherine

    Leafy spurge (Euphoria esula L.) is a perennial noxious weed that has been encroaches on the native grassland regions of North America resulting in biological and economic impacts. Leafy spurge growth is most prevalent along river banks and in pasture areas. Due to poor accessibility and the cost and labour associated with data collection, estimates of number and size of leafy spurge infestations is poor. Remote sensing has the ability to cover large areas, providing an alternate means to ground surveys and will allow for the capability to create an accurate baseline of infestations. Airborne hyperspectral data were collected over the two test sites selected on the Blood Reserve in Southern Alberta using a combined Airborne Imaging Spectrometer for different Applications (AISA) Eagle and Hawk sensor systems in July, 2010. This study used advanced analysis tools, including spectral mixture analysis, spectral angle mapper and mixture-tuned matched filter techniques to evaluate the ability to detect leafy spurge patches. The results show that patches of leafy spurge with flowering stem density >40 stems m-2 were identified with 85 % accuracy while identification of lower density stems were less accurate (10 - 40 %). The results are promising with respect to quantifying areas of significant leafy spurge infestation and targeting biological control and potential insect release sites.

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

    Microsoft Academic Search

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

    2007-01-01

    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

  14. Detection of camouflaged targets using hyperspectral imaging technology

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    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.

  15. Detecting citrus canker by hyperspectral reflectance imaging and PCA-based image classification method

    NASA Astrophysics Data System (ADS)

    Qin, Jianwei; Burks, Thomas F.; Kim, Moon S.; Chao, Kuanglin; Ritenour, Mark A.

    2008-04-01

    Citrus canker is one of the most devastating diseases that threaten citrus crops. Technologies that can efficiently identify citrus canker would assure fruit quality and safety and enhance the competitiveness and profitability of the citrus industry. This research was aimed to investigate the potential of using hyperspectral imaging technique for detecting canker lesions on citrus fruit. A portable hyperspectral imaging system consisting of an automatic sample handling unit, a light source, and a hyperspectral imaging unit was developed for citrus canker detection. The imaging system was used to acquire reflectance images from citrus samples in the wavelength range between 400 nm and 900 nm. Ruby Red grapefruits with normal and various diseased skin conditions including canker, copper burn, greasy spot, wind scar, cake melanose, and specular melanose were tested. Hyperspectral reflectance images were analyzed using principal component analysis (PCA) to compress the 3-D hyperspectral image data and extract useful image features that could be used to discriminate cankerous samples from normal and other diseased samples. Image processing and classification algorithms were developed based upon the transformed images of PCA. The overall accuracy for canker detection was 92.7%. This research demonstrated that hyperspectral imaging technique could be used for discriminating citrus canker from other confounding diseases.

  16. Hyperspectral Reflectance Signatures and Point Clouds for Precision Agriculture by Light Weight Uav Imaging System

    NASA Astrophysics Data System (ADS)

    Honkavaara, E.; Kaivosoja, J.; Mäkynen, J.; Pellikka, I.; Pesonen, L.; Saari, H.; Salo, H.; Hakala, T.; Marklelin, L.; Rosnell, T.

    2012-07-01

    The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.

  17. Real-time implementation of optimized maximum noise fraction transform for feature extraction of hyperspectral images

    NASA Astrophysics Data System (ADS)

    Wu, Yuanfeng; Gao, Lianru; Zhang, Bing; Zhao, Haina; Li, Jun

    2014-01-01

    We present a parallel implementation of the optimized maximum noise fraction (G-OMNF) transform algorithm for feature extraction of hyperspectral images on commodity graphics processing units (GPUs). The proposed approach explored the algorithm data-level concurrency and optimized the computing flow. We first defined a three-dimensional grid, in which each thread calculates a sub-block data to easily facilitate the spatial and spectral neighborhood data searches in noise estimation, which is one of the most important steps involved in OMNF. Then, we optimized the processing flow and computed the noise covariance matrix before computing the image covariance matrix to reduce the original hyperspectral image data transmission. These optimization strategies can greatly improve the computing efficiency and can be applied to other feature extraction algorithms. The proposed parallel feature extraction algorithm was implemented on an Nvidia Tesla GPU using the compute unified device architecture and basic linear algebra subroutines library. Through the experiments on several real hyperspectral images, our GPU parallel implementation provides a significant speedup of the algorithm compared with the CPU implementation, especially for highly data parallelizable and arithmetically intensive algorithm parts, such as noise estimation. In order to further evaluate the effectiveness of G-OMNF, we used two different applications: spectral unmixing and classification for evaluation. Considering the sensor scanning rate and the data acquisition time, the proposed parallel implementation met the on-board real-time feature extraction.

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

    PubMed

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

    2012-11-30

    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

  19. A thermal infrared hyperspectral imager (tasi) for buried landmine detection

    Microsoft Academic Search

    Steve Achal; John E. McFee; Tyler Ivanco; Cliff Anger

    2007-01-01

    DRDC Suffeld and Itres Research have collaborated to investigate the use of hyperspectral imaging (HSI) for surface and buried landmine detection since 1989. Visible\\/near infrared (casi) and short wave infrared (sasi) families of imagers have been developed which have demonstrated reliable HSI detection of surface-laid mines, based on their reflectance spectra, from airborne and ground-based platforms. However, they have limited

  20. Hyperspectral Image Compression Employing a Model of Anomalous Pixels

    Microsoft Academic Search

    Barbara Penna; Tammam Tillo; Enrico Magli; Gabriella Olmo

    2007-01-01

    We propose a new lossy compression algorithm for hyperspectral images, which is based on the spectral Karhunen-Loeve transform, followed by spatial JPEG 2000, which employs a model of anomalous pixels during the compression process. Results on Airborne Visible\\/Infrared Imaging Spectrometer scenes show that the new algorithm provides better rate-distortion performance, as well as improved anomaly detection performance, with respect to

  1. Hyperspectral image lossless compression using DSC and 2-D CALIC

    Microsoft Academic Search

    Xueping Yan; Jiaji Wu

    2010-01-01

    In recent few years, DSC (Distributed Source Coding) technology is catched much attentions in remote sensing image compression field,due to its excellent performance and low encoding complexity. In this paper, we propose a DSC-based practical solution for hyperspectral image lossless compression system, which applies the DSC technique using the power channel codes of Low-Density-Parity-Check Accumulated(LDPCA) codes and incorporates an efficient

  2. Hyperspectral image compression using SPIHT based on DCT and DWT

    Microsoft Academic Search

    Haiping Wei; Baojun Zhao; Peikun He

    2007-01-01

    In this paper, an algorithm for hyperspectral image compression is presented. It carries DCT (Discrete Cosine Transform) on spectral bands to exploit the spectral correlation and then DWT (Discrete Wavelet Transform) on every eigen image to exploit the spatial correlation. After that, 3D-SPIHT (three-dimensional Set Partitioning in Hierarchical Trees) is performed for encoding. Experiments were done on the OMIS-I (Operational

  3. Integration of PCA and JPEG2000 for hyperspectral image compression

    Microsoft Academic Search

    Qian Du; Wei Zhu

    2007-01-01

    In this paper, we report our recent investigation on principal components analysis (PCA) and JPEG2000 in hyperspectral image compression, where the PCA is for spectral coding and JPEG2000 is for spatial coding for principal component (PC) images (referred to as PCA+JP2K). We find out such an integrated scheme significantly outperforms the commonly used 3-dimensional (3D) JPEG2000 (3D-JP2K) in rate-distortion performance,

  4. Hyperspectral imaging of bruises in the SWIR spectral region

    NASA Astrophysics Data System (ADS)

    Randeberg, Lise L.; Hernandez-Palacios, Julio

    2012-02-01

    Optical diagnostics of bruised skin might provide important information for characterization and age determination of such injuries. Hyperspectral imaging is one of the optical techniques that have been employed for bruise characterization. This technique combines high spatial and spectral resolution and makes it possible to study both chromophore signatures and -distributions in an injury. Imaging and spectroscopy in the visible spectral range have resulted in increased knowledge about skin bruises. So far the SWIR region has not been explored for this application. The main objective of the current study was to characterize bruises in the SWIR wavelength range. Hyperspectral images in the SWIR (950-2500nm ) and VNIR (400-850nm) spectral range were collected from 3 adult volunteers with bruises of known age. Data were collected over a period of 8 days. The data were analyzed using spectroscopic techniques and statistical image analysis. Preliminary results from the pilot study indicate that SWIR hyperspectral imaging might be an important supplement to imaging in the visible part of the spectrum. The technique emphasizes local edema and gives a possibility to visualize features that cannot easily be seen in the visible part of the spectrum.

  5. Recent developments in hyperspectral imaging for assessment of food quality and safety.

    PubMed

    Huang, Hui; Liu, Li; Ngadi, Michael O

    2014-01-01

    Hyperspectral imaging which combines imaging and spectroscopic technology is rapidly gaining ground as a non-destructive, real-time detection tool for food quality and safety assessment. Hyperspectral imaging could be used to simultaneously obtain large amounts of spatial and spectral information on the objects being studied. This paper provides a comprehensive review on the recent development of hyperspectral imaging applications in food and food products. The potential and future work of hyperspectral imaging for food quality and safety control is also discussed. PMID:24759119

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

    PubMed Central

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

    2014-01-01

    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. PMID:25426272

  7. SUPER-RESOLUTION OF HYPERSPECTRAL IMAGES USING LOCAL SPECTRAL G. Licciardi1

    E-print Network

    Paris-Sud XI, Université de

    SUPER-RESOLUTION OF HYPERSPECTRAL IMAGES USING LOCAL SPECTRAL UNMIXING G. Licciardi1 , M sensing applications it is preferable to have images with both high spectral and spatial resolutions hyperspectral images with high spa- tial resolution multispectral images in order to obtain super- resolution

  8. Identification of unknown waste sites using MIVIS hyperspectral images

    SciTech Connect

    Gomarasca, M.A.; Strobelt, S. [National Research Council, Milano (Italy)

    1996-11-01

    This paper presents the results on the individuation of known and unknown (illegal) waste sites using Landsat TM satellite imagery and airborne MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) data for detailed analysis in Italy. Previous results with Landsat TM imagery were partially positive for large waste site identification and negative for small sites. Information acquired by the MIVIS hyperspectral system presents three main characteristics: local scale study, possibility to plan the proper period based on the objectives of the study, high number of spectral bands with high spectral and geometrical resolution. MIVIS airborne shootings were carried out on 7 July 1994 at noon with 4x4 m pixel resolution. The MIVIS 102 bands` sensors can distinguish even objects with similar spectral behavior, thanks to its high spectral resolution. Identification of degraded sites is obtained using traditional spectral and statistical operators (NDVI, Principal Component Analysis, Maximum Likelihood classifier) and innovative combination of filtered band ratios realized to extract specific waste elements (acid slimes or contaminated soils). One of the aims that concerns with this study is the definition of an operative program for the characterization, identification and classification of defined categories of waste disposal sites. The best schedule for the data collection by airborne MIVIS oriented to this target is defined. The planning of the proper flight, based on the waste sites features, is important to optimize this technology. One of the most efficient methods for detecting hidden waste sites is the thermal inertia so two images are necessary: one during low sun load and one with high sun load. The results obtained are operationally useful and winning. This instrument, supported by correct analysis techniques, may offer new interesting prospects in territorial management and environmental monitoring. 5 refs., 5 figs., 1 tab.

  9. Hyperspectral imaging for detection of cholesterol in human skin

    NASA Astrophysics Data System (ADS)

    Milani?, Matija; Bjorgan, Asgeir; Larsson, Marcus; Marraccini, Paolo; Strömberg, Tomas; Randeberg, Lise L.

    2015-03-01

    Hypercholesterolemia is characterized by high levels of cholesterol in the blood and is associated with an increased risk of atherosclerosis and coronary heart disease. Early detection of hypercholesterolemia is necessary to prevent onset and progress of cardiovascular disease. Optical imaging techniques might have a potential for early diagnosis and monitoring of hypercholesterolemia. In this study, hyperspectral imaging was investigated for this application. The main aim of the study was to identify spectral and spatial characteristics that can aid identification of hypercholesterolemia in facial skin. The first part of the study involved a numerical simulation of human skin affected by hypercholesterolemia. A literature survey was performed to identify characteristic morphological and physiological parameters. Realistic models were prepared and Monte Carlo simulations were performed to obtain hyperspectral images. Based on the simulations optimal wavelength regions for differentiation between normal and cholesterol rich skin were identified. Minimum Noise Fraction transformation (MNF) was used for analysis. In the second part of the study, the simulations were verified by a clinical study involving volunteers with elevated and normal levels of cholesterol. The faces of the volunteers were scanned by a hyperspectral camera covering the spectral range between 400 nm and 720 nm, and characteristic spectral features of the affected skin were identified. Processing of the images was done after conversion to reflectance and masking of the images. The identified features were compared to the known cholesterol levels of the subjects. The results of this study demonstrate that hyperspectral imaging of facial skin can be a promising, rapid modality for detection of hypercholesterolemia.

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

    NASA Astrophysics Data System (ADS)

    Dierssen, Heidi M.

    2013-09-01

    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.

  11. Anomaly detection and classification for hyperspectral imagery

    Microsoft Academic Search

    Chein-I. Chang; Shao-Shan Chiang

    2002-01-01

    Anomaly detection becomes increasingly important in hyperspectral image analysis, since hyperspectral imagers can now uncover many material substances which were previously unresolved by multispectral sensors. Two types of anomaly detection are of interest and considered in this paper. One was previously developed by Reed and Yu to detect targets whose signatures are distinct from their surroundings. Another was designed to

  12. Hyperspectral image classification based on NMF Features Selection Method

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  13. Real-time airborne hyperspectral imaging of land mines

    NASA Astrophysics Data System (ADS)

    Ivanco, Tyler; Achal, Steve; McFee, John E.; Anger, Cliff; Young, Jane

    2007-04-01

    DRDC Suffeld and Itres Research have jointly investigated the use of visible and infrared hyperspectral imaging (HSI) for surface and buried land mine detection since 1989. These studies have demonstrated reliable passive HSI detection of surface-laid mines, based on their reflectance spectra, from airborne and ground-based platforms. Commercial HSI instruments collect and store image data at aircraft speeds, but the data are analysed off- line. This is useful for humanitarian demining, but unacceptable for military countermine operations. We have developed a hardware and software system with algorithms that can process the raw hyperspectral data in real time to detect mines. The custom algorithms perform radiometric correction of the raw data, then classify pixels of the corrected data, referencing a spectral signature library. The classification results are stored and displayed in real time, that is, within a few frame times of the data acquisition. Such real-time mine detection was demonstrated for the first time from a slowly moving land vehicle in March 2000. This paper describes an improved system which can achieve real-time detection of mines from an airborne platform, with its commensurately higher data rates. The system is presently compatible with the Itres family of visible/near infrared, short wave infrared and thermal infrared pushbroom hyperspectral imagers and its broadband thermal infrared pushbroom imager. Experiments to detect mines from an airborne platform in real time were conducted at DRDC Suffield in November 2006. Surface-laid land mines were detected in real time from a slowly moving helicopter with generally good detection rates and low false alarm rates. To the authors' knowledge, this is the first time that land mines have been detected from an airborne platform in real time using hyperspectral imaging.

  14. Application of decorrelation stretching method to hyperspectral fundus image processing

    NASA Astrophysics Data System (ADS)

    Nagaoka, T.; Nakamura, A.; Aizawa, K.; Kanazawa, M.; Kezuka, T.; Miura, M.; Usui, M.; Ohtsubo, S.; Sota, T.

    2007-02-01

    We have developed a near-infrared hyperspectral imaging system that can acquire both spectral and spatial data covering a 50-degree field at the fundus surface within 5 seconds. Single wavelength band reflectance images with bandwidth of 20 nm have demonstrated that choroidal vascular patterns can be clearly observed as bright images for the central wavelength ranging from 740 to 860 nm, while retinal blood vessels are seen as dark images for that ranging from 740 to 920 nm. It is desirable for clinical use to separate the choroidal vascular patterns image from the retinal blood vessels image. To this end, we have applied the decorrelation stretch to processing of spectral images. We have found the following. Original fundus spectral images have stripes noise. The decorrelation stretch emphasizes the noise and, thus, the noise has to be removed by, for example, DCT (Discrete Cosine Transform) filter beforehand. The choroidal vascular image can be successfully separated from the retinal vascular image. Furthermore, the macular is superimposed on the latter as it should be so from the viewpoint of anatomy. The result suggests that useful information may be extracted by combining hyperspectral images with the decorrelation stretch.

  15. Making digital phantoms with spectral and spatial light modulators for quantitative applications of hyperspectral optical medical imaging devices

    NASA Astrophysics Data System (ADS)

    Chon, Bonghwan; Tokumasu, Fuyuki; Lee, Ji Youn; Allen, David W.; Rice, Joseph P.; Hwang, Jeeseong

    2015-03-01

    We present a procedure to generate digital phantoms with a hyperspectral image projector (HIP) consisting of two liquid crystal on silicon (LCoS) spatial light modulators (SLMs). The digital phantoms are 3D image data cubes of the spatial distribution of spectrally resolved abundances of intracellular light-absorbing oxy-hemoglobin molecules in single erythrocytes. Spectrally and spatially resolved image data indistinguishable from the real scene may be used as standards to calibrate image sensors and validate image analysis algorithms for their measurement quality, performance consistency, and inter-laboratory comparisons for quantitative biomedical imaging applications.

  16. Hyperspectral imaging for detecting pathogens grown on agar plates

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

    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.

  17. Miniaturized hyperspectral imager calibration and UAV flight campaigns

    NASA Astrophysics Data System (ADS)

    Saari, Heikki; Pölönen, Ilkka; Salo, Heikki; Honkavaara, Eija; Hakala, Teemu; Holmlund, Christer; Mäkynen, Jussi; Mannila, Rami; Antila, Tapani; Akujärvi, Altti

    2013-10-01

    VTT Technical Research Centre of Finland has developed Tunable Fabry-Perot Interferometer (FPI) based miniaturized hyperspectral imager which can be operated from light weight Unmanned Aerial Vehicles (UAV). The concept of the hyperspectral imager has been published in the SPIE Proc. 7474, 8174 and 8374. This instrument requires dedicated laboratory and on-board calibration procedures which are described. During summer 2012 extensive UAV Hyperspectral imaging campaigns in the wavelength range 400 - 900 nm at resolution range 10 - 40 nm @ FWHM were performed to study forest inventory, crop biomass and nitrogen distributions and environmental status of natural water applications. The instrument includes spectral band limiting filters which can be used for the on-board wavelength scale calibration by scanning the FPI pass band center wavelength through the low and high edge of the operational wavelength band. The procedure and results of the calibration tests will be presented. A short summary of the performed extensive UAV imaging campaign during summer 2012 will be presented.

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

    PubMed

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

    2013-01-01

    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

  19. Tunable narrow-band filter for LWIR hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Daly, James T.; Bodkin, W. Andrew; Schneller, William J.; Kerr, Robert B.; Noto, John; Haren, Raymond; Eismann, Michael T.; Karch, Barry K.

    2000-04-01

    IR sensing has been a key enabling technology in military systems providing advantages in night vision, surveillance, and ever more accurate targeting. Passive hyperspectral imagin, the ability to gather and process IR spectral information from each pixel of an IR image, can ultimately provide 2D composition maps of a scene under study. FInding applications such as atmospheric, and geophysical remote sensing, camouflaged target recognition, and defence against chemical weapons.

  20. Hyperspectral cathodoluminescence imaging of modern and fossil carbonate shells

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

    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.

  1. PARTIAL LEAST SQUARES REGRESSION OF HYPERSPECTRAL IMAGES FOR CONTAMINATION DETECTION ON POULTRY CARCASSES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Abstract The U.S. Department of Agriculture has developed multispectral and hyperspectral imaging systems to detect faecal contaminants. Until recently, the hyperspectral imaging system has been used as a research tool to detect a few optimum wavelengths for use in a multispectral imaging system. ...

  2. Real-time hyperspectral image cube compression combining adaptive classification and partial transform coding

    Microsoft Academic Search

    Zheng Zhou; Jian Liu; Jinwen Tian

    2006-01-01

    In using partial transform for the coding of hyperspectral image, it must consider spectral decorrelation between image components, issues that a combined adaptive classification and partial transform algorithm for hyperspectral image compression is presented in this paper. Our method uses a linear prediction based on adaptive classification to decorrelate the spectrum redundancy and a 2D integer reversible DCT-based scheme as

  3. Visible to SWIR hyperspectral imaging for produce safety and quality evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging techniques, combining the advantages of spectroscopy and imaging, have found wider use in food quality and safety evaluation applications during the past decade. In light of the prevalent use of hyperspectral imaging techniques in the visible to near-infrared (VNIR: 400 -1000 n...

  4. Detection of physical defects in solar cells by hyperspectral imaging technology

    Microsoft Academic Search

    Qingli Li; Weisheng Wang; Chao Ma; Ziqiang Zhu

    2010-01-01

    A hyperspectral imaging system is developed and is used to identify cracks and fracture defects in solar cells. The basic principles and key technologies of this system are presented, along with a characterization of its performance. The system can provided both single-band images and spectrums of solar cells by laser scanning and hyperspectral imaging. The spectral angle mapper algorithm is

  5. A prior knowledge model for multidimensional striping noise compensation in hyperspectral imaging devices

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

    In this paper, a prior knowledge model is proposed in order to increase the effectiveness of a multidimensional striping noise compensation (SNC) algorithm. This is accomplished by considering an optoelectronic approach, thereby generating a more accurate mathematical representation of the hyperspectral acquisition process. The proposed model includes knowledge on the system spectral response, which can be obtained by means of an input with known spectral radiation. Further, the model also considers the dependence of the noise structure on the analog-digital conversion process, that is, schemes such as active-pixel sensor (APS) and passive-pixel sensor (PPS) have been considered. Finally, the model takes advantage of the degree of crosstalk between consecutive bands in order to determinate how much of this spectral information is contributing to the read out data obtained in a particular band. All prior knowledge is obtained by a series of experimental analysis, and then integrated into the model. After estimating the required parameters, the applicability of the multidimensional SNC is illustrated by compensating for stripping noise in hyperspectral images acquired using an experimental setup. A laboratory prototype, based on both a Photonfocus Hurricane hyperspectral camera and a Xeva Xenics NIR hyperspectral camera, has been implemented to acquire data in the range of 400-1000 [nm] and 900-1700 [nm], respectively. Also, a mobile platform has been used to simulate and synchronize the scanning procedure of the cameras and an uniform tungsten lamp has been installed to ensure an equal spectral radiance between the different bands for calibration purpose.

  6. MIST Final Report: Multi-sensor Imaging Science and Technology

    SciTech Connect

    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

    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.

  7. Hyperspectral image segmentation using a cooperative nonparametric approach

    NASA Astrophysics Data System (ADS)

    Taher, Akar; Chehdi, Kacem; Cariou, Claude

    2013-10-01

    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%.

  8. Scale-space in hyperspectral image analysis

    Microsoft Academic Search

    Julio M. Duarte-Carvajalino; Miguel Vélez-Reyes; Paul Castillo

    2006-01-01

    For two decades, techniques based on Partial Differential Equations (PDEs) have been used in monochrome and color image processing for image segmentation, restoration, smoothing and multiscale image representation. Among these techniques, parabolic PDEs have found a lot of attention for image smoothing and image restoration purposes. Image smoothing by parabolic PDEs can be seen as a continuous transformation of the

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

    PubMed

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

    2013-01-01

    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

  10. Multi-scale vector tunnel classification algorithm for hyperspectral images

    NASA Astrophysics Data System (ADS)

    Demirci, S.; Erer, I.; Unaldi, Nu.

    2013-05-01

    Hyperspectral image (HSI) classification consists of a variety of algorithms involving supervised or unsupervised. In supervised classification, some reference data are used. Training data are not used in unsupervised classification methods. The type of a classification algorithm depends on the nature of the input and reference data. The spectral matching, statistical and kernel based methods are the most widely known classification algorithms for hyperspectral imaging. Spectral matching algorithms try to identify the similarity of the unknown spectral signature of test pixels with the expected signature. Even though most spectra in real applications are random, the amount of training data with respect to the dimensionality affects the performances of the statistical classifiers substantially. In this study, an efficient spectral similarity method employing Multi-Scale Vector Tunnel Algorithm (MS-VTA) for supervised classification of the materials in hyperspectral imagery is introduced. With the proposed algorithm, a simple spectral similarity based decision rule using limited amount of reference data or spectral signature is formed and compared with the Euclidian Distance (ED) and the Spectral Angle Map (SAM) classifiers. The prediction of multi-level upper and lower spectral boundaries of spectral signatures for all classes across spectral bands constitutes the basic principle of the proposed algorithm.

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

    SciTech Connect

    Bernacki, Bruce E.; Phillips, Mark C.

    2010-05-01

    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.

  12. ASIC image sensors

    Microsoft Academic Search

    D. Renshaw; P. B. Denyer; G. Wang; M. Lu

    1990-01-01

    Two image array sensors designed and fabricated using a standard two-level metal ASIC CMOS process are described. The results show that good quality grey-level images can be formed, and that CMOS sensors arrays can be successfully integrated with efficient analogue sense amplifiers and with digital control\\/image-processing logic. The first sensor is a prototype 128×128 pixel test array. The second is

  13. Hyperspectral image segmentation method based on spatial-spectral constrained region active contour

    Microsoft Academic Search

    Junping Zhang; Jiawei Chen; Ye Zhang; Bin Zou

    2010-01-01

    Hyperspectral image provides rich information of ground covers, which has been brought great attention. Combining hyperspectral spatial and spectral constraint, an image segmentation method based on region active contour is proposed in this paper. The energy function in Chan-Vese's method is improved and both spatial and spectral information are employed. Spatial term of the function is restricted by global spatial

  14. Morphological scale-space for hyperspectral images and dimensionality exploration using tensor modeling

    Microsoft Academic Search

    Santiago Velasco-Forero; J. Angulo

    2009-01-01

    This paper proposes a framework to integrate spatial information into unsupervised feature extraction for hyperspectral images. In this approach a nonlinear scale-space representation using morphological levelings is formulated. In order to apply feature extraction, tensor principal components are computed involving spatial and spectral information. The proposed method has shown significant gain over the conventional schemes used with real hyperspectral images.

  15. Classification of hyperspectral images by using morphological attribute filters and Independent Component Analysis

    Microsoft Academic Search

    Mauro Dalla Mura; Alberto Villa; Jon Atli Benediktsson; Jocelyn Chanussot; Lorenzo Bruzzone

    2010-01-01

    In this paper, a technique based on Independent Component Analysis (ICA) and morphological attribute filters is presented for the classification of high geometrical resolution hyperspectral images. The ICA is computed instead of the conventional principal component analysis (PCA) in order to better model the information in the hyperspectral image. The spatial characteristics of the objects in the scene are modeled

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

    Microsoft Academic Search

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

    2008-01-01

    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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Microsoft Academic Search

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

    2007-01-01

    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

  19. POULTRY SKIN TUMOR DETECTION IN HYPERSPECTRAL REFLECTANCE IMAGES BY COMBINING CLASSIFIERS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper presents a new method for detecting poultry skin tumors in hyperspectral reflectance images. We employ the principal component analysis (PCA), discrete wavelet transform (DWT), and kernel discriminant analysis (KDA) to extract the independent feature sets in hyperspectral reflectance imag...

  20. On-Line Hyperspectral Transmittance Imaging for Internal Defect Detection of Pickling Cucumbers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging technique under transmittance mode was investigated for detection of internal defect in pickling cucumbers such as carpel suture separation or hollow cucumbers caused by mechanical stress. A prototype of on-line hyperspectral transmittance imaging system was developed for real...

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

    Microsoft Academic Search

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

    2012-01-01

    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

  2. Application of Hyperspectral Imaging in Food Safety Inspection and Control: A Review

    Microsoft Academic Search

    Yao-Ze Feng; Da-Wen Sun

    2012-01-01

    Food safety is a great public concern, and outbreaks of food-borne illnesses can lead to disturbance to the society. Consequently, fast and nondestructive methods are required for sensing the safety situation of produce. As an emerging technology, hyperspectral imaging has been successfully employed in food safety inspection and control. After presenting the fundamentals of hyperspectral imaging, this paper provides a

  3. Quantitative wavelength analysis and image classification for intraoperative cancer diagnosis with hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

    Complete surgical removal of tumor tissue is essential for postoperative prognosis after surgery. Intraoperative tumor imaging and visualization are an important step in aiding surgeons to evaluate and resect tumor tissue in real time, thus enabling more complete resection of diseased tissue and better conservation of healthy tissue. As an emerging modality, hyperspectral imaging (HSI) holds great potential for comprehensive and objective intraoperative cancer assessment. In this paper, we explored the possibility of intraoperative tumor detection and visualization during surgery using HSI in the wavelength range of 450 nm - 900 nm in an animal experiment. We proposed a new algorithm for glare removal and cancer detection on surgical hyperspectral images, and detected the tumor margins in five mice with an average sensitivity and specificity of 94.4% and 98.3%, respectively. The hyperspectral imaging and quantification method have the potential to provide an innovative tool for image-guided surgery.

  4. Embedded Bone Fragment Detection in Chicken Fillets using Transmittance Image Enhancement and Hyperspectral Reflectance Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper is concerned with the detection of bone fragments embedded in compressed de-boned skinless chicken breast fillets by enhancing single-band transmittance images generated by back-lighting and exploiting spectral information from hyperspectral reflectance images. Optical imaging of chicken ...

  5. MORPHOLOGICAL HYPERSPECTRAL IMAGE CLASSIFICATION: A PARALLEL

    E-print Network

    Plaza, Antonio J.

    , the SE acts as a probe for extracting or suppressing specific structures of the image objects, checking are defined in MM, namely erosion and dilation. The application of the erosion operator to an image yields of the dilation operator to an image produces an output image, which shows where the SE hits the objects

  6. Single aflatoxin contaminated corn kernel analysis with fluorescence hyperspectral image

    NASA Astrophysics Data System (ADS)

    Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Ononye, Ambrose; Brown, Robert L.; Cleveland, Thomas E.

    2010-04-01

    Aflatoxins are toxic secondary metabolites of the fungi Aspergillus flavus and Aspergillus parasiticus, among others. Aflatoxin contaminated corn is toxic to domestic animals when ingested in feed and is a known carcinogen associated with liver and lung cancer in humans. Consequently, aflatoxin levels in food and feed are regulated by the Food and Drug Administration (FDA) in the US, allowing 20 ppb (parts per billion) limits in food and 100 ppb in feed for interstate commerce. Currently, aflatoxin detection and quantification methods are based on analytical tests including thin-layer chromatography (TCL) and high performance liquid chromatography (HPLC). These analytical tests require the destruction of samples, and are costly and time consuming. Thus, the ability to detect aflatoxin in a rapid, nondestructive way is crucial to the grain industry, particularly to corn industry. Hyperspectral imaging technology offers a non-invasive approach toward screening for food safety inspection and quality control based on its spectral signature. The focus of this paper is to classify aflatoxin contaminated single corn kernels using fluorescence hyperspectral imagery. Field inoculated corn kernels were used in the study. Contaminated and control kernels under long wavelength ultraviolet excitation were imaged using a visible near-infrared (VNIR) hyperspectral camera. The imaged kernels were chemically analyzed to provide reference information for image analysis. This paper describes a procedure to process corn kernels located in different images for statistical training and classification. Two classification algorithms, Maximum Likelihood and Binary Encoding, were used to classify each corn kernel into "control" or "contaminated" through pixel classification. The Binary Encoding approach had a slightly better performance with accuracy equals to 87% or 88% when 20 ppb or 100 ppb was used as classification threshold, respectively.

  7. Data collection with a dual-band infrared hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Smith, Dale J.; Gupta, Neelam

    2005-08-01

    A novel dual-band hyperspectral imaging system has been used to collect field test data for robotics vision applications. The imaging system can collect full scene hyperspectral images in both the long wave infrared (LWIR) band (8-10.5 ?m) and the mid-wave infrare (MWIR) band (4-5.25 ?m) simultaneously. The imager uses a specially designed Ge diffractive lens with a dual-band 320×240 HgCdTe infrared focal plane array (FPA) cooled with a Sterling cooler. The stacked FPA consists of two layers: the top one sensitive in the MWIR region and the bottom one sensitive in the LWIR region. The diffractive lens is designed to focus a first order, single-color (i.e., 8.0 ?m) image in the LWIR onto the bottom layer of the FPA while at the same time focusing a second order single-color (i.e., 4.0 ?m) image in the MWIR onto the top layer of the FPA. Images at different wavelengths are acquired by moving the lens along its optical axis. Moving the lens over the entire range during data collection allows sequential collection of spectral images in each band resulting in the collection of two complete image cubes. The focal length of the lens is 75 mm at 9 ?m. The spectral resolution of the imager is 0.1 ?m at the 9 ?m wavelength. In general, 128 narrow wavelength bands are collected in each of the two broad spectral regions. After data collection, the images are processed to remove noise, contributions from unfocused wavelengths, and magnification differences. A description of the imager, data collection, noise removal, post-processing, and analysis are presented.

  8. Hyperspectral image classifier based on beach spectral feature

    NASA Astrophysics Data System (ADS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-03-01

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

  9. Hyperspectral imaging of microalgae using two-photon excitation.

    SciTech Connect

    Sinclair, Michael B.; Melgaard, David Kennett; Reichardt, Thomas A. (Sandia National Laboratories, Livermore, CA); Timlin, Jerilyn Ann; Garcia, Omar Fidel; Luk, Ting Shan; Jones, Howland D. T.; Collins, Aaron M.

    2010-10-01

    A considerable amount research is being conducted on microalgae, since microalgae are becoming a promising source of renewable energy. Most of this research is centered on lipid production in microalgae because microalgae produce triacylglycerol which is ideal for biodiesel fuels. Although we are interested in research to increase lipid production in algae, we are also interested in research to sustain healthy algal cultures in large scale biomass production farms or facilities. The early detection of fluctuations in algal health, productivity, and invasive predators must be developed to ensure that algae are an efficient and cost-effective source of biofuel. Therefore we are developing technologies to monitor the health of algae using spectroscopic measurements in the field. To do this, we have proposed to spectroscopically monitor large algal cultivations using LIDAR (Light Detection And Ranging) remote sensing technology. Before we can deploy this type of technology, we must first characterize the spectral bio-signatures that are related to algal health. Recently, we have adapted our confocal hyperspectral imaging microscope at Sandia to have two-photon excitation capabilities using a chameleon tunable laser. We are using this microscope to understand the spectroscopic signatures necessary to characterize microalgae at the cellular level prior to using these signatures to classify the health of bulk samples, with the eventual goal of using of LIDAR to monitor large scale ponds and raceways. By imaging algal cultures using a tunable laser to excite at several different wavelengths we will be able to select the optimal excitation/emission wavelengths needed to characterize algal cultures. To analyze the hyperspectral images generated from this two-photon microscope, we are using Multivariate Curve Resolution (MCR) algorithms to extract the spectral signatures and their associated relative intensities from the data. For this presentation, I will show our two-photon hyperspectral imaging results on a variety of microalgae species and show how these results can be used to characterize algal ponds and raceways.

  10. Experimental evaluation of a hyperspectral imager for near-infrared fluorescent contrast agent studies

    NASA Astrophysics Data System (ADS)

    Luthman, A. S.; Bohndiek, Sarah E.

    2015-03-01

    Hyperspectral imaging (HSI) systems have the potential to combine morphological and spectral information to provide detailed and high sensitivity readouts in biological and medical applications. As HSI enables simultaneous detection in several spectral bands, the technology has significant potential for use in real-time multiplexed contrast agent studies. Examples include tumor detection in intraoperative and endoscopic imaging as well as histopathology. A multiplexed readout from multiple disease targets, such as cell surface receptors overexpressed in cancer cells, could improve both sensitivity and specificity of tumor identification. Here, we evaluate a commercial, compact, near-infrared HSI sensor that has the potential to enable low cost, video rate HSI for multiplexed fluorescent contrast agent studies in biomedical applications. The hyperspectral imager, based on a monolithically integrated Fabry-Perot etalon, has 70 spectral bands between 600-900 nm, making it ideal for this application. Initial calibration of the imager was performed to determine wavelength band response, quantum efficiency and the effect of F-number on the spectral response. A platform for wide-field fluorescence imaging in reflectance using fluorophore specific LED excitation was then developed. The applicability of the imaging platform for simultaneous readout of multiple fluorophore signals was demonstrated using a dilution series of Alexa Fluor 594 and Alexa Fluor 647, showing that nanomolar fluorophore concentrations can be detected. Our results show that the HSI system can clearly resolve the emission spectra of the two fluorophores in mixtures of concentrations across several orders of magnitude, indicating a high dynamic range performance. We therefore conclude that the HSI sensor tested here is suitable for detecting fluorescence in biomedical imaging applications.

  11. Wide-field hyperspectral 3D imaging of functionalized gold nanoparticles targeting cancer cells by reflected light microscopy.

    PubMed

    2015-05-01

    We present a new hyperspectral reflected light microscopy system with a scanned broadband supercontinuum light source. This wide-field and low phototoxic hyperspectral imaging system has been successful for performing spectral three-dimensional (3D) localization and spectroscopic identification of CD44-targeted PEGylated AuNPs in fixed cell preparations. Such spatial and spectral information is essential for the improvement of nanoplasmonic-based imaging, disease detection and treatment in complex biological environment. The presented system can be used for real-time 3D NP tracking as spectral sensors, thus providing new avenues in the spatio-temporal characterization and detection of bioanalytes. 3D image of the distribution of functionalized AuNPs attached to CD44-expressing MDA-MB-231 human cancer cells. PMID:24961507

  12. Improved detection and false alarm rejection for chemical vapors using passive hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Marinelli, William J.; Miyashiro, Rex; Gittins, Christopher M.; Konno, Daisei; Chang, Shing; Farr, Matt; Perkins, Brad

    2013-05-01

    Two AIRIS sensors were tested at Dugway Proving Grounds against chemical agent vapor simulants. The primary objectives of the test were to: 1) assess performance of algorithm improvements designed to reduce false alarm rates with a special emphasis on solar effects, and 3) evaluate performance in target detection at 5 km. The tests included 66 total releases comprising alternating 120 kg glacial acetic acid (GAA) and 60 kg triethyl phosphate (TEP) events. The AIRIS sensors had common algorithms, detection thresholds, and sensor parameters. The sensors used the target set defined for the Joint Service Lightweight Chemical Agent Detector (JSLSCAD) with TEP substituted for GA and GAA substituted for VX. They were exercised at two sites located at either 3 km or 5 km from the release point. Data from the tests will be presented showing that: 1) excellent detection capability was obtained at both ranges with significantly shorter alarm times at 5 km, 2) inter-sensor comparison revealed very comparable performance, 3) false alarm rates < 1 incident per 10 hours running time over 143 hours of sensor operations were achieved, 4) algorithm improvements eliminated both solar and cloud false alarms. The algorithms enabling the improved false alarm rejection will be discussed. The sensor technology has recently been extended to address the problem of detection of liquid and solid chemical agents and toxic industrial chemical on surfaces. The phenomenology and applicability of passive infrared hyperspectral imaging to this problem will be discussed and demonstrated.

  13. Synthesis of Multispectral Bands from Hyperspectral Data: Validation Based on Images Acquired by AVIRIS, Hyperion, ALI, and ETM+

    NASA Technical Reports Server (NTRS)

    Blonski, Slawomir; Glasser, Gerald; Russell, Jeffrey; Ryan, Robert; Terrie, Greg; Zanoni, Vicki

    2003-01-01

    Spectral band synthesis is a key step in the process of creating a simulated multispectral image from hyperspectral data. In this step, narrow hyperspectral bands are combined into broader multispectral bands. Such an approach has been used quite often, but to the best of our knowledge accuracy of the band synthesis simulations has not been evaluated thus far. Therefore, the main goal of this paper is to provide validation of the spectral band synthesis algorithm used in the ART software. The next section contains a description of the algorithm and an example of its application. Using spectral responses of AVIRIS, Hyperion, ALI, and ETM+, the following section shows how the synthesized spectral bands compare with actual bands, and it presents an evaluation of the simulation accuracy based on results of MODTRAN modeling. In the final sections of the paper, simulated images are compared with data acquired by actual satellite sensors. First, a Landsat 7 ETM+ image is simulated using an AVIRIS hyperspectral data cube. Then, two datasets collected with the Hyperion instrument from the EO-1 satellite are used to simulate multispectral images from the ALI and ETM+ sensors.

  14. Adaptive classification of hyperspectral images using local consistency

    NASA Astrophysics Data System (ADS)

    Bian, Xiaoyong; Zhang, Xiaolong; Liu, Renfeng; Ma, Li; Fu, Xiaowei

    2014-11-01

    A spatial method of multistructure sampling based rotation-invariant uniform local binary pattern (named MsLBPriu2) for classification of hyperspectral images is proposed. This method exploits the local property (micro-/macrostructure) of local image patches encoded in the classifier by considering a local neighboring structure around each central pixel and can well suppress the difference of rotational textures for each multicluster class. The proposed method is simple yet efficient for extracting isotropic and anisotropic spatial features from local image patches via different extended sampling on circular regions and elliptical ones with four different rotational angles. Furthermore, the rotation-invariant characteristic of extracted isotropic features is achieved by the inclusion of a rotation-invariant uniform LBP operator. Moreover, the proposed method becomes more robust with respect to the within-class variation. Finally, different classifiers, support vector machine, K-nearest neighbor, and linear discriminant analysis, are compared to evaluate MsLBPriu2 and other feature sets/entropy-based query-by-bagging active learning. We demonstrate the performance of our approach on four different hyperspectral remote sensing images. Experimental results show that the new set of reduced spatial features has a better performance than a variety of state-of-the-art classification algorithms.

  15. Rapid hyperspectral imaging in the mid-infrared

    NASA Astrophysics Data System (ADS)

    Kröger, N.; Egl, A.; Engel, M.; Gretz, N.; Haase, K.; Herpich, I.; Neudecker, S.; Pucci, A.; Schönhals, A.; Petrich, W.

    2014-03-01

    Despite the successes of mid-infrared hyperspectral imaging in a research environment, progress in the migration of technology into the day-to-day clinical application is slow. Clinical acceptance may be improved if the spectroscopy would be faster and the infrared microscopes available at lower cost. Here we present first results of a fast, multi-scale mid-infrared microscopy setup which allows for the investigation of 10.6×11.7 mm2 and 2.8×3.1mm2 fields of view with a resolution of 23.0+/-3.5 ?m and 9.4+/-1.8 ?m, respectively. Tunable quantum cascade lasers in the wavenumber ranges of 1030-1090 cm-1 and 1160-1320 cm-1 serve as light sources. A vapor cell is used as a frequency reference during the rapid scanning. As far as the imaging is concerned, it is the high spectral power density of the quantum cascade laser which enables the use of a microbolometer array while still obtaining reasonable signal-to-noise ratios on each pixel. Hyperspectral images are taken in times which can be as low as 52s for the overall image acquisition including referencing.

  16. Multiparadigm Space Processing for Hyperspectral Imaging

    Microsoft Academic Search

    Adam Jacobs; Chris Conger; Alan D. George

    2008-01-01

    Projected demands for future space missions, where on-board sensor processing and autonomous control rapidly expand computational requirements, are outpacing technologies and trends in conventional embedded microprocessors. To achieve higher levels of performance as well as relative performance versus power consumption, new processing technologies are of increasing interest for space systems. Technologies such as reconfigurable computing based upon FPGAs and vector

  17. [Hyperspectral image classification based on 3-D gabor filter and support vector machines].

    PubMed

    Feng, Xiao; Xiao, Peng-feng; Li, Qi; Liu, Xiao-xi; Wu, Xiao-cui

    2014-08-01

    A three-dimensional Gabor filter was developed for classification of hyperspectral remote sensing image. This method is based on the characteristics of hyperspectral image and the principle of texture extraction with 2-D Gabor filters. Three-dimensional Gabor filter is able to filter all the bands of hyperspectral image simultaneously, capturing the specific responses in different scales, orientations, and spectral-dependent properties from enormous image information, which greatly reduces the time consumption in hyperspectral image texture extraction, and solve the overlay difficulties of filtered spectrums. Using the designed three-dimensional Gabor filters in different scales and orientations, Hyperion image which covers the typical area of Qi Lian Mountain was processed with full bands to get 26 Gabor texture features and the spatial differences of Gabor feature textures corresponding to each land types were analyzed. On the basis of automatic subspace separation, the dimensions of the hyperspectral image were reduced by band index (BI) method which provides different band combinations for classification in order to search for the optimal magnitude of dimension reduction. Adding three-dimensional Gabor texture features successively according to its discrimination to the given land types, supervised classification was carried out with the classifier support vector machines (SVM). It is shown that the method using three-dimensional Gabor texture features and BI band selection based on automatic subspace separation for hyperspectral image classification can not only reduce dimensions; but also improve the classification accuracy and efficiency of hyperspectral image. PMID:25474965

  18. [Hyperspectral image classification based on 3-D gabor filter and support vector machines].

    PubMed

    Feng, Xiao; Xiao, Peng-feng; Li, Qi; Liu, Xiao-xi; Wu, Xiao-cui

    2014-08-01

    A three-dimensional Gabor filter was developed for classification of hyperspectral remote sensing image. This method is based on the characteristics of hyperspectral image and the principle of texture extraction with 2-D Gabor filters. Three-dimensional Gabor filter is able to filter all the bands of hyperspectral image simultaneously, capturing the specific responses in different scales, orientations, and spectral-dependent properties from enormous image information, which greatly reduces the time consumption in hyperspectral image texture extraction, and solve the overlay difficulties of filtered spectrums. Using the designed three-dimensional Gabor filters in different scales and orientations, Hyperion image which covers the typical area of Qi Lian Mountain was processed with full bands to get 26 Gabor texture features and the spatial differences of Gabor feature textures corresponding to each land types were analyzed. On the basis of automatic subspace separation, the dimensions of the hyperspectral image were reduced by band index (BI) method which provides different band combinations for classification in order to search for the optimal magnitude of dimension reduction. Adding three-dimensional Gabor texture features successively according to its discrimination to the given land types, supervised classification was carried out with the classifier support vector machines (SVM). It is shown that the method using three-dimensional Gabor texture features and BI band selection based on automatic subspace separation for hyperspectral image classification can not only reduce dimensions; but also improve the classification accuracy and efficiency of hyperspectral image. PMID:25508744

  19. Material characterization using a hyperspectral infrared imaging spectrometer

    SciTech Connect

    Aimonetti, W D; Bixler, J V; Roberts, R S

    1998-10-30

    Fourier transform spectroscopy has found application in many areas including chemometrics, biomedical and biochemical studies, and atmospheric chemistry. This paper describes an investigation into the application of the LLNL Hyperspectral Infrared Imaging Spectrometer (HIRIS) to the non-destructive evaluation of man-made and natural materials. We begin by describing the HIRIS system and the objects studied in the investigation. Next, we describe the technique used to collect the hyperspec- tral imagery, and discuss the processing required to transform the data into usable form. We then describe a technique to analyze the data, and provide some preliminary results.

  20. Application of novel hyperspectral imaging technologies in combat casualty care

    NASA Astrophysics Data System (ADS)

    Cancio, Leopoldo C.

    2010-02-01

    Novel hyperspectral imaging (HSI) methods may play several important roles in Combat Casualty Care: (1) HSI of the skin may provide spatial data on hemoglobin saturation of oxygen, as a "window" into perfusion during shock. (2) HSI or similar technology could be incorporated into closed-loop, feedback-controlled resuscitation systems. (3) HSI may provide information about tissue viability and/or wound infection. (4) HSI in the near-infrared range may provide information on the tissue water content--greatly affected, e.g., by fluid resuscitation. Thus, further refinements in the speed and size of HSI systems are sought to make these capabilities available on the battlefield.

  1. Advanced hyperspectral video imaging system using Amici prism.

    PubMed

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

    2014-08-11

    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

  2. Hyperspectral and Multispectral Image Fusion Based on a Sparse Representation

    NASA Astrophysics Data System (ADS)

    Wei, Qi; Bioucas-Dias, Jose; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2015-07-01

    This paper presents a variational based approach to fusing hyperspectral and multispectral images. The fusion process is formulated as an inverse problem whose solution is the target image assumed to live in a much lower dimensional subspace. A sparse regularization term is carefully designed, relying on a decomposition of the scene on a set of dictionaries. The dictionary atoms and the corresponding supports of active coding coefficients are learned from the observed images. Then, conditionally on these dictionaries and supports, the fusion problem is solved via alternating optimization with respect to the target image (using the alternating direction method of multipliers) and the coding coefficients. Simulation results demonstrate the efficiency of the proposed algorithm when compared with the state-of-the-art fusion methods.

  3. Advanced Airborne Hyperspectral Imaging System (AAHIS): an imaging spectrometer for maritime applications

    NASA Astrophysics Data System (ADS)

    Voelker, Mark A.; Resmini, Ronald G.; Mooradian, Gregory C.; McCord, Thomas B.; Warren, Christopher P.; Fene, Michael W.; Coyle, Christopher C.; Anderson, Richard

    1995-06-01

    The Advanced Airborne Hyperspectral Imaging System (AAHIS) is a compact, lightweight visible and near IR pushbroom hyperspectral imaging spectrometer flown on a Piper Aztec aircraft. AAHIS is optimized for use in shallow water, littoral, and vegetation remote sensing. Data are collected at up to 55 frames/second and may be displayed and analyzed inflight or recorded for post-flight processing. Swath width is 200 meters at a flight altitude of 1 km. Each image pixel contains hyperspectral data simultaneously recorded in up to 288 contiguous spectral channels covering the 432 to 832 nm spectral region. Pixel binning typically yields pixels 1.0 meter square with a spectral channel width of 5.5 nm. Design and performance of the AAHIS is presented, including processed imagery demonstrating feature detection and materials discrimination on land and underwater at depths up to 27 meters.

  4. Abstract--We are developing a hyperspectral imaging system aimed at imaging fluorescent molecules in two

    E-print Network

    Leahy, Richard M.

    spectrum of the fluorescent light will provide additional information, thus allowing an improvement of the wavelength spectrum allows the determination of the depth of a localized fluorescent object. A spectralAbstract-- We are developing a hyperspectral imaging system aimed at imaging fluorescent molecules

  5. Extraction of spatial features in hyperspectral images based on the analysis of differential attribute profiles

    NASA Astrophysics Data System (ADS)

    Falco, Nicola; Benediktsson, Jon A.; Bruzzone, Lorenzo

    2013-10-01

    The new generation of hyperspectral sensors can provide images with a high spectral and spatial resolution. Recent improvements in mathematical morphology have developed new techniques such as the Attribute Profiles (APs) and the Extended Attribute Profiles (EAPs) that can effectively model the spatial information in remote sensing images. The main drawbacks of these techniques is the selection of the optimal range of values related to the family of criteria adopted to each filter step, and the high dimensionality of the profiles, which results in a very large number of features and therefore provoking the Hughes phenomenon. In this work, we focus on addressing the dimensionality issue, which leads to an highly intrinsic information redundancy, proposing a novel strategy for extracting spatial information from hyperspectral images based on the analysis of the Differential Attribute Profiles (DAPs). A DAP is generated by computing the derivative of the AP; it shows at each level the residual between two adjacent levels of the AP. By analyzing the multilevel behavior of the DAP, it is possible to extract geometrical features corresponding to the structures within the scene at different scales. Our proposed approach consists of two steps: 1) a homogeneity measurement is used to identify the level L in which a given pixel belongs to a region with a physical meaning; 2) the geometrical information of the extracted regions is fused into a single map considering their level L previously identified. The process is repeated for different attributes building a reduced EAP, whose dimensionality is much lower with respect to the original EAP ones. Experiments carried out on the hyperspectral data set of Pavia University area show the effectiveness of the proposed method in extracting spatial features related to the physical structures presented in the scene, achieving higher classification accuracy with respect to the ones reported in the state-of-the-art literature

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  7. Calibration methodology and performance characterization of a polarimetric hyperspectral imager

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  8. NIR DLP hyperspectral imaging system for medical applications

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    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.

  9. SETA-Hyperspectral Imaging Spectrometer for Marco Polo mission.

    NASA Astrophysics Data System (ADS)

    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

    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).

  10. Digital Compressive Quantitation and Hyperspectral Imaging

    E-print Network

    2013-07-25

    imaging and online monitoring, routinely generate large, high dimensional data ... variate optical elements, such as a liquid-crystal spatial light modulator or digital ..... been previously used in demonstrating the performance of a. DMD-

  11. Comparison of multi- and hyperspectral imaging data of leaf rust infected wheat plants

    NASA Astrophysics Data System (ADS)

    Franke, Jonas; Menz, Gunter; Oerke, Erich-Christian; Rascher, Uwe

    2005-10-01

    In the context of precision agriculture, several recent studies have focused on detecting crop stress caused by pathogenic fungi. For this purpose, several sensor systems have been used to develop in-field-detection systems or to test possible applications of remote sensing. The objective of this research was to evaluate the potential of different sensor systems for multitemporal monitoring of leaf rust (puccinia recondita) infected wheat crops, with the aim of early detection of infected stands. A comparison between a hyperspectral (120 spectral bands) and a multispectral (3 spectral bands) imaging system shows the benefits and limitations of each approach. Reflectance data of leaf rust infected and fungicide treated control wheat stand boxes (1sqm each) were collected before and until 17 days after inoculation. Plants were grown under controlled conditions in the greenhouse and measurements were taken under consistent illumination conditions. The results of mixture tuned matched filtering analysis showed the suitability of hyperspectral data for early discrimination of leaf rust infected wheat crops due to their higher spectral sensitivity. Five days after inoculation leaf rust infected leaves were detected, although only slight visual symptoms appeared. A clear discrimination between infected and control stands was possible. Multispectral data showed a higher sensitivity to external factors like illumination conditions, causing poor classification accuracy. Nevertheless, if these factors could get under control, even multispectral data may serve a good indicator for infection severity.

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

    Microsoft Academic Search

    Qian Du; Nicolas H. Younan

    2008-01-01

    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

  13. Hyperspectral Image Compression: Adapting SPIHT and EZW to Anisotropic 3-D Wavelet Coding

    Microsoft Academic Search

    Emmanuel Christophe; Corinne Mailhes; Pierre Duhamel

    2008-01-01

    Hyperspectral images present some specific characteristics that should be used by an efficient compression system. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity. Some wavelet-based compression algorithms have been successfully used for some hyperspectral space missions. This paper focuses on the optimization of a full wavelet compression system for

  14. Development of a Hyperspectral Imaging System for Online Quality Inspection of Pickling Cucumbers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper reports on the development of a hyperspectral imaging prototype for evaluation of external and internal quality of pickling cucumbers. The prototype consisted of a two-lane round belt conveyor, two illumination sources (one for reflectance and one for transmittance), and a hyperspectral i...

  15. Active Learning via Multi-View and Local Proximity Co-Regularization for Hyperspectral Image Classification

    Microsoft Academic Search

    Wei Di; Melba M. Crawford

    2011-01-01

    A novel co-regularization framework for active learning is proposed for hyperspectral image classification. The first regularizer explores the intrinsic multi-view information em- bedded in the hyperspectral data. By adaptively and quantitatively measuring the disagreement level, it focuses only on samples with high uncertainty and builds a contention pool which is a small subset of the overall unlabeled data pool, thereby

  16. Mid-infrared hyperspectral imaging of painting materials

    NASA Astrophysics Data System (ADS)

    Rosi, Francesca; Harig, Roland; Miliani, Costanza; Braun, René; Sali, Diego; Daveri, Alessia; Brunetti, Brunetto G.; Sgamellotti, Antonio

    2013-05-01

    A novel hyperspectral imaging system (HI90, Bruker Optics), working in the mid-infrared range and recently developed for the remote identification and mapping of hazardous compounds, has here been optimized for investigating painting surfaces. The painting Sestante 10 (1982) by Alberto Burri has been spectrally and spatially investigated with the HI90 system revealing the distribution of inorganic materials constituting the artworks. In order to validate the results obtainable by the imager for the pigment identification previous tests on laboratory models were performed. Yellow, white and blue pigments painted with different binders (namely egg, alkyd, acrylic and vinyl) were investigated by the HI90. Afterwards, the polychrome painting Sestante 10 was investigated focusing the attention on the inorganic material distribution revealing the presence of different extenders (kaolin, BaSO4, CaSO4) mixed with the various silica-based pigments present in the painting. The brightness temperature spectra collected by HI90 have also been compared to single point reflection spectra acquired by a conventional portable FTIR spectrometer (Alpha-R by Bruker Optics) highlighting the good spectral quality of the imaging system. This comparison permitted also to evaluate the spectral response and the diagnostic strengths of the spectral range available by the HI90 imaging (1300-860 cm-1), validating the reliability of the obtained chemical images. This study clearly highlights the high potential of the new hyperspectral imaging system and opens up new perspectives in the current scientific interest devoted to the application of mapping and imaging methods for the study of painting surfaces.

  17. Application of hyperspectral imaging in food safety inspection and control: a review.

    PubMed

    Feng, Yao-Ze; Sun, Da-Wen

    2012-01-01

    Food safety is a great public concern, and outbreaks of food-borne illnesses can lead to disturbance to the society. Consequently, fast and nondestructive methods are required for sensing the safety situation of produce. As an emerging technology, hyperspectral imaging has been successfully employed in food safety inspection and control. After presenting the fundamentals of hyperspectral imaging, this paper provides a comprehensive review on its application in determination of physical, chemical, and biological contamination on food products. Additionally, other studies, including detecting meat and meat bone in feedstuffs as well as organic residue on food processing equipment, are also reported due to their close relationship with food safety control. With these applications, it can be demonstrated that miscellaneous hyperspectral imaging techniques including near-infrared hyperspectral imaging, fluorescence hyperspectral imaging, and Raman hyperspectral imaging or their combinations are powerful tools for food safety surveillance. Moreover, it is envisaged that hyperspectral imaging can be considered as an alternative technique for conventional methods in realizing inspection automation, leading to the elimination of the occurrence of food safety problems at the utmost. PMID:22823350

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

    Microsoft Academic Search

    Jessica J. Mitchell; Nancy F. Glenn

    2009-01-01

    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

  19. [Retrieval of spectral characteristics of hyperspectral sensor and retrieval of reflectance spectra].

    PubMed

    Wang, Tian-xing; Yan, Guang-jian; Ren, Hua-zhong; Mu, Xi-han

    2010-10-01

    On-orbit spectral calibration of hyperspectral imaging data is a key step for quantitatively analyzing them. Like the atmospheric correction, accurate spectral calibration is very necessary for improved studies of land or ocean surface properties. Based on the previous literatures, a new method which coupled an optimization algorithm was developed to simultaneously retrieve the central wavelength and the full width at half maximum (FWHM) of the hyperspectral sensor without needing the in situ reflectance spectra. Firstly, the Hyperion data set simulated using MODTRAN4 with the Hyperion spectral specification was used to test the new method, and the results indicated that the maximum error was less than 0.1 and 0.7 nm for central wavelength and FWHM respectively when the spectral shift is 5 nm. Then the algorithm was applied to the Hyperion data acquired on May 20, 2008 over Heihe River Basin and it was iteratively performed for each detector of the two spectrometers of Hyperion. The results showed that the VNIR of Hyperion had a pronounced smile effect, and the shift in on-orbit calibration with respect to the laboratory was from -2 to +2 nm, while the SWIR has essentially no smile effect, the wavelength correction was relatively flat over all sample with an approximately constant value of 3 nm. The FWHM in VNIR could range from -0.2 to 0.5 nm as a function of sample number of the spectrometer, and in SWIR it ranged from -2 to -3 nm. So for both the VNIR and SWIR, the original spectral calibration should be updated. These results showed good agreement with previous research findings, and which also proved the feasibility of the new method. Finally, with the updated spectral calibration characteristics, the sample reflectances of desert and vegetation target in our study site were reconstructed by applying a further atmospheric correction, and as expected, the strong spikes around the typical atmospheric absorption were almost disappeared. PMID:21137406

  20. Hyperspectral imaging applied to medical diagnoses and food safety

    NASA Astrophysics Data System (ADS)

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

    2003-08-01

    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 conventional diagnostic imaging. By analyzing reflected and fluorescent light applied to the human body, a HSI system serves as a diagnostic tool as well as a method for evaluating the effectiveness of applied therapies. The safe supply and production of food is also of paramount importance to public health illness prevention. Although this paper will focus on imaging and spectroscopy in food inspection procedures -- the detection of contaminated food sources -- to ensure food quality, HSI also shows promise in detecting pesticide levels in food production (agriculture.)

  1. Hyperspectral imaging of cells: toward real-time pathological assessment

    NASA Astrophysics Data System (ADS)

    Demos, Stavros G.; Ramsamooj, Rajen

    2003-12-01

    The goal of this work is to develop micro-scale noninvasive photonic instrumentation and techniques that will enable real-time imaging and monitoring of microstructures and cells in tissues. We utilize a hyperspectral microscope to explore the differences of native fluorescence and polarized light scattering from cellular components using various excitation wavelengths. The key optical "signature" characteristics that differentiate the various cellular components are used to obtain composite images that highlight their presence and the relative concentration of various tissue chromophores. The sensitivity has been optimized in our specially designed instrumentation so that image acquisition times are very short for real-time application in a clinical setting. This technology is not invasive to the cells and therefore it can be used to monitor their function while they are still alive.

  2. Hyperspectral data collections with the new wedge imaging spectrometer

    SciTech Connect

    Jeter, J.W.; Hartshorne, R.; Thunen, J.G. [Hughes Santa Barbara Remote Sensing (SBRS), Goleta, CA (United States)

    1996-11-01

    The Wedge Imaging Spectrometer (WIS) applies a unique technology to hyperspectral imaging systems, allowing flexibility and high performance in a very compact package. This innovation is based on the use of a linear spectral wedge filter mated directly to an area detector array, avoiding the use of bulky and complex optics required for imaging spectrometers based on gratings or prism concepts. The technology was realized in an earlier flight demonstration system as previously reported. Second generation VNIR and SWIR instruments have now been developed, each with two filters whose spectral bandwidths are optimized for specific spectral features. The SWIR instrument can be extended to operate in the 3-5 PM mid-wave spectral region. The new instrument is currently completing its integration and test phase. Preliminary results indicate excellent performance potential for a wide range of applications. 2 figs., 1 tab.

  3. Monitoring biofilm attachment on medical devices surfaces using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

    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.

  5. Efficient detection in hyperspectral imagery

    Microsoft Academic Search

    Susan M. Schweizer; José M. F. Moura

    2001-01-01

    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

  6. Hyperspectral imagery: Clutter adaptation in anomaly detection

    Microsoft Academic Search

    Susan M. Schweizer; José M. F. Moura

    2000-01-01

    Hyperspectral sensors are passive sensors that simultaneously record images for hundreds of contiguous and narrowly spaced regions of the electromagnetic spectrum. Each image corresponds to the same ground scene, thus creating a cube of images that contain both spatial and spectral information about the objects and backgrounds in the scene. In this paper, we present an adaptive anomaly detector designed

  7. Near-infrared hyperspectral reflectance imaging for detection of bruises on pickling cucumbers

    Microsoft Academic Search

    Diwan P. Ariana; Renfu Lu; Daniel E. Guyer

    2006-01-01

    Mechanical injury often causes hidden internal damage to pickling cucumbers, which lowers the quality of pickled products and can incur economic losses to the processor. A near-infrared hyperspectral imaging system was developed to capture hyperspectral images from pickling cucumbers in the spectral region of 900–1700nm. The system consisted of an imaging spectrograph attached to an InGaAs camera with line-light fiber

  8. A simultaneous dual-band infrared hyperspectral imager for standoff detection

    Microsoft Academic Search

    Neelam Gupta; Dale Smith

    2005-01-01

    A novel dual-band hyperspectral imager has been developed to collect 128-band hyperspectral image cubes simultaneously in both 4-5.25 mum (mid wave IR, MWIR) and 8-10.5 mum (long wave IR, LWIR) bands for both target detection and standoff detection of chemical and biological agents. The imager uses a specially designed diffractive optics Ge lens with a dual-band 320×240 HgCdTe infrared (IR)

  9. Evaluation of the GPU architecture for the implementation of target detection algorithms for hyperspectral imagery

    Microsoft Academic Search

    Blas Trigueros-Espinosa; Miguel Vélez-Reyes; Nayda G. Santiago-Santiago; Samuel Rosario-Torres

    2011-01-01

    Hyperspectral sensors can collect hundreds of images taken at different narrow and contiguously spaced spectral bands. This high-resolution spectral information can be used to identify materials and objects within the field of view of the sensor by their spectral signature, but this process may be computationally intensive due to the large data sizes generated by the hyperspectral sensors, typically hundreds

  10. Preliminary hyperspectral volcano observations using Airborne Radiative Spectral Scanner (ARTS)

    Microsoft Academic Search

    T. Jitsufuchi

    2008-01-01

    Airborne-imaging spectral systems can often efficiently identify volcanic phenomena that are difficult to detect by satellite imagery. Since 1990, the National Research Institute for Earth Science and Disaster Prevention (NIED) has been developing our original airborne-imaging spectral systems for volcano observations. In 2006, we developed a new airborne hyperspectral sensor, the Airborne Radiative Transfer Spectral Scanner (ARTS), for hyperspectral volcano

  11. Karhunen-Loève transform for compressive sampling hyperspectral images

    NASA Astrophysics Data System (ADS)

    Liu, Lei; Yan, Jingwen; Zheng, Xianwei; Peng, Hong; Guo, Di; Qu, Xiaobo

    2015-01-01

    Compressed sensing (CS) is a new jointly sampling and compression technology for remote sensing. In hyperspectral imaging, a typical CS method encodes the two-dimensional (2-D) spatial information of each spectral band or encodes the third spectral information simultaneously. However, encoding the spatial information is much easier than encoding the spectral information. Therefore, it is crucial to make use of the spectral information to improve the compression rate on 2-D CS data. We propose to encode the third spectral information with an adaptive Karhunen-Loève transform. With a mathematical proof, we show that interspectral correlations are preserved among 2-D randomly encoded spatial information. This property means that one can compress 2-D CS data effectively with a Karhunen-Loève transform. Experiments demonstrate that the proposed method can better reconstruct both spectral curves and spatial images than traditional compression methods at the bit rates 0 to 1.

  12. Apple ripeness detection using hyperspectral laser scatter imaging

    NASA Astrophysics Data System (ADS)

    Van Beers, Robbe; Aernouts, Ben; De Baerdemaeker, Josse; Saeys, Wouter

    2013-05-01

    A hyperspectral laser scatter imaging (HLSI) system based on a supercontinuum laser in combination with a monochromator has been developed for contactless and non-destructive measuring the ripeness of Braeburn apples. Reflectance images were obtained by a CCD camera at 91 different wavelengths ranging from 550 nm to 1000 nm and transformed into reflectance profiles. A linear function was fitted to the logarithm (log10) of the extracted profiles, resulting in an intercept and a slope. These two parameters were then correlated with apple ripeness parameters such as firmness and soluble solids content (SSC) measured by the reference, destructive methods. Preliminary results showed the potential of slope and intercept to be used as a ripeness indicator. Moreover, during fruit ripening, the new HLSI measurement technique clearly showed the degradation of chlorophyll over time.

  13. Towards a colony counting system using hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Masschelein, B.; Robles-Kelly, A.; Blanch, C.; Tack, N.; Simpson-Young, B.; Lambrechts, A.

    2012-03-01

    Colony counting is a procedure used in microbiology laboratories for food quality monitoring, environmental management, etc. Its purpose is to detect the level of contamination due to the presence and growth of bacteria, yeasts and molds in a given product. Current automated counters require a tedious training and setup procedure per product and bacteria type and do not cope well with diversity. This contrasts with the setting at microbiology laboratories, where a wide variety of food and bacteria types have to be screened on a daily basis. To overcome the limitations of current systems, we propose the use of hyperspectral imaging technology and examine the spectral variations induced by factors such as illumination, bacteria type, food source and age and type of the agar. To this end, we perform experiments making use of two alternative hyperspectral processing pipelines and compare our classification results to those yielded by color imagery. Our results show that colony counting may be automated through the automatic recovery of the illuminant power spectrum and reflectance. This is consistent with the notion that the recovery of the illuminant should minimize the variations in the spectra due to reflections, shadows and other photometric artifacts. We also illustrate how, with the reflectance at hand, the colonies can be counted making use of classical segmentation and classification algorithms.

  14. Multi- and hyperspectral UAV imaging system for forest and agriculture applications

    NASA Astrophysics Data System (ADS)

    Mäkynen, Jussi; Saari, Heikki; Holmlund, Christer; Mannila, Rami; Antila, Tapani

    2012-06-01

    VTT Technical Research Centre of Finland has developed a Fabry-Perot Interferometer (FPI) based hyperspectral imager compatible with light weight UAV (Unmanned Aerial Vehicle) platforms (SPIE Proc. 74741, 8186B2). The FPI based hyperspectral imager was used in a UAV imaging campaign for forest and agriculture tests during the summer 2011 (SPIE Proc. 81743). During these tests high spatial resolution Color-Infrared (CIR) images and hyperspectral images were recorded on separate flights. The spectral bands of the CIR camera were 500 - 580 nm for the green band, 580 - 700 nm for the red band and 700 - 1000 nm for the near infrared band. For the summer 2012 flight campaign a new hyperspectral imager is currently being developed. A custom made CIR camera will also be used. The system which includes both the high spatial resolution Color-Infrared camera and a light weight hyperspectral imager can provide all necessary data with just one UAV flight over the target area. The new UAV imaging system contains a 4 Megapixel CIR camera which is used for the generation of the digital surface models and CIR mosaics. The hyperspectral data can be recorded in the wavelength range 500 - 900 nm at a resolution of 10 - 30 nm at FWHM. The resolution can be selected from approximate values of 10, 15, 20 or 30 nm at FWHM.

  15. 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 ...

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

    E-print Network

    Kollegala, Revathi

    2012-07-16

    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 ...

  17. Compact Infrared Hyperspectral Imaging Polarimeter Julia Craven, Michael W. Kudenov, Maryn G. Stapelbroek, Eustace L. Dereniak

    E-print Network

    Dereniak, Eustace L.

    Blvd., Tucson, AZ 85721 ABSTRACT A compact SWIR/MWIR infrared hyperspectral imaging polarimeter (IHIP of the interferogram over spectral regions that include the visible to short wave infrared (SWIR) using a Michelson

  18. A novel scheme for the compression and classification of hyperspectral images

    Microsoft Academic Search

    Bei Xie; T. Bose; E. Merenyi

    2009-01-01

    Since hyperspectral images are very large, it is desirable to compress them before transmission. After receiving the compressed image, decompression is applied before performing image classification and other operations. In this paper, a new processing scheme is proposed, where image transform and quantization are applied for image compression at the transmitter and classification is performed directly on the compressed data

  19. Principles and applications of hyperspectral imaging in quality evaluation of agro-food products: a review.

    PubMed

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

    2012-01-01

    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 is its aptitude to incorporate both spectroscopy and imaging techniques not only to make a direct assessment of different components simultaneously but also to locate the spatial distribution of such components in the tested products. Associated with multivariate analysis protocols, hyperspectral imaging shows a convinced attitude to be dominated in food authentication and analysis in future. The marvellous potential of the hyperspectral imaging technique as a non-destructive tool has driven the development of more sophisticated hyperspectral imaging systems in food applications. The aim of this review is to give detailed outlines about the theory and principles of hyperspectral imaging and to focus primarily on its applications in the field of quality evaluation of agro-food products as well as its future applicability in modern food industries and research. PMID:22823348

  20. Hyperspectral image compression based on the framework of DSC using 3D-wavelet and LDPC

    Microsoft Academic Search

    Jiaji Wu; Kun Jiang; Yong Fang; Licheng Jiao

    2009-01-01

    In this paper, we propose a method based on both 3D-wavelet transform and low-density parity-check codes to realize the compression of hyperspectral images on the framework of DSC (Distributed Source Coding). The new approach which combines DSC and 3D-wavelet transform technique makes it possible to realize low encoding complexity at the encoder and achieve efficient performance of hyperspectral image compression.

  1. A new architecture for hyperspectral image processing and analysis system: design and implementation

    Microsoft Academic Search

    Jianlin Yu; Xingtang Hu; Bing Zhang; Shunian Ning

    2003-01-01

    A new architecture for HIPAS (Hyperspectral Image Processing and Analysis System V2.0) was introduced in this paper which was modified and improved based on the first version of HIPAS V1.0. The comprehensive hyperspectral image analyzing system has been developed under VC++6.0 integrated development environment (IDE) and obtained perfect runtime efficiency and stability. The base architecture was specially designed and implemented

  2. ICER3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

    Microsoft Academic Search

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

    2006-01-01

    ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide loss- less and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decom- position structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating

  3. Spectral\\/spatial hyperspectral image compression in conjunction with virtual dimensionality

    Microsoft Academic Search

    Bharath Ramakrishna; Jing Wang; Chein-I. Chang; Antonio Plaza; Hsuan Ren; Chein-Chi Chang; Janet L. Jensen; James O. Jensen

    2005-01-01

    Hyperspectral image compression can be performed by either 3-D compression or spectral\\/spatial compression. It has been demonstrated that due to high spectral resolution hyperspectral image compression can be more effective if compression is carried out spectrally and spatially in two separate stages. One commonly used spectral\\/spatial compression implements principal components analysis (PCA) or wavelet for spectral compression followed by a

  4. Trench CCD image sensor

    Microsoft Academic Search

    T. Yamada; A. Fukumoto

    1989-01-01

    The authors describe and present simulation data on the device structure, process flow, and operation of the Trench CCD (charge coupled device), which is being developed to increase the resolution of solid-state image sensors. The device provides larger dynamic range, higher sensitivity, and no image lag together with great packing density. A charge transfer channel formed around a trench eliminates

  5. Hyperspectral image reconstruction for x-ray fluorescence tomography.

    PubMed

    Gürsoy, Do?a; Biçer, Tekin; Lanzirotti, Antonio; Newville, Matthew G; De Carlo, Francesco

    2015-04-01

    A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses a penalty term that has the effect of encouraging local continuity of model parameter estimates in both spatial and spectral dimensions simultaneously. The performance of the reconstruction method is demonstrated with experimental data acquired from a seed of arabidopsis thaliana collected at the 13-ID-E microprobe beamline at the Advanced Photon Source. The resulting element distribution estimates with the proposed approach show significantly better reconstruction quality than the conventional analytical inversion approaches, and allows for a high data compression factor which can reduce data acquisition times remarkably. In particular, this technique provides the capability to tomographically reconstruct full energy dispersive spectra without compromising reconstruction artifacts that impact the interpretation of results. PMID:25968737

  6. Hyperspectral image classification through bilayer graph-based learning.

    PubMed

    Gao, Yue; Ji, Rongrong; Cui, Peng; Dai, Qionghai; Hua, Gang

    2014-07-01

    Hyperspectral image classification with limited number of labeled pixels is a challenging task. In this paper, we propose a bilayer graph-based learning framework to address this problem. For graph-based classification, how to establish the neighboring relationship among the pixels from the high dimensional features is the key toward a successful classification. Our graph learning algorithm contains two layers. The first-layer constructs a simple graph, where each vertex denotes one pixel and the edge weight encodes the similarity between two pixels. Unsupervised learning is then conducted to estimate the grouping relations among different pixels. These relations are subsequently fed into the second layer to form a hypergraph structure, on top of which, semisupervised transductive learning is conducted to obtain the final classification results. Our experiments on three data sets demonstrate the merits of our proposed approach, which compares favorably with state of the art. PMID:24771580

  7. On combining spectral and spatial information of hyperspectral image for camouflaged target detecting

    NASA Astrophysics Data System (ADS)

    Hua, Wenshen; Liu, Xun; Yang, Jia

    2013-12-01

    Detecting enemy's targets and being undetectable play increasingly important roles in modern warfare. Hyperspectral images can provide large spectral range and high spectral resolution, which are invaluable in discriminating between camouflaged targets and backgrounds. As supervised classification requires prior knowledge which cannot be acquired easily, unsupervised classification usually is adopted to process hyperspectral images to detect camouflaged target. But one of its drawbacks—low detecting accuracy confines its application for camouflaged target detecting. Most research on the processing of hyperspectral image tends to focus exclusively on spectral domain and ignores spatial domain. However current hyperspectral image provides high spatial resolution which contains useful information for camouflaged target detecting. A new method combining spectral and spatial information is proposed to increase the detecting accuracy using unsupervised classification. The method has two steps. In the first step, a traditional unsupervised classifier (i.e. K-MEANS, ISODATA) is adopted to classify the hyperspectral image to acquire basic classifications or clusters. During the second step, a 3×3 model and spectral angle mapping are utilized to test the spatial character of the hyperspectral image. The spatial character is defined as spatial homogeneity and calculated by spectral angle mapping. Theory analysis and experiment shows the method is reasonable and efficient. Camouflaged targets are extracted from the background and different camouflaged targets are also recognized. And the proposed algorithm outperforms K-MEANS in terms of detecting accuracy, robustness and edge's distinction. This paper demonstrates the new method is meaningful to camouflaged targets detecting.

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

    PubMed Central

    Moroni, Monica; Dacquino, Carlo; Cenedese, Antonio

    2012-01-01

    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

  9. Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

    NASA Astrophysics Data System (ADS)

    Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

    2014-05-01

    The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

  10. Hyperspectral image classification based on spatial and spectral features and sparse representation

    NASA Astrophysics Data System (ADS)

    Yang, Jing-Hui; Wang, Li-Guo; Qian, Jin-Xi

    2014-12-01

    To minimize the low classification accuracy and low utilization of spatial information in traditional hyperspectral image classification methods, we propose a new hyperspectral image classification method, which is based on the Gabor spatial texture features and nonparametric weighted spectral features, and the sparse representation classification method (Gabor-NWSF and SRC), abbreviated GNWSF-SRC. The proposed (GNWSF-SRC) method first combines the Gabor spatial features and nonparametric weighted spectral features to describe the hyperspectral image, and then applies the sparse representation method. Finally, the classification is obtained by analyzing the reconstruction error. We use the proposed method to process two typical hyperspectral data sets with different percentages of training samples. Theoretical analysis and simulation demonstrate that the proposed method improves the classification accuracy and Kappa coefficient compared with traditional classification methods and achieves better classification performance.

  11. Geometric correction method of rotary scanning hyperspectral image in agriculture application

    NASA Astrophysics Data System (ADS)

    Wan, Peng; Yang, Guijun; Xu, Bo; Feng, Haikuan; Yu, Haiyang

    2015-04-01

    In order to meet the demand of farmland plot experiments hyperspectral images acquisition, an equipment that incorporating an aerial lift vehicle with hyperspectral imager was proposed. In this manner, high spatial resolution (in millimeter) imageries were collected, which meets the need of spatial resolution on farm experiments, but also improves the efficiency of image acquisition. In allusion to the image circular geometric distortion which produced by telescopic arm rotation, an image rectification method that based on mounted position and orientation system was proposed. Experimental results shows that the image rectification method is effective.

  12. A hyperspectral image optimizing method based on sub-pixel MTF analysis

    NASA Astrophysics Data System (ADS)

    Wang, Yun; Li, Kai; Wang, Jinqiang; Zhu, Yajie

    2015-04-01

    Hyperspectral imaging is used to collect tens or hundreds of images continuously divided across electromagnetic spectrum so that the details under different wavelengths could be represented. A popular hyperspectral imaging methods uses a tunable optical band-pass filter settled in front of the focal plane to acquire images of different wavelengths. In order to alleviate the influence of chromatic aberration in some segments in a hyperspectral series, in this paper, a hyperspectral optimizing method uses sub-pixel MTF to evaluate image blurring quality was provided. This method acquired the edge feature in the target window by means of the line spread function (LSF) to calculate the reliable position of the edge feature, then the evaluation grid in each line was interpolated by the real pixel value based on its relative position to the optimal edge and the sub-pixel MTF was used to analyze the image in frequency domain, by which MTF calculation dimension was increased. The sub-pixel MTF evaluation was reliable, since no image rotation and pixel value estimation was needed, and no artificial information was introduced. With theoretical analysis, the method proposed in this paper is reliable and efficient when evaluation the common images with edges of small tilt angle in real scene. It also provided a direction for the following hyperspectral image blurring evaluation and the real-time focal plane adjustment in real time in related imaging system.

  13. Operational multi-angle hyperspectral remote sensing for feature detection

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R.; Brooks, Donald K.

    2013-10-01

    Remote sensing results of land and water surfaces from airborne and satellite platforms are dependent upon the illumination geometry and the sensor viewing geometry. Correction of pushbroom hyperspectral imagery can be achieved using bidirectional reflectance factors (BRF's) image features based upon their multi-angle hyperspectral signatures. Ground validation of features and targets utilize non-imaging sensors such as hemispherical goniometers. In this paper, a new linear translation based hyperspectral imaging goniometer system is described. Imagery and hyperspectral signatures obtained from a rotation stage platform and the new linear non-hemispherical goniometer system shows applications and a multi-angle correction approach for multi-angle hyperspectral pushbroom imagery corrections. Results are presented in a manner in order to describe how ground, vessel and airborne based multi-angle hyperspectral signatures can be applied to operational hyperspectral image acquisition by the calculation of hyperspectral anisotropic signature imagery. The results demonstrate the analysis framework from the systems to water and coastal vegetation for exploitation of surface and subsurface feature or target detection based using the multi-angle radiative transfer based BRF's. The hyperspectral pushbroom multi-angle analysis methodology forms a basis for future multi-sensor based multi-angle change detection algorithms.

  14. Noise-Resistant Wavelet-Based Bayesian Fusion of Multispectral and Hyperspectral Images

    Microsoft Academic Search

    Yifan Zhang; Steve De Backer; Paul Scheunders

    2009-01-01

    In this paper, a technique is presented for the fusion of multispectral (MS) and hyperspectral (HS) images to enhance the spatial resolution of the latter. The technique works in the wavelet domain and is based on a Bayesian estimation of the HS image, assuming a joint normal model for the images and an additive noise imaging model for the HS

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

    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.

  17. Hyper-spectral imaging of aircraft exhaust plumes

    NASA Astrophysics Data System (ADS)

    Bowen, Spencer; Bradley, Kenneth; Gross, Kevin; Perram, Glen; Marciniak, Michael

    2008-10-01

    An imaging Fourier-transform spectrometer has been used to determine low spatial resolution temperature and chemical species concentration distributions of aircraft jet engine exhaust plumes. An overview of the imaging Fourier transform spectrometer and the methodology of the project is presented. Results to date are shared and future work is discussed. Exhaust plume data from a Turbine Technologies, LTD, SR-30 turbojet engine at three engine settings was collected using a Telops Field-portable Imaging Radiometric Spectrometer Technology Mid-Wave Extended (FIRST-MWE). Although the plume exhibited high temporal frequency fluctuations, temporal averaging of hyper-spectral data-cubes produced steady-state distributions, which, when co-added and Fourier transformed, produced workable spectra. These spectra were then reduced using a simplified gaseous effluent model to fit forward-modeled spectra obtained from the Line-By-Line Radiative Transfer Model (LBLRTM) and the high-resolution transmission (HITRAN) molecular absorption database to determine approximate temperature and concentration distributions. It is theorized that further development of the physical model will produce better agreement between measured and modeled data.

  18. SPATIAL STRUCTURES DETECTION IN HYPERSPECTRAL IMAGES USING MATHEMATICAL MORPHOLOGY

    E-print Network

    Angulo,Jesús

    The aim of this paper is to apply genuine hyperspectral math- ematical morphology to extract spatial, Supervised Learning, Spatial/Spectral Feature Extraction, Hyperspectral Imagery. 1. INTRODUCTION be referred as dilations and erosions in the mathematical morphology framework [9], i.e., the pair of vector

  19. Hyperspectral Image Classification Using Dictionary-Based Sparse Representation

    Microsoft Academic Search

    Yi Chen; Nasser M. Nasrabadi; Trac D. Tran

    2011-01-01

    A new sparsity-based algorithm for the classification of hyperspectral imagery is proposed in this paper. The proposed algorithm relies on the observation that a hyperspectral pixel can be sparsely represented by a linear combination of a few training samples from a structured dictionary. The sparse representation of an unknown pixel is expressed as a sparse vector whose nonzero entries correspond

  20. Quantitative Vibrational Imaging by Hyperspectral Stimulated Raman Scattering Microscopy and Multivariate Curve Resolution Analysis

    PubMed Central

    Zhang, Delong; Wang, Ping; Slipchenko, Mikhail N.; Ben-Amotz, Dor; Weiner, Andrew M.; Cheng, Ji-Xin

    2013-01-01

    Spectroscopic imaging has been an increasingly critical approach for unveiling specific molecules in biological environments. Towards this goal, we demonstrate hyperspectral stimulated Raman loss (SRL) imaging by intra-pulse spectral scanning through a femtosecond pulse shaper. The hyperspectral stack of SRL images is further analyzed by a multivariate curve resolution (MCR) method to reconstruct quantitative concentration images for each individual component and retrieve the corresponding vibrational Raman spectra. Using these methods, we demonstrate quantitative mapping of dimethyl sulfoxide concentration in aqueous solutions and in fat tissue. Moreover, MCR is performed on SRL images of breast cancer cells to generate maps of principal chemical components along with their respective vibrational spectra. These results show the great capability and potential of hyperspectral SRL microscopy for quantitative imaging of complicated biomolecule mixtures through resolving overlapped Raman bands. PMID:23198914

  1. Wavelet compression techniques for hyperspectral data

    NASA Technical Reports Server (NTRS)

    Evans, Bruce; Ringer, Brian; Yeates, Mathew

    1994-01-01

    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.

  2. Implementation of Low-Complexity Principal Component Analysis for Remotely Sensed Hyperspectral-Image Compression

    Microsoft Academic Search

    Qian Du; Wei Zhu; James E. Fowler

    2007-01-01

    Remotely sensed hyperspectral imagery has vast data volume, for which data compression is a necessary processing step. Spectral decorrelation is critical to successful hyperspectral-image compression. Principal component analysis (PCA) is well-known for its superior performance in data decorrelation, and it has been demonstrated that using PCA for spectral decorrelation can yield rate-distortion and data-analysis performance superior to other widely used

  3. Towards Real-Time Compression of Hyperspectral Images Using Virtex-II FPGAs

    Microsoft Academic Search

    Antonio Plaza

    2007-01-01

    Hyperspectral imagery is a new type of high-dimensional image data which is now used in many Earth-based and planetary exploration\\u000a applications. Many efforts have been devoted to designing and developing compression algorithms for hyperspectral imagery.\\u000a Unfortunately, most available approaches have largely overlooked the impact of mixed pixels and subpixel targets, which can\\u000a be accurately modeled and uncovered by resorting to

  4. Hyperspectral extensions in the MuSES signature code

    Microsoft Academic Search

    Wellesley Pereira; David Less; Leonard Rodriguez; Allen Curran; Uri Bernstein; Yit-Tsi Kwan

    2008-01-01

    In recent years, military operations have seen an increasing demand for high-fidelity predictive ground target signature modeling in the hyperspectral thermal IR bands (2 to 25 mum). Simulating hyperspectral imagery of large scenes has become a necessary component in evaluating ATR algorithms due to the prohibitive costs and the large volume of data amassed by multi-band imaging sensors. To address

  5. Hyperspectral imaging applied to complex particulate solids systems

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Serranti, Silvia

    2008-04-01

    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.

  6. Gas plume quantification in downlooking hyperspectral longwave infrared images

    NASA Astrophysics Data System (ADS)

    Turcotte, Caroline S.; Davenport, Michael R.

    2010-10-01

    Algorithms have been developed to support quantitative analysis of a gas plume using down-looking airborne hyperspectral long-wave infrared (LWIR) imagery. The resulting gas quantification "GQ" tool estimates the quantity of one or more gases at each pixel, and estimates uncertainty based on factors such as atmospheric transmittance, background clutter, and plume temperature contrast. GQ uses gas-insensitive segmentation algorithms to classify the background very precisely so that it can infer gas quantities from the differences between plume-bearing pixels and similar non-plume pixels. It also includes MODTRAN-based algorithms to iteratively assess various profiles of air temperature, water vapour, and ozone, and select the one that implies smooth emissivity curves for the (unknown) materials on the ground. GQ then uses a generalized least-squares (GLS) algorithm to simultaneously estimate the most likely mixture of background (terrain) material and foreground plume gases. Cross-linking of plume temperature to the estimated gas quantity is very non-linear, so the GLS solution was iteratively assessed over a range of plume temperatures to find the best fit to the observed spectrum. Quantification errors due to local variations in the camera-topixel distance were suppressed using a subspace projection operator. Lacking detailed depth-maps for real plumes, the GQ algorithm was tested on synthetic scenes generated by the Digital Imaging and Remote Sensing Image Generation (DIRSIG) software. Initial results showed pixel-by-pixel gas quantification errors of less than 15% for a Freon 134a plume.

  7. Hyperspectral imaging for detection of scab in wheat

    NASA Astrophysics Data System (ADS)

    Delwiche, Stephen R.; Kim, Moon S.

    2000-12-01

    Scab (Fusarium head blight) is a disease that causes wheat kernels to be shriveled, underweight, and difficult to mill. Scab is also a health concern because of the possible concomitant production of the mycotoxin deoxynivalenol. Current official inspection procedures entail manual human inspection. A study was undertaken to explore the possibility of detecting scab-damaged wheat kernels by machine vision. A custom-made hyperspectral imaging system, possessing a wavelength range of 425 to 860 nm with neighboring bands 3.7 nm apart, a spatial resolution of 0.022 mm2/pixel, and 16-bit per pixel dynamic range, gathered images of non-touching kernels from three wheat varieties. Each variety was represented by 32 normal and 32 scab-damaged kernels. From a search of wavelengths that could be used to separate the two classes (normal vs. scab), a linear discriminant function was constructed from the best R((lambda) 1)/R((lambda) 2), based on the assumption of a multivariate normal distribution for each class and the pooling of the covariance error that averaged between 2 and 17%, dependent on wheat variety. With expansion to the testing of more varieties, a two-to-four wavelength machine vision system appears to be a feasible alternative to manual inspection.

  8. Optimal Segmentation Strategy for Compact Representation of Hyperspectral Image Cubes

    SciTech Connect

    Paglieroni, D; Roberts, R

    2000-02-08

    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 novel approach for automatically and efficiently generating a particular type of compact hypercube representation, referred to as a supercube. The hypercube is segmented into regions that contain pixels with similar spectral shapes that are spatially connected, and the pixel connectivity constraint can be relaxed. Thresholds of similarity in spectral shape between pairs of pixels are derived directly from the hypercube data. One superpixel is generated for each region as some linear combination of pixels belonging to that region. The superpixels are optimal in the sense that the linear combination coefficients are computed so as to minimize the level of noise. Each hypercube pixel is represented in the supercube by applying a gain and bias to the superpixel assigned to the region containing that pixel. Examples are provided.

  9. Visible hyperspectral imaging evaluating the cutaneous response to ultraviolet radiation

    NASA Astrophysics Data System (ADS)

    Ilias, Michail A.; Häggblad, Erik; Anderson, Chris; Salerud, E. Göran

    2007-02-01

    In vivo diagnostics of skin diseases as well as understanding of the skin biology constitute a field demanding characterization of physiological and anatomical parameters. Biomedical optics has been successfully used, to qualitatively and quantitatively estimate the microcirculatory conditions of superficial skin. Capillaroscopy, laser Doppler techniques and spectroscopy, all elucidate different aspects of microcirculation, e.g. capillary anatomy and distribution, tissue perfusion and hemoglobin oxygenation. We demonstrate the use of a diffuse reflectance hyperspectral imaging system for spatial and temporal characterization of tissue oxygenation, important to skin viability. The system comprises: light source, liquid crystal tunable filter, camera objective, CCD camera, and the decomposition of the spectral signature into relative amounts of oxy- and deoxygenized hemoglobin as well as melanin in every pixel resulting in tissue chromophore images. To validate the system, we used a phototesting model, creating a graded inflammatory response of a known geometry, in order to evaluate the ability to register spatially resolved reflectance spectra. The obtained results demonstrate the possibility to describe the UV inflammatory response by calculating the change in tissue oxygen level, intimately connected to a tissue's metabolism. Preliminary results on the estimation of melanin content are also presented.

  10. Investigation of NIR hyperspectral imaging for discriminating melamine in milk powder

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

    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.

  11. Fusion of Hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction

    Microsoft Academic Search

    G. A. Licciardi; M. M. Khan; J. Chanussot; A. Montanvert; L. Condat; C. Jutten

    2011-01-01

    This paper presents a novel method for the enhancement of spatial quality of Hyperspectral (HS) images while making use of a high resolution panchromatic (PAN) image. Due to the high number of bands the application of a pansharpening technique to HS images may result in an increase of the computational load and complexity. Thus a dimensionality reduction preprocess, compressing the

  12. Multiband semifragile watermarking for multi and hyperspectral images based on iterative tree structured vector quantization

    Microsoft Academic Search

    Jordi Serra; David Megías; Jordi Herrera-Joancomarti; Julià Minguillón

    2006-01-01

    In this paper a novel semifragile watermarking scheme for images with multiple bands is presented. We propose to use the remote sensing image as a whole, using a vector quantization approach, instead of processing each band separately. This scheme uses the signature of the multispectral or hyperspectral image to embed the mark in it and detects a modification of the

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

    PubMed Central

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

    2014-01-01

    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

  14. Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

    Microsoft Academic Search

    X. Rosalind Wang; Adrian J. Brown; B. Upcroft

    2005-01-01

    In this paper, we apply the incremental EM method to Bayesian network classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

    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.

  16. NASA image-based geological expert system development project for hyperspectral image analysis

    NASA Technical Reports Server (NTRS)

    Chiou, W. C., Sr.

    1985-01-01

    The NASA image-based geological expert system was applied to analyze remotely sensed hyperspectral image data. The major objective is for geologists to identify the earth surface mineral properties directly from the airborne and spaceborne imaging spectrometer data. With certain constraints, it is shown that the system can identify correctly different classes of mineral. It has the built-in learning paradigm to enhance the confidence factor of mineral identification. A very powerful natural language system was incorporated as the user-friendly front end, and the concurrent processing efficiency of the frame-based knowledge representation in the hypercube microsupercomputer simulation was tested.

  17. A comparison of noise reduction methods for image enhancement in classification of hyperspectral imagery

    Microsoft Academic Search

    Shirley Morillo-Contreras; Miguel Velez-Reyes; Shawn D. Hunt

    2005-01-01

    A particular challenge in hyperspectral remote sensing of benthic habitats is that the signal exiting from the water is a small component of the overall signal received at the satellite or airborne sensor. Therefore, in order to be able to discriminate different ecological areas in benthic habitats, it is important to have a high signal to noise ratio (SNR). The

  18. Multivariate curve resolution for the analysis of remotely sensed thermal infrared hyperspectral images.

    SciTech Connect

    Haaland, David Michael; Stork, Christopher Lyle; Keenan, Michael Robert

    2004-07-01

    While hyperspectral imaging systems are increasingly used in remote sensing and offer enhanced scene characterization relative to univariate and multispectral technologies, it has proven difficult in practice to extract all of the useful information from these systems due to overwhelming data volume, confounding atmospheric effects, and the limited a priori knowledge regarding the scene. The need exists for the ability to perform rapid and comprehensive data exploitation of remotely sensed hyperspectral imagery. To address this need, this paper describes the application of a fast and rigorous multivariate curve resolution (MCR) algorithm to remotely sensed thermal infrared hyperspectral images. Employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, it is demonstrated that MCR can successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. We take a semi-synthetic approach to obtaining image data containing gas plumes by adding emission gas signals onto real hyperspectral images. MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of an ammonia gas plume component added near the minimum detectable quantity.

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

    PubMed Central

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

    2014-01-01

    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

  20. Error-Resilient and Low-Complexity Onboard Lossless Compression of Hyperspectral Images by Means of Distributed Source Coding

    Microsoft Academic Search

    Andrea Abrardo; Mauro Barni; Enrico Magli; Filippo Nencini

    2010-01-01

    In this paper, we propose a lossless compression algorithm for hyperspectral images inspired by the distributed-source-coding (DSC) principle. DSC refers to separate compression and joint decoding of correlated sources, which are taken as adjacent bands of a hyperspectral image. This concept is used to design a compression scheme that provides error resilience, very low complexity, and good compression performance. These

  1. AN EFFICIENT COMPRESSION ALGORITHM FOR HYPERSPECTRAL IMAGES BASED ON A MODIFIED CODING FRAMEWORK OF H.264\\/AVC

    Microsoft Academic Search

    Guizhong Liu; Fan Zhao; Guofu Qu

    In this paper, an efficient compression algorithm for hyperspectral images is proposed, which is based on a modified coding framework of H.264\\/AVC. In virtue of the flexible and diverse prediction modes of H264\\/AVC, the most suitable ones are assigned for the macroblocks ( 16 16× pixel regions of a band) of the hyperspectral images other than for the whole band

  2. HYPERSPECTRAL/MULTISPECTRAL LINE-SCAN IMAGING SYSTEM FOR AUTOMATED POULTRY CARCASS INSPECTION APPLICATIONS FOR FOOD SAFETY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral/multispectral line-scan imaging system was developed for differentiation of wholesome and systemically diseased chickens. In-plant testing was conducted for chickens on a commercial evisceration line moving at a speed of 70 birds per minute. Hyperspectral image data was acquired fo...

  3. Early detection of disease-oriented state from hyperspectral tongue images with principal component analysis and vector rotation

    Microsoft Academic Search

    Satoshi Yamamoto; Norimichi Tsumura; Keiko Ogawa-Ochiai; Toshiya Nakaguchi; Yuji Kasahara; Takao Namiki; Yoichi Miyake

    2010-01-01

    In this article, we propose an effective color-processing algorithm to analyze the hyperspectral image of the tongue and its application to preventive medicine by the concept of Japanese traditional herbal medicine (Kampo medicine). Kampo medicine contains a number of concepts useful for preventive medicine such as “Mibyou” - disease-oriented state - signs of abnormalities. Hyperspectral images of the tongue were

  4. CCD imaging sensors

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

    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.

  5. Hierarchical clustering approach for unsupervised image classification of hyperspectral data

    Microsoft Academic Search

    Sanghoon Lee; Melba M. Crawford

    2004-01-01

    A multistage hierarchical clustering technique, which is an unsupervised technique, has been proposed in this paper for classifying the hyperspectral data. The multistage algorithm consists of two stages. The \\

  6. Survey of hyperspectral image denoising methods based on tensor decompositions

    NASA Astrophysics Data System (ADS)

    Lin, Tao; Bourennane, Salah

    2013-12-01

    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.

  7. Hyperspectral imaging based techniques applied to polluted clay characterization

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Serranti, Silvia

    2006-10-01

    Polluted soils analysis and characterization is one of the basic step to perform in order to collect all the information to design and set-up correct soil reclamation strategies. Soil analysis is usually performed through "in-situ" sampling and laboratory analysis. Such an approach is usually quite expensive and does not allow to reach a direct and detailed knowledge of large areas for the intrinsic limits (high costs) linked to direct sampling and polluting elements detection. As a consequence numerical strategies are applied to extrapolate, starting from a discrete set of data, that is those related to collected samples, information about the contamination level of areas not directly interested by physical sampling. These models are usually very difficult to handle both for the intrinsic variability characterizing the media (soils) and for the high level of interactions between polluting agents, soil characteristics (organic matter content, size class distribution of the inorganic fraction, composition, etc.) and environmental conditions (temperature, humidity, presence of vegetation, human activities, etc.). Aim of this study, starting from previous researches addressed to evaluate the potentialities of hyperspectral imaging approach in polluting soil characterization, was to evaluate the results obtainable in the investigation of an "ad hoc" polluted benthonic clay, usually utilized in rubbish dump, in order to define fast and reliable control strategies addressed to monitor the status of such a material in terms of insulation.

  8. Hyperspectral molecular imaging of multiple receptors using immunolabeled plasmonic nanoparticles

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    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.

  9. Hyperspectral imaging based procedures applied to bottom ash characterization

    NASA Astrophysics Data System (ADS)

    Bonifazi, Giuseppe; Serranti, Silvia

    2007-09-01

    Bottom ash from Municipal Solid Waste Incinerators (MSWIs) is mainly land filled or used as material for the foundation of road in European countries. Bottom ash is usually first crushed to below 40 mm and separated magnetically to recover the steel scrap. The remaining material contains predominantly sand, sinters and pieces of stone, glass and ceramics, which could be used as building material if strict technical and environmental requirements are respected. The main problem is the presence of residual organic matter in the ash and the large surface area presented by the fine fraction that creates leaching values, for elements such as copper, that are above the accepted levels for standard building materials. Main aim of the study was to evaluate the possibility offered by hyperspectral imaging to identify organic matter inside the residues in order to develop control/selection strategies to be implemented inside the bottom ash recycling plant. Reflectance spectra of selected bottom ash samples have been acquired in the VIS-NIR field (400- 1000 nm). Results showed as the organic content of the different samples influences the spectral signatures, in particular an inverse correlation between reflectance level and organic matter content was found.

  10. Maize kernel hardness classification by near infrared (NIR) hyperspectral imaging and multivariate data analysis.

    PubMed

    Williams, Paul; Geladi, Paul; Fox, Glen; Manley, Marena

    2009-10-27

    The use of near infrared (NIR) hyperspectral imaging and hyperspectral image analysis for distinguishing between hard, intermediate and soft maize kernels from inbred lines was evaluated. NIR hyperspectral images of two sets (12 and 24 kernels) of whole maize kernels were acquired using a Spectral Dimensions MatrixNIR camera with a spectral range of 960-1662 nm and a sisuChema SWIR (short wave infrared) hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm. Exploratory principal component analysis (PCA) was used on absorbance images to remove background, bad pixels and shading. On the cleaned images, PCA could be used effectively to find histological classes including glassy (hard) and floury (soft) endosperm. PCA illustrated a distinct difference between glassy and floury endosperm along principal component (PC) three on the MatrixNIR and PC two on the sisuChema with two distinguishable clusters. Subsequently partial least squares discriminant analysis (PLS-DA) was applied to build a classification model. The PLS-DA model from the MatrixNIR image (12 kernels) resulted in root mean square error of prediction (RMSEP) value of 0.18. This was repeated on the MatrixNIR image of the 24 kernels which resulted in RMSEP of 0.18. The sisuChema image yielded RMSEP value of 0.29. The reproducible results obtained with the different data sets indicate that the method proposed in this paper has a real potential for future classification uses. PMID:19808104

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    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.

  12. Potential of hyperspectral imaging for rapid prediction of hydroxyproline content in chicken meat.

    PubMed

    Xiong, Zhenjie; Sun, Da-Wen; Xie, Anguo; Han, Zhong; Wang, Lu

    2015-05-15

    In this study, the potential of hyperspectral imaging (HSI) for predicting hydroxyproline content in chicken meat was investigated. Spectral data contained in the hyperspectral images (400-1000 nm) of chicken meat was extracted, and a partial least square regression (PLSR) model was then developed for predicting hydroxyproline content. The model yielded acceptable results with regression coefficient in prediction (Rp) of 0.874 and root mean error squares in prediction (RMESP) of 0.046. Based on the eight optimal wavelengths selected by regression coefficients (RC) from the PLSR model, a new RC-PLSR model was built and good results were shown with high Rp of 0.854 and low RMSEP of 0.049. Finally, distribution maps of hydroxyproline were created by transferring the RC-PLSR model to each pixel in the hyperspectral images. The results demonstrated that HSI has the capability for rapid and non-destructive determination of hydroxyproline content in chicken meat. PMID:25577100

  13. Auxiliary Sensors For "Pushbroom" Imaging

    NASA Technical Reports Server (NTRS)

    Jones, Kenneth L.

    1992-01-01

    Proposed subsystem of small auxiliary imaging sensors yields additional data on motion of linear imaging sensor scanned across scene perpendicular to its length. Sensors yield data on components of motion to which inertial, radar, and air-speed detectors insensitive. Additional data on motion enhances geometric fidelity.

  14. Wavefront image sensor chip

    PubMed Central

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

    2010-01-01

    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

  15. Preliminary study of detection of buried landmines using a programmable hyperspectral imager

    Microsoft Academic Search

    John E. McFee; Herb T. Ripley; Roger Buxton; Andrew M. Thriscutt

    1996-01-01

    Experiments were conducted to determine if buried mines could be detected by measuring the change in reflectance spectra of vegetation above mine burial sites. Mines were laid using hand methods and simulated mechanical methods and spectral images were obtained over a three month period using a casi hyperspectral imager scanned from a personnel lift. Mines were not detectable by measurement

  16. 3D optical sectioning with a new hyperspectral confocal fluorescence imaging system.

    SciTech Connect

    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

    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.

  17. Interference and noise-adjusted principal component analysis for hyperspectral image compression

    Microsoft Academic Search

    Qian Du

    2004-01-01

    Hyperspectral images have high spectral resolution that enables accurate object classification. But its vast data volume brings about problems in data transmission and data storage. How to reduce the data volume while keeping the important information for the following data analysis is a challenging task. Principal Components Analysis (PCA) is a typical method for data compression, which re-arranges image information

  18. Semisupervised Hyperspectral Image Segmentation Using Multinomial Logistic Regression With Active Learning

    Microsoft Academic Search

    Jun Li; José M. Bioucas-Dias; Antonio Plaza

    2010-01-01

    This paper presents a new semisupervised segmentation algorithm, suited to high-dimensional data, of which remotely sensed hyperspectral image data sets are an example. The algorithm implements two main steps: 1) semisupervised learning of the posterior class distributions followed by 2) segmentation, which infers an image of class labels from a posterior distribution built on the learned class distributions and on

  19. ESTIMATING WITHIN-FIELD VARIATIONS IN SOIL PROPERTIES FROM AIRBORNE HYPERSPECTRAL IMAGES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The ability of hyperspectral image (HSI) data to provide estimates of soil electrical conductivity (EC) and soil fertility levels without requiring extensive field data collection was investigated. Bare soil images were acquired using a prism grating pushbroom scanner in April 2000 and May 2001 for ...

  20. Sub-pixel Hyperspectral Image Analysis using Piece-wise Convex Spectral Unmixing

    E-print Network

    Pivovarov, Peter

    for detecting and classifying dif- ferent materials in an image scene down to the sub-pixel level. Sub-pixel hyperspectral image analysis can be applied to a wide range of applica- tions including remote sensing, landmine and explosive object detection, trace explosives detection and medical applications such as tissue or cell

  1. ASSESSING THE MATURITY OF APPLES BY INTEGRATING HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE IMAGING TECHNIQUES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fluorescence and reflectance are two different forms of light interaction with the matter, and they can be complementary in measuring fruit maturity and quality. In this research, a hyperspectral imaging system was used to acquire both reflectance and fluorescence images from 'Golden Delicious' appl...

  2. Detection of melamine in milk powders based on NIR hyperspectral imaging and spectral similarity analyses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Melamine (2,4,6-triamino-1,3,5-triazine) contamination of food has become an urgent and broadly recognized topic as a result of several food safety scares in the past five years. Hyperspectral imaging techniques that combine the advantages of spectroscopy and imaging have been widely applied for a v...

  3. Cloud masking in remotely sensed hyperspectral images using linear and nonlinear spectral mixture analysis

    E-print Network

    Plaza, Antonio J.

    The presence of clouds in satellite spectral images prevents adequate characterization of land coverCloud masking in remotely sensed hyperspectral images using linear and nonlinear spectral mixture (1) GPDS, Dept. of Electronic Eng., University of Valencia (Spain) (2) Dept. of Computer Science

  4. Evaluation of Hyperspectral Imaging and Predictive Modeling to Determine Fertility and Development of Broiler Hatching Eggs

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A hyperspectral imaging system and a predictive modeling technique was evaluated for determining fertility and early embryo development of broiler chicken hatching eggs. Twenty-four broiler-strain eggs were collected (12 fertile, 12 infertile) for each of 8 replicate trials (n=192) and imaged on Da...

  5. A CCD Camera?based Hyperspectral Imaging System for Stationary and Airborne Applications

    Microsoft Academic Search

    Chenghai Yang; James H. Everitt; Michael R. Davis; Chengye Mao

    2003-01-01

    This paper describes a CCD (charge coupled device) camera?based hyperspectral imaging system designed for both stationary and airborne remote sensing applications. The system consists of a high performance digital CCD camera, an imaging spectrograph, an optional focal plane scanner, and a PC computer equipped with a frame grabbing board and camera utility software. The CCD camera provides 1280(h) × 1024(v)

  6. Research on dimension reduction method for hyperspectral remote sensing image based on global mixture coordination factor analysis

    NASA Astrophysics Data System (ADS)

    Wang, S.; Wang, C.

    2015-06-01

    Over the past thirty years, the hyperspectral remote sensing technology is attracted more and more attentions by the researchers. The dimension reduction technology for hyperspectral remote sensing image data is one of the hotspots in current research of hyperspectral remote sensing. In order to solve the problems of nonlinearity, the high dimensions and the redundancy of the bands that exist in the hyperspectral data, this paper proposes a dimension reduction method for hyperspectral remote sensing image data based on the global mixture coordination factor analysis. In the first place, a linear low dimensional manifold is obtained from the nonlinear and high dimensional hyperspectral image data by mixture factor analysis method. In the second place, the parameters of linear low dimensional manifold are estimated by the EM algorithm of find a local maximum of the data log-likelihood. In the third place, the manifold is aligned to a global parameterization by the global coordinated factor analysis model and then the lowdimension image data of hyperspectral image data is obtained at last. Through the comparison of different dimensionality reduction method and different classification method for the low-dimensional data, the result illuminates the proposed method can retain maximum spectral information in hyperspectral image data and can eliminate the redundant among bands.

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

    PubMed

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

    2014-07-01

    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

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

    SciTech Connect

    Gentry, S.M.; Levenson, R.

    1999-01-21

    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.

  9. Target detection algorithm for airborne thermal hyperspectral data

    NASA Astrophysics Data System (ADS)

    Marwaha, R.; Kumar, A.; Raju, P. L. N.; Krishna Murthy, Y. V. N.

    2014-11-01

    Airborne hyperspectral imaging is constantly being used for classification purpose. But airborne thermal hyperspectral image usually is a challenge for conventional classification approaches. The Telops Hyper-Cam sensor is an interferometer-based imaging system that helps in the spatial and spectral analysis of targets utilizing a single sensor. It is based on the technology of Fourier-transform which yields high spectral resolution and enables high accuracy radiometric calibration. The Hypercam instrument has 84 spectral bands in the 868 cm-1 to 1280 cm-1 region (7.8 ?m to 11.5 ?m), at a spectral resolution of 6 cm-1 (full-width-half-maximum) for LWIR (long wave infrared) range. Due to the Hughes effect, only a few classifiers are able to handle high dimensional classification task. MNF (Minimum Noise Fraction) rotation is a data dimensionality reducing approach to segregate noise in the data. In this, the component selection of minimum noise fraction (MNF) rotation transformation was analyzed in terms of classification accuracy using constrained energy minimization (CEM) algorithm as a classifier for Airborne thermal hyperspectral image and for the combination of airborne LWIR hyperspectral image and color digital photograph. On comparing the accuracy of all the classified images for airborne LWIR hyperspectral image and combination of Airborne LWIR hyperspectral image with colored digital photograph, it was found that accuracy was highest for MNF component equal to twenty. The accuracy increased by using the combination of airborne LWIR hyperspectral image with colored digital photograph instead of using LWIR data alone.

  10. Hyperspectral image compression using entropy-constrained predictive trellis coded quantization.

    PubMed

    Abousleman, G P; Marcellin, M W; Hunt, B R

    1997-01-01

    A training-sequence-based entropy-constrained predictive trellis coded quantization (ECPTCQ) scheme is presented for encoding autoregressive sources. For encoding a first-order Gauss-Markov source, the mean squared error (MSE) performance of an eight-state ECPTCQ system exceeds that of entropy-constrained differential pulse code modulation (ECDPCM) by up to 1.0 dB. In addition, a hyperspectral image compression system is developed, which utilizes ECPTCQ. A hyperspectral image sequence compressed at 0.125 b/pixel/band retains an average peak signal-to-noise ratio (PSNR) of greater than 43 dB over the spectral bands. PMID:18282949

  11. The design of a wide-angle and wide spectral range pushbroom hyperspectral imager

    NASA Astrophysics Data System (ADS)

    Qi, Hongxing; Yao, Bo; Wang, Jianyu; Yuan, Liyin

    2014-11-01

    We present the design of a compact, wide-angle pushbroom hyperspectral imager with a 42-deg wide field of view and a broadband response that covers the spectral range 450 to 2500 nm and provides a spectral sampling of 10 nm on SWIR and 5nm on VISNIR. The hyperspectral imager has finished the remote sensing experiment by emplaning on the YUN-12,and its performance meets the design parameters. The design is the high level technology and serves as an example for illustrating the design principles specific to this type of system.

  12. Quantification and spatial characterization of moisture and NaCl content of Iberian dry-cured ham slices using NIR hyperspectral imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging technology is increasingly regarded as a powerful tool for the classification and spatial quantification of a wide range of agrofood product properties. Taking into account the difficulties involved in validating hyperspectral calibrations, the models constructed here proved mo...

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

    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.

  14. Comparison of Spectral and Image Morphological Analysis for Egg Early Hatching Property Detection Based on Hyperspectral Imaging

    PubMed Central

    Zhang, Wei; Pan, Leiqing; Tu, Kang; Zhang, Qiang; Liu, Ming

    2014-01-01

    The use of non-destructive methods to detect egg hatching properties could increase efficiency in commercial hatcheries by saving space, reducing costs, and ensuring hatching quality. For this purpose, a hyperspectral imaging system was built to detect embryo development and vitality using spectral and morphological information of hatching eggs. A total of 150 green shell eggs were used, and hyperspectral images were collected for every egg on day 0, 1, 2, 3 and 4 of incubation. After imaging, two analysis methods were developed to extract egg hatching characteristic. Firstly, hyperspectral images of samples were evaluated using Principal Component Analysis (PCA) and only one optimal band with 822 nm was selected for extracting spectral characteristics of hatching egg. Secondly, an image segmentation algorithm was applied to isolate the image morphologic characteristics of hatching egg. To investigate the applicability of spectral and image morphological analysis for detecting egg early hatching properties, Learning Vector Quantization neural network (LVQNN) was employed. The experimental results demonstrated that model using image morphological characteristics could achieve better accuracy and generalization than using spectral characteristic parameters, and the discrimination accuracy for eggs with embryo development were 97% at day 3, 100% at day 4. In addition, the recognition results for eggs with weak embryo development reached 81% at day 3, and 92% at day 4. This study suggested that image morphological analysis was a novel application of hyperspectral imaging technology to detect egg early hatching properties. PMID:24551130

  15. Real-time hyperspectral fluorescence imaging of pancreatic ?-cell dynamics with the image mapping spectrometer

    PubMed Central

    Elliott, Amicia D.; Gao, Liang; Ustione, Alessandro; Bedard, Noah; Kester, Robert; Piston, David W.; Tkaczyk, Tomasz S.

    2012-01-01

    Summary The development of multi-colored fluorescent proteins, nanocrystals and organic fluorophores, along with the resulting engineered biosensors, has revolutionized the study of protein localization and dynamics in living cells. Hyperspectral imaging has proven to be a useful approach for such studies, but this technique is often limited by low signal and insufficient temporal resolution. Here, we present an implementation of a snapshot hyperspectral imaging device, the image mapping spectrometer (IMS), which acquires full spectral information simultaneously from each pixel in the field without scanning. The IMS is capable of real-time signal capture from multiple fluorophores with high collection efficiency (?65%) and image acquisition rate (up to 7.2?fps). To demonstrate the capabilities of the IMS in cellular applications, we have combined fluorescent protein (FP)-FRET and [Ca2+]i biosensors to measure simultaneously intracellular cAMP and [Ca2+]i signaling in pancreatic ?-cells. Additionally, we have compared quantitatively the IMS detection efficiency with a laser-scanning confocal microscope. PMID:22854044

  16. Mapping the land cover in coastal Gabes oases using the EO-1 HYPERION hyperspectral sensor

    NASA Astrophysics Data System (ADS)

    Ben-Arfa, Jouda; Bergès, Jean Claude; Beltrando, Gérard; Rim, Katlane; Zargouni, Fouad

    2015-04-01

    Gabes region is characterized by unique maritime oases in Mediterranean basin. Unfortunately these oases are sensitive areas due to a harsh competition for land and water between different user groups (urban, industry, agriculture). An industrial complex is now located in center of this region, cultivation practices have shifted from a traditional multi-layer plant association system and moreover the Gabes city itself is expanding in the very core of oases. The oases of Gabes are transformed into city oases; they undergo multiform interactions whose amplify their environmental dynamic. A proper management of this environment should be based on a fine cartography of land use and remote sensing plays a major role in this issue. However the use of legacy natural resource remote sensing data is disappointing. The crop production strategies rely on a fine scale ground split among various uses and the ground resolution of these satellites is not adequate. Our study relies on hyperspectral images in order to cartography oases boundaries and land use. We tested the potential of Hyperion hyperspectral satellite imagery for mapping dynamics oases covered. We have the opportunity to access EO1/Hyperion data on seven different dates on 2009 and 2010. This dataset allows us to compare various hyperspectral based processing both on the basis on information pertinence and time stability. In this frame some index appear as significantly efficient: cellulose index, vegetation mask, water presence index. On another side spectral unmixing looks as more sensitive to slight ground changes. These results raise the issue of compared interest of enhancing spatial resolution versus spectral resolution. Whereas high resolution ground observation satellites are obviously more appropriate for visual recognition process, reliable information could be extracted from hyperspectral information through a fully automatic process.

  17. Monitoring, analysis and classification of vegetation and soil data collected by a small and lightweight hyperspectral imaging system

    NASA Astrophysics Data System (ADS)

    Mönnig, Carsten

    2014-05-01

    The increasing precision of modern farming systems requires a near-real-time monitoring of agricultural crops in order to estimate soil condition, plant health and potential crop yield. For large sized agricultural plots, satellite imagery or aerial surveys can be used at considerable costs and possible time delays of days or even weeks. However, for small to medium sized plots, these monitoring approaches are cost-prohibitive and difficult to assess. Therefore, we propose within the INTERREG IV A-Project SMART INSPECTORS (Smart Aerial Test Rigs with Infrared Spectrometers and Radar), a cost effective, comparably simple approach to support farmers with a small and lightweight hyperspectral imaging system to collect remotely sensed data in spectral bands in between 400 to 1700nm. SMART INSPECTORS includes the whole remote sensing processing chain of small scale remote sensing from sensor construction, data processing and ground truthing for analysis of the results. The sensors are mounted on a remotely controlled (RC) Octocopter, a fixed wing RC airplane as well as on a two-seated Autogyro for larger plots. The high resolution images up to 5cm on the ground include spectra of visible light, near and thermal infrared as well as hyperspectral imagery. The data will be analyzed using remote sensing software and a Geographic Information System (GIS). The soil condition analysis includes soil humidity, temperature and roughness. Furthermore, a radar sensor is envisaged for the detection of geomorphologic, drainage and soil-plant roughness investigation. Plant health control includes drought stress, vegetation health, pest control, growth condition and canopy temperature. Different vegetation and soil indices will help to determine and understand soil conditions and plant traits. Additional investigation might include crop yield estimation of certain crops like apples, strawberries, pasture land, etc. The quality of remotely sensed vegetation data will be tested with ground truthing tools like a spectrometer, visual inspection and ground control panel. The soil condition will also be monitored with a wireless sensor network installed on the examined plots of interest. Provided with this data, a farmer can respond immediately to potential threats with high local precision. In this presentation, preliminary results of hyperspectral images of distinctive vegetation cover and soil on different pasture test plots are shown. After an evaluation period, the whole processing chain will offer farmers a unique, near real- time, low cost solution for small to mid-sized agricultural plots in order to easily assess crop and soil quality and the estimation of harvest. SMART INSPECTORS remotely sensed data will form the basis for an input in a decision support system which aims to detect crop related issues in order to react quickly and efficiently, saving fertilizer, water or pesticides.

  18. Experimental comparison of support vector machines with random forests for hyperspectral image land cover classification

    NASA Astrophysics Data System (ADS)

    Abe, B. T.; Olugbara, O. O.; Marwala, T.

    2014-06-01

    The performances of regular support vector machines and random forests are experimentally compared for hyperspectral imaging land cover classification. Special characteristics of hyperspectral imaging dataset present diverse processing problems to be resolved under robust mathematical formalisms such as image classification. As a result, pixel purity index algorithm is used to obtain endmember spectral responses from Indiana pine hyperspectral image dataset. The generalized reduced gradient optimization algorithm is thereafter executed on the research data to estimate fractional abundances in the hyperspectral image and thereby obtain the numeric values for land cover classification. The Waikato environment for knowledge analysis (WEKA) data mining framework is selected as a tool to carry out the classification process by using support vector machines and random forests classifiers. Results show that performance of support vector machines is comparable to that of random forests. This study makes a positive contribution to the problem of land cover classification by exploring generalized reduced gradient method, support vector machines, and random forests to improve producer accuracy and overall classification accuracy. The performance comparison of these classifiers is valuable for a decision maker to consider tradeoffs in method accuracy versus method complexity.

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

    SciTech Connect

    Love, Steven P [Los Alamos National Laboratory

    2008-01-01

    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.

  20. Hyperspectral band selection using statistical models

    Microsoft Academic Search

    Jochen Maerker; Wolfgang Groß; Wolfgang Middelmann; Alfons Ebert

    2011-01-01

    Hyperspectral sensors are delivering a data cube consisting of hundreds of images gathered in adjacent frequency bands. Processing such data requires solutions to handle the computational complexity and the information redundancy. In principle, there are two different approaches deployable. Data compression merges this imagery to some few images. Hereby only the essential information is preserved. Small variations are treated as

  1. Lossless Compression of Hyperspectral Images Using Multiband Lookup Tables

    Microsoft Academic Search

    Bruno Aiazzi; Stefano Baronti; Luciano Alparone

    2009-01-01

    In this letter a novel method suitable for the lossless compression of hyperspectral imagery is presented. The proposed method generalizes two previous algorithms, in which the concept of nearest neighbor (NN) prediction implemented through either one or two lookup tables (LUTs) was introduced. Now M LUTs are defined on each of the N previous bands, from which prediction is calculated.

  2. Thermal infrared hyperspectral imaging from vehicle-carried instrumentation

    Microsoft Academic Search

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

    2002-01-01

    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 \\

  3. Atmospheric characterization using space-based hyperspectral imaging systems

    Microsoft Academic Search

    S. Kacenjar; M. Honvedel

    2004-01-01

    The detection and subsequent quantification of certain effluent pollutants into the atmosphere can assist policy makers in formulating effective guidelines for public safety and environmental quality standards. This process is complicated by the fact that the atmospheric varies in radiometric properties not necessarily represented by data gathered with radiosonde devices. This work discusses a hyperspectral processing approach that addresses this

  4. Bayesian signal processing techniques for hyperspectral image unmixing

    E-print Network

    Kouroupetroglou, Georgios

    emerged as one of the fastest growing technologies in the field of remote sensing. Hyperspectral im- agery is proposed, termed BI-ICE, which is computationally efficient, and can be considered as a first-moments ap refers to the process of remotely obtaining data about an object (in our case a geographical area

  5. Improvement to an interband version of the linear prediction approach for hyperspectral image compression

    Microsoft Academic Search

    Jarno S. Mielikainen; Pekka J. Toivanen

    2003-01-01

    This paper proposes an improvement to an interband version of the linear prediction approach for lossless compression of hyperspectral images. The improvements consisted of the use of non-predictable bands and the varied size of the sample set. Our improved method achieved an average compression ratio of 3.19 using 13 Airborne Visible\\/Infrared Imaging Spectrometer (AVIRIS) images, compared to 3.08 in the

  6. Fast Hyperspectral Imaging Using a Mid-Infrared Tunable External Cavity Quantum Cascade Laser

    SciTech Connect

    Phillips, Mark C.; Ho, Nicolas

    2008-04-23

    An active hyperspectral imaging system using an external cavity quantum cascade laser and a focal plane array acquiring images at 25 Hz from 985 cm-1 to 1075 cm-1 with a resolution of 0.3 cm 1 is demonstrated. The chemical imaging of gases is demonstrated in both static and dynamic cases. The system was also used to analyze liquid and solid samples.

  7. Classification of Hyperspectral Images Compressed through 3D-JPEG2000

    Microsoft Academic Search

    Ian Blanes; Alaitz Zabala; Gerard Moré; Xavier Pons; Joan Serra-sagristà

    2008-01-01

    Classification of hyperspectral images is paramount to an increasing number of user applications. With the advent of more\\u000a powerful technology, sensed images demand for larger requirements in computational and memory capabilities, which has led\\u000a to devise compression techniques to alleviate the transmission and storage necessities.\\u000a \\u000a Classification of compressed images is addressed in this paper. Compression takes into account the spectral

  8. Hyperspectral Image Segmentation Using a New Bayesian Approach With Active Learning

    Microsoft Academic Search

    Jun Li; José M. Bioucas-Dias; Antonio Plaza

    2011-01-01

    This paper introduces a new supervised Bayesian ap- proach to hyperspectral image segmentation with active learning, which consists of two main steps. First, we use a multinomial logis- tic regression (MLR) model to learn the class posterior probability distributions. This is done by using a recently introduced logistic regression via splitting and augmented Lagrangian algorithm. Second, we use the information

  9. HIGH PERFORMANCE COMPUTING FOR HYPERSPECTRAL IMAGE ANALYSIS: PERSPECTIVE AND STATE-OF-THE-ART

    E-print Network

    Plaza, Antonio J.

    -OF-THE-ART Antonio Plaza1 , Qian Du2 , Yang-Lang Chang3 1 Department of Technology of Computers and Communications of computers, and specialized hardware ar- chitectures such as field programmable gate arrays (FPGAs, FPGAs. 1. INTRODUCTION Hyperspectral imaging is concerned with the measurement, analysis

  10. REFLECTANCE CALIBRATION OF FOCAL PLANE ARRAY HYPERSPECTRAL IMAGING SYSTEM FOR AGRICULTURAL AND FOOD SAFETY APPLICATIONS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A method to calibrate a pushbroom hyperspectral imaging system for "near-field" applications in agricultural and food safety has been demonstrated. The method consists of a modified geometric control point correction applied to a focal plane array to remove smile and keystone distortion from the sy...

  11. Comparison between visible/ NIR spectroscopy and hyperspectral imaging for detecting surface contaminants on poultry carcasses

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The U. S. Department of Agriculture, Agricultural Research Service has been developing a method and system to detect fecal contamination on processed poultry carcasses with hyperspectral and multispectral imaging systems. The patented method utilizes a three step approach to contaminant detection. S...

  12. Hyperspectral Imaging for Mapping of Total Nitrogen Spatial Distribution in Pepper Plant

    PubMed Central

    Yu, Ke-Qiang; Zhao, Yan-Ru; Li, Xiao-Li; Shao, Yong-Ni; Liu, Fei; He, Yong

    2014-01-01

    Visible/near-infrared (Vis/NIR) hyperspectral imaging was employed to determine the spatial distribution of total nitrogen in pepper plant. Hyperspectral images of samples (leaves, stems, and roots of pepper plants) were acquired and their total nitrogen contents (TNCs) were measured using Dumas combustion method. Mean spectra of all samples were extracted from regions of interest (ROIs) in hyperspectral images. Random frog (RF) algorithm was implemented to select important wavelengths which carried effective information for predicting the TNCs in leaf, stem, root, and whole-plant (leaf-stem-root), respectively. Based on full spectra and the selected important wavelengths, the quantitative relationships between spectral data and the corresponding TNCs in organs (leaf, stem, and root) and whole-plant (leaf-stem-root) were separately developed using partial least-squares regression (PLSR). As a result, the PLSR model built by the important wavelengths for predicting TNCs in whole-plant (leaf-stem-root) offered a promising result of correlation coefficient (R) for prediction (RP?=?0.876) and root mean square error (RMSE) for prediction (RMSEP?=?0.426%). Finally, the TNC of each pixel within ROI of the sample was estimated to generate the spatial distribution map of TNC in pepper plant. The achievements of the research indicated that hyperspectral imaging is promising and presents a powerful potential to determine nitrogen contents spatial distribution in pepper plant. PMID:25549353

  13. Nondestructive measurement of firmness and soluble solids content for apple fruit using hyperspectral scattering images

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nondestructive sensing is critical to assuring postharvest quality of apple fruit and increasing consumer acceptance and satisfaction. The objective of this research was to use a hyperspectral scattering technique to acquire spectral scattering images from apple fruit and to develop a data analysis ...

  14. Peach maturity/quality assessment using hyperspectral imaging-based spatially-resolved technique

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objective of this research was to measure the absorption and reduced scattering coefficients of peaches, using a hyperspectral imaging-based spatially-resolved method, for their maturity/quality assessment. A newly developed optical property measuring instrument was used for acquiring hyperspect...

  15. A line-scan hyperspectral system for high-throughput Raman chemical imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A line-scan hyperspectral system was developed to enable Raman chemical imaging for large sample areas. A custom-designed 785 nm line-laser, based on a scanning mirror, serves as an excitation source. A 45° dichroic beamsplitter reflects the laser light to form a 24 cm × 1 mm excitation line normall...

  16. Unified Lossy and Near-Lossless Hyperspectral Image Compression Based on JPEG 2000

    Microsoft Academic Search

    Gisela Carvajal; Barbara Penna; Enrico Magli

    2008-01-01

    We propose a compression algorithm for hyperspectral images featuring both lossy and near-lossless compression. The algorithm is based on JPEG 2000 and provides better near-lossless compression performance than 3D-CALIC. We also show that its effect on the results of selected applications is negligible and, in some cases, better than JPEG 2000.

  17. Determination of Wheat Kernel Black Point Damage using Hyper-Spectral Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A feasibility study was conducted on the use of hyperspectral imaging to differentiate sound wheat kernels from those with a damage condition called black point or black tip. Individual kernels of hard red spring wheat were loaded in indented slots on a blackened machined aluminum plate. Damage cond...

  18. HYPERSPECTRAL REFLECTANCE AND FLUORESCENCE IMAGING SYSTEM FOR FOOD QUALITY AND SAFETY

    Microsoft Academic Search

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

    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

  19. Toward an Optimal SVM Classification System for Hyperspectral Remote Sensing Images

    Microsoft Academic Search

    Yakoub Bazi; Farid Melgani

    2006-01-01

    Recent remote sensing literature has shown that support vector machine (SVM) methods generally outperform traditional statistical and neural methods in classification problems involving hyperspectral images. However, there are still open issues that, if suitably addressed, could allow further improvement of their performances in terms of classification accuracy. Two especially critical issues are: 1) the determination of the most appropriate feature

  20. ONLINE HYPERSPECTRAL LINE-SCAN FLUORESCENCE IMAGING FOR SAFETY INSPECTION OF APPLES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A recently developed fast hyperspectral line-scan imaging system integrated with a commercial apple-sorting machine was evaluated for rapid detection of animal feces matter on apples online. Golden Delicious apples obtained from a local orchard were artificially contaminated with a thin smear of co...

  1. Lossy hyperspectral image compression tuned for spectral mixture analysis applications on NVidia graphics processing units

    Microsoft Academic Search

    Antonio Plaza; Javier Plaza; Sergio Sánchez; Abel Paz

    2009-01-01

    In this paper, we develop a computationally efficient approach for lossy compression of remotely sensed hyperspectral images which has been specifically tuned to preserve the relevant information required in spectral mixture analysis (SMA) applications. The proposed method is based on two steps: 1) endmember extraction, and 2) linear spectral unmixing. Two endmember extraction algorithms: the pixel purity index (PPI) and

  2. Low-Complexity Hyperspectral Image Compression on a Multi-tiled Architecture

    Microsoft Academic Search

    Karel H. G. Walters; Andre B. J. Kokkeler; Sabih Gerez; G. J. M. Smit

    2009-01-01

    The increasing amount of data produced in satellites poses a downlink communication problem due to the limited data rate of the downlink. This bottleneck is solved by introducing more and more processing power on-board to compress data to a satisfiable rate. This paper introduces an algorithm which has been developed to compress hyperspectral images at low complexity and describes its

  3. Improving SVM classification accuracy using a hierarchical approach for hyperspectral images

    Microsoft Academic Search

    Begüm Demir; Sarp Ertürk

    2009-01-01

    This paper proposes to combine standard SVM classification with a hierarchical approach to increase SVM classification accuracy as well as reduce computational load of SVM testing. Support vectors are obtained by applying SVM training to the entire original training data. For classification, multi-level two-dimensional wavelet decomposition is applied to each hyperspectral image band and low spatial frequency components of each

  4. Lossy hyperspectral image compression with state-of-the-art video encoder

    Microsoft Academic Search

    Lucana Santos; Sebastian López; Gustavo M. Callicó; Jose F. López; Roberto Sarmiento

    2011-01-01

    One of the main drawbacks encountered when dealing with hyperspectral images is the vast amount of data to process. This is especially dramatic when data are acquired by a satellite or an aircraft due to the limited bandwidth channel needed to transmit data to a ground station. Several solutions are being explored by the scientific community. Software approaches have limited

  5. Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer

    NASA Astrophysics Data System (ADS)

    Goto, Atsushi; Nishikawa, Jun; Kiyotoki, Shu; Nakamura, Munetaka; Nishimura, Junichi; Okamoto, Takeshi; Ogihara, Hiroyuki; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

    2015-01-01

    Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa.

  6. Three-Dimensional Tarp Coding for the Compression of Hyperspectral Images

    E-print Network

    Fowler, James E.

    Three-Dimensional Tarp Coding for the Compression of Hyperspectral Images Yonghui Wang, Justin T. Rucker, and James E. Fowler Abstract--An embedded wavelet-based coder for the compression of hy to vectorized acceleration in single-instruction-multiple-data (SIMD) hard- ware. The proposed 3D tarp coder

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

    E-print Network

    Hanlon, Roger T.

    Hyperspectral imaging of cuttlefish camouflage indicates good color match in the eyes of fish, Irvine, CA, and approved April 13, 2011 (received for review December 30, 2010) Camouflage visual predators have keen color perception, and thus camouflage patterns should provide some degree

  8. Least squares subspace projection approach to mixed pixel classification for hyperspectral images

    Microsoft Academic Search

    Cheng-I. Chang; Xiao-Li Zhao; Mark L. G. Althouse; Jeng Jong Pan

    1998-01-01

    An orthogonal subspace projection (OSP) method using linear mixture modeling was recently explored in hyperspectral image classification and has shown promise in signature detection, discrimination, and classification. In this paper, the OSP is revisited and extended by three unconstrained least squares subspace projection approaches, called signature space OSP, target signature space OSP, and oblique subspace projection, where the abundances of

  9. Automation of waste recycling using hyperspectral image analysis Artzai Picon1

    E-print Network

    Whelan, Paul F.

    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 that the proposed solution can be used to replace the manual procedure that is currently used in WEEE recycling

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

    E-print Network

    Plaza, Antonio J.

    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

  11. Portable hyperspectral fluorescence imaging system for detection of biofilms on stainless steel surfaces

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A rapid nondestructive technology is needed to detect bacterial contamination on the surfaces of food processing equipment to reduce public health risks. A portable hyperspectral fluorescence imaging system was used to evaluate potential detection of microbial biofilm on stainless steel typically u...

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

    PubMed Central

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

    2014-01-01

    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

  13. Classification of gram-positive and gram-negative foodborne pathogenic bacteria with hyperspectral microscope imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Optical method with hyperspectral microscope imaging (HMI) has potential for identification of foodborne pathogenic bacteria from microcolonies rapidly with a cell level. A HMI system that provides both spatial and spectral information could be an effective tool for analyzing spectral characteristic...

  14. Rapid identification of salmonella serotypes with stereo and hyperspectral microscope imaging Methods

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

  15. Rice Seed Cultivar Identification Using Near-Infrared Hyperspectral Imaging and Multivariate Data Analysis

    PubMed Central

    Kong, Wenwen; Zhang, Chu; Liu, Fei; Nie, Pengcheng; He, Yong

    2013-01-01

    A near-infrared (NIR) hyperspectral imaging system was developed in this study. NIR hyperspectral imaging combined with multivariate data analysis was applied to identify rice seed cultivars. Spectral data was exacted from hyperspectral images. Along with Partial Least Squares Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA), K-Nearest Neighbor Algorithm (KNN) and Support Vector Machine (SVM), a novel machine learning algorithm called Random Forest (RF) was applied in this study. Spectra from 1,039 nm to 1,612 nm were used as full spectra to build classification models. PLS-DA and KNN models obtained over 80% classification accuracy, and SIMCA, SVM and RF models obtained 100% classification accuracy in both the calibration and prediction set. Twelve optimal wavelengths were selected by weighted regression coefficients of the PLS-DA model. Based on optimal wavelengths, PLS-DA, KNN, SVM and RF models were built. All optimal wavelengths-based models (except PLS-DA) produced classification rates over 80%. The performances of full spectra-based models were better than optimal wavelengths-based models. The overall results indicated that hyperspectral imaging could be used for rice seed cultivar identification, and RF is an effective classification technique. PMID:23857260

  16. Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer.

    PubMed

    Goto, Atsushi; Nishikawa, Jun; Kiyotoki, Shu; Nakamura, Munetaka; Nishimura, Junichi; Okamoto, Takeshi; Ogihara, Hiroyuki; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

    2015-01-01

    Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa. PMID:25604546

  17. Vis/NIR line-scan hyperspectral imaging techniques for food safety and quality inspection

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The great utility of spectral line-scan hyperspectral imaging platforms for visible to near-infrared reflectance and fluorescence has been demonstrated for development and implementation of methods and techniques for a broad range of food safety and quality issues, and including the use of multispec...

  18. [An algorithm of spectral minimum shannon entropy on extracting endmember of hyperspectral image].

    PubMed

    Yang, Ke-ming; Liu, Shi-wen; Wang, Lin-wei; Yang, Jie; Sun, Yang-yang; He, Dan-dan

    2014-08-01

    It's significant to study the algorithm of endmember extraction, which is the key for pixel unmixing,in the fields of feature identification, abundance inversion, quantitative remote sensing and so on. Based on the theory of shannon entropy and Gaussian distribution function, a new algorithm, named spectral minimum shannon entropy (SMSE) method for extracting end-members of hyperspectral images, is proposed in the present paper after analyzing the characteristics of spectra of the hyperspectral images. This algorithm was applied to extract the endmembers of an AVRIRS hyperspectral image, it was found that these extracted endmember spectra have higher precision by matching with the spectral library of United States Geological Survey (USGS). At the same time, it was also found that the SMSE algorithm has better efficiency and accuracy for extracting endmember spectra through comparing and analyzing comprehensively the results of endmember extraction of the experimental data by using the methods of SMSE, pixel purity index (PPI), sequential maximum angle convex cone (SMACC) and so on. In addition, the SMACC and SMSE are used to extract the endmembers in a Hyperion hyperspectral image, and it is concluded that the results of the SMSE is better than the SMACC's. Thus, the SMSE algorithm can be thought to have a certain degree of universal applicability. PMID:25508746

  19. [An algorithm of spectral minimum shannon entropy on extracting endmember of hyperspectral image].

    PubMed

    Yang, Ke-ming; Liu, Shi-wen; Wang, Lin-wei; Yang, Jie; Sun, Yang-yang; He, Dan-dan

    2014-08-01

    It's significant to study the algorithm of endmember extraction, which is the key for pixel unmixing,in the fields of feature identification, abundance inversion, quantitative remote sensing and so on. Based on the theory of shannon entropy and Gaussian distribution function, a new algorithm, named spectral minimum shannon entropy (SMSE) method for extracting end-members of hyperspectral images, is proposed in the present paper after analyzing the characteristics of spectra of the hyperspectral images. This algorithm was applied to extract the endmembers of an AVRIRS hyperspectral image, it was found that these extracted endmember spectra have higher precision by matching with the spectral library of United States Geological Survey (USGS). At the same time, it was also found that the SMSE algorithm has better efficiency and accuracy for extracting endmember spectra through comparing and analyzing comprehensively the results of endmember extraction of the experimental data by using the methods of SMSE, pixel purity index (PPI), sequential maximum angle convex cone (SMACC) and so on. In addition, the SMACC and SMSE are used to extract the endmembers in a Hyperion hyperspectral image, and it is concluded that the results of the SMSE is better than the SMACC's. Thus, the SMSE algorithm can be thought to have a certain degree of universal applicability. PMID:25474967

  20. PORTABLE HYPERSPECTRAL FLUORESCENCE IMAGING SYSTEM FOR DETECTION OF BIOFILM ON STAINLESS STEEL COUPON

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Portable hyperspectral fluorescence imaging, as a rapid nondestructive method, was used to investigate detection of bacterial contamination on the surfaces of food processing equipment. In this study, stainless steel plates typically used to manufacture food processing equipment was utilized to gro...

  1. Applying visible hyperspectral (chemical) imaging to estimate the age of bruises.

    PubMed

    Payne, Gemma; Langlois, Neil; Lennard, Chris; Roux, Claude

    2007-07-01

    Hyperspectral (chemical) imaging collects spectroscopic data in a two-dimensional spatial format. The potential application for the determination of the age of bruises is demonstrated and compared to reflectance probe spectrophotometry as well as photography. Blood was deposited on white cotton cloth or injected subcutaneously into pig skin to simulate a 'fresh bruise'. A mixture of blood and bile was used to simulate 'old' bruises. On the cloth background all the photographic methods clearly separated the two groups of samples (i.e. 'blood only' from 'blood plus bile'). However, on the pig skin the two groups could be separated by one of the photographic methods only. Separation of blood from blood and bile mixtures was obtained on the cloth and skin backgrounds using spectrophotometry and hyperspectral imaging. In a test using serial dilutions of blood and bile mixtures, the hyperspectral system performed slightly better than the spectrophotometer. The former also had the advantage of imaging a wider area and providing spatial data. Hyperspectral (chemical) imaging and spectrophotometry are superior to photography for the detection of bilirubin on a background of skin (due to the presence of yellow chromophores); this technology combined with mathematical analysis of the spectral data warrants further investigation. PMID:17725236

  2. Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

  3. Kernel Based Subspace Projection of Near Infrared Hyperspectral Images of Maize Kernels

    E-print Network

    Kernel Based Subspace Projection of Near Infrared Hyperspectral Images of Maize Kernels Rasmus, Technical University of Denmark Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, Denmark {rl University of Denmark Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby, Denmark aa

  4. Hyperspectral near-infrared reflectance imaging for detection of defect tomatoes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cuticle cracks on tomatoes are potential sites of pathogenic infection that may cause deleterious consequences both to consumer health and to fresh and fresh-cut produce markets. The feasibility of a hyperspectral near-infrared imaging technique in the spectral range of 1000 nm to 1700 nm was inves...

  5. Assessment of bacterial biofilm on stainless steel by hyperspectral fluorescence imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral fluorescence imaging techniques were investigated for detection of two genera of microbial biofilms on stainless steel material which is commonly used to manufacture food processing equipment. Stainless steel coupons were deposited in nonpathogenic E. coli O157:H7 and Salmonella cultu...

  6. ROBUST ANOMALY DETECTION IN HYPERSPECTRAL IMAGING J. Frontera-Pons1

    E-print Network

    Paris-Sud XI, Université de

    ROBUST ANOMALY DETECTION IN HYPERSPECTRAL IMAGING J. Frontera-Pons1 , M.A. Veganzones2 , S. Velasco, Iceland ABSTRACT Anomaly Detection methods are used when there is not enough information about the target. INTRODUCTION Target detection (TD) and anomaly detection (AD) of mul- tidimensional signals have proved

  7. Reflectance calibration of focal plane array hyperspectral imaging system for agricultural and food safety applications

    NASA Astrophysics Data System (ADS)

    Lawrence, Kurt C.; Park, Bosoon; Windham, William R.; Mao, Chengye; Poole, Gavin H.

    2003-03-01

    A method to calibrate a pushbroom hyperspectral imaging system for "near-field" applications in agricultural and food safety has been demonstrated. The method consists of a modified geometric control point correction applied to a focal plane array to remove smile and keystone distortion from the system. Once a FPA correction was applied, single wavelength and distance calibrations were used to describe all points on the FPA. Finally, a percent reflectance calibration, applied on a pixel-by-pixel basis, was used for accurate measurements for the hyperspectral imaging system. The method was demonstrated with a stationary prism-grating-prism, pushbroom hyperspectral imaging system. For the system described, wavelength and distance calibrations were used to reduce the wavelength errors to <0.5 nm and distance errors to <0.01mm (across the entrance slit width). The pixel-by-pixel percent reflectance calibration, which was performed at all wavelengths with dark current and 99% reflectance calibration-panel measurements, was verified with measurements on a certified gradient Spectralon panel with values ranging from about 14% reflectance to 99% reflectance with errors generally less than 5% at the mid-wavelength measurements. Results from the calibration method, indicate the hyperspectral imaging system has a usable range between 420 nm and 840 nm. Outside this range, errors increase significantly.

  8. Hyperspectral imaging for mapping of total nitrogen spatial distribution in pepper plant.

    PubMed

    Yu, Ke-Qiang; Zhao, Yan-Ru; Li, Xiao-Li; Shao, Yong-Ni; Liu, Fei; He, Yong

    2014-01-01

    Visible/near-infrared (Vis/NIR) hyperspectral imaging was employed to determine the spatial distribution of total nitrogen in pepper plant. Hyperspectral images of samples (leaves, stems, and roots of pepper plants) were acquired and their total nitrogen contents (TNCs) were measured using Dumas combustion method. Mean spectra of all samples were extracted from regions of interest (ROIs) in hyperspectral images. Random frog (RF) algorithm was implemented to select important wavelengths which carried effective information for predicting the TNCs in leaf, stem, root, and whole-plant (leaf-stem-root), respectively. Based on full spectra and the selected important wavelengths, the quantitative relationships between spectral data and the corresponding TNCs in organs (leaf, stem, and root) and whole-plant (leaf-stem-root) were separately developed using partial least-squares regression (PLSR). As a result, the PLSR model built by the important wavelengths for predicting TNCs in whole-plant (leaf-stem-root) offered a promising result of correlation coefficient (R) for prediction (RP?=?0.876) and root mean square error (RMSE) for prediction (RMSEP?=?0.426%). Finally, the TNC of each pixel within ROI of the sample was estimated to generate the spatial distribution map of TNC in pepper plant. The achievements of the research indicated that hyperspectral imaging is promising and presents a powerful potential to determine nitrogen contents spatial distribution in pepper plant. PMID:25549353

  9. Evaluation of Internal Defect and Surface Color of Whole Pickles Using Hyperspectral Imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging operated under simultaneous reflectance (400-675 nm) and transmittance (675-1000 nm) modes was studied for non-destructive and non-contact sensing of surface color and bloater damage in whole pickles. Good and defective pickles were collected from a commercial pickle processing...

  10. DETECTION OF INTERNAL DEFECT IN PICKLING CUCUMBERS USING HYPERSPECTRAL TRANSMITTANCE IMAGING

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Internal quality is an important aspect in the quality control and assurance of pickled products. A rapid and nondestructive method for internal defect detection would be of value to the pickle industry. A hyperspectral transmittance imaging technique was developed to detect internal defect in the ...

  11. VISIBLE/NEAR-INFRARED HYPERSPECTRAL TRANSMITTANCE IMAGING FOR DETECTION OF INTERNAL MECHANICAL INJURY IN PICKLING CUCUMBERS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Internal product quality is an important aspect in the quality control and assurance of pickled products. A rapid and non-destructive method for internal defect detection would be of value to the pickling cucumber industry. A hyperspectral transmittance imaging technique was developed to detect inte...

  12. Internal defect detection of whole pickles using hyperspectral reflectance and transmittance imaging

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging technique in simultaneous reflectance and transmittance modes was investigated for detection of hollow or bloater damage on whole pickles that was caused by mechanical injury during harvesting and handling or developed during the brining process. Normal and bloated pickle sampl...

  13. Spectral Angle Mapper Classification of Fluorescence Hyperspectral Image for Aflatoxin Contaminated Corn

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Aflatoxin contamination in corn is a serious problem for both producers and consumers. The present study applied the Spectral Angle Mapper classification technique to classify single corn kernels into contaminated and healthy groups. Fluorescence hyperspectral images were used in the classification....

  14. Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen content in

    E-print Network

    Paris-Sud XI, Université de

    Potential of field hyperspectral imaging as a non destructive method to assess leaf nitrogen on leaf optical properties have been proposed for a non- destructive diagnosis to replace Nitrogen Nutrition Index which is a costly and destructive method. We intend here to study leaf nitrogen concentra

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

    NASA Astrophysics Data System (ADS)

    Paz, Abel; Plaza, Antonio

    2010-08-01

    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.

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

    NASA Astrophysics Data System (ADS)

    Gholizadeh, Hamed

    2013-09-01

    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.

  17. A taxonomy of algorithms for chemical vapor detection with hyperspectral imaging spectroscopy

    NASA Astrophysics Data System (ADS)

    Manolakis, Dimitris G.; D'Amico, Francis M.

    2005-05-01

    Remote detection of chemical vapors in the atmosphere has a wide range of civilian and military applications. In the past few years there has been significant interest in the detection of effluent plumes using hyperspectral imaging spectroscopy in the 8-12- m atmospheric window. A major obstacle in the full exploitation of this technology is the fact that everything in the infrared is a source of radiation. As a result, the emission from the gases of interest is always mixed with emission by the more abundant atmospheric constituents and by other objects in the sensor field of view. The radiance fluctuations in this background emission constitute an additional source of interference which is much stronger than the detector noise. The purpose of this paper is threefold. First, we review the thin plume approximation, the resulting additive signal model, and the key differences between reflective and emissive radiance signal models. Second, based on the additive signal model we derive two families of detection algorithms using the generalized likelihood ratio test. The first family models the background using a multivariate normal distribution whereas the second family models the background using a linear subspace. Finally, we present a taxonomy of the available algorithms and show that some other ad-hoc approaches, like orthogonal background suppression, are simplified special cases of optimally derived detectors.

  18. Development of Research Infrastructure in Nevada for the Exploitation of Hyperspectral Image Data to Address Proliferation and Detection of Chemical and Biological Materials.

    SciTech Connect

    James V. Taranik

    2007-12-31

    This research was to exploit hyperspectral reflectance imaging technology for the detection and mapping variability (clutter) of the natural background against which gases in the atmosphere are imaged. The natural background consists of landscape surface cover composed of consolidated rocks, unconsolidated rock weathering products, soils, coatings on rock materials, vegetation, water, materials constructed by humans, and mixtures of the above. Human made gases in the atmosphere may indicate industrial processes important to detecting non-nuclear chemical and biological proliferation. Our research was to exploit the Visible and Near-Infrared (NIR) and the Short-wave Infrared (SWIR) portions of the electromagnetic spectrum to determine the properties of solid materials on the earth’s surface that could influence the detection of gases in the Long-Wave Infrared (LWIR). We used some new experimental hyperspectral imaging technologies to collect data over the Non-Proliferation Test and Evaluation Center (NPTEC) located on the Nevada Test Site (NTS). The SpecTIR HyperSpecTIR (HST) and Specim Dual hyperspectral sensors were used to understand the variability in the imaged background (clutter), that detected, measured, identified and mapped with operational commercial hyperspectral techniques. The HST sensors were determined to be more experimental than operational because of problems with radiometric and atmospheric data correction. However the SpecTIR Dual system, developed by Specim in Finland, eventually was found to provide cost-effective hyperspectral image data collection and it was possible to correct the Dual system’s data for specific areas. Batch processing of long flightlines was still complex, and if comparison to laboratory spectra was desired, the Dual system data still had to be processed using the empirical line method. This research determined that 5-meter spatial resolution was adequate for mapping natural background variations. Furthermore, this research determined that spectral resolution of 10um was adequate, but a signal to noise above 300:1 was desirable for hyperspectral sensors with this spectral resolution. Finally, we acquired a hyperspectral thermal dataset (SEBASS) at 3m spatial resolution over our study area in Beatty, Nevada that can be co-registered with the hyperspectral reflectance, LIDAR and digital Orthophoto data sets. This data set will enable us to quantify how measurements in the reflected infrared can be used to make inferences about the response of materials in the thermal infrared, the topic of our follow-on NA-22 investigation ending in 2008. These data provide the basis for our investigations proposed for the NA-22 2008 Broad Area Announcement. Beginning in June 2008, SpecTIR Corporation and Aerospace Corporation plan to fly the SpecTIR Dual and SEBASS in a stabilized mount in a twin Otter aircraft. This research provides the foundation for using reflected and emitted hyperspectral measurements together for mapping geologic and soil materials in arid to semi-arid regions.

  19. Retrieval of multi- and hyperspectral images using an interactive relevance feedback form of content-based image retrieval

    NASA Astrophysics Data System (ADS)

    Alber, Irwin E.; Farber, Morton S.; Yeager, Nancy; Xiong, Ziyou; Pottenger, William M.

    2001-03-01

    This paper demonstrates the capability of a set of image search algorithms and display tools to search large databases for multi- and hyperspectral image cubes most closely matching a particular query cube. An interactive search and analysis tool is presented and tested based on a relevance feedback approach that uses the human-in-the-loop to enhance a content-based image retrieval process to rapidly find the desired set of image cubes.

  20. Segmented PCA and JPEG2000 for hyperspectral image compression

    Microsoft Academic Search

    Wei Zhu; Qian Du; James E. Fowler

    2009-01-01

    Principal component analysis (PCA) is the most efficient spectral decorrelation approach for hyperspectral imagery. In conjunction with JPEG2000 for optimal bit allocation and spatial coding, the resulting PCA+JPEG2000 can yield superior rate-distortion performance and the following data analysis performance. However, the involved overhead bits consumed by the large transformation matrix may affect the performance at low bitrates, particularly when the

  1. The Role of Hyperspectral Imaging in the Visualization of Obliterated Writings

    NASA Astrophysics Data System (ADS)

    Ayub, Hina; Williams, Diane

    2006-03-01

    The forensic questioned document community has encountered difficulty visualizing obliterated writing using conventional methods. Cases have been reported in which pencil obliterated by ink, and ink obliterated by ink, cannot be discerned visually. Conventional methods for visualization of obliterated writings do not adequately visualize writing when obliteration is made with the same color ink, or when graphite pencil writings are obliterated by ink. We report the use of hyperspectral imaging to successfully view obliterated writings in which a ``true black'' ink obliterated graphite as well as graphite/graphite and ink/ink obliterations. Hyperspectral imaging (HSI) is a novel optical technique in which hundreds of narrow contiguous bands, over a large range of wavelengths, can be viewed to yield a complete spectral profile at each pixel in the image. HSI has evolved as the product of conventional two-dimensional imaging and spectroscopy. The resultant image of HSI is a three-dimensional data cube, with the pixels constrained to a single plane, and the complete reflectance spectra seen along the orthogonal axis. We used three types of hyperspectral imaging systems, which provided a wavelength range spanning approximately 300-1700 nm, to visualize the obliterated writing samples. Additionally, we will present data obtained from the use of thermal imaging to successfully view obliterated writings.

  2. Hyperspectral laser-induced flourescence imaging for assessing internal quality of kiwi fruit

    NASA Astrophysics Data System (ADS)

    Liu, Muhua; Liao, Yifeng; Zhou, Xiaomei

    2008-03-01

    This paper describes an experimental study on non-destructive methods for predicting quality of kiwifruits using fluorescence imaging. The method is based on hyperspectral laser-induced fluorescence imaging in the region between 700 and 1110 nm, and estimates the kiwifruits quality in terms of internal sugar content and firmness. A station for acquiring hyperspectral laser-induced fluorescence imaging has been designed and carefully choosing each component. The fluorescence imaging acquired by the station has been pre-processed by selecting regions of interest (ROIs) of 50 100 × pixels. A line regressing prediction method estimates the quality of kiwifruit samples. The results obtained in classification show that the station and prediction model enables the correct discrimination of kiwifruits internal sugar content and firmness with a percentage of r= 98.5%, SEP=0.4 and r=99.9%, SEP=0.62.

  3. Characterization of BxPC3-transplanted mice by hyperspectral autofluorescence imaging and Raman spectroscopy

    NASA Astrophysics Data System (ADS)

    Sawa, Masanori; Andriana, Bibin Bintang; Sato, Hidetoshi

    2014-02-01

    Live subcutaneous tumor grown in nude mouse is studied in situ with hyperspectral autofluorescence imaging and Raman spectroscopy. The purpose of the study is to develop methods for characterization of biochemical changing and of histological type of tumor without labeling. The results show that there are site depending variation in the fluorescence and Raman spectra. At the spot in which calcification is in process, Raman spectra showed a strong and specific band at 957 cm-1 due to PO4 species. The autofluosescence image can prove the histological changes based on the NADH and FAD which are major fluorophores in biological tissues. The hyperspectral image is analyzed with principal component analysis and the reconstructed images successfully depicts a different between necrotic and viable part within living subcutaneous tumor.

  4. Postfire soil burn severity mapping with hyperspectral image unmixing

    USGS Publications Warehouse

    Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

    2007-01-01

    Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

  5. Wavelet-based Bayesian fusion of multispectral and hyperspectral images using Gaussian scale mixture model

    Microsoft Academic Search

    Yifan Zhang

    2012-01-01

    In this article, a wavelet-based Bayesian fusion framework is presented, in which a low spatial resolution hyperspectral (HS) image is fused with a high spatial resolution multispectral (MS) image by accounting for the joint statistics. Particularly, a zero-mean heavy-tailed model, Gaussian scale mixture model, is employed as the prior, which is believed to be capable of modelling the distribution of

  6. Wavelet-based Bayesian fusion of multispectral and hyperspectral images using Gaussian scale mixture model

    Microsoft Academic Search

    Yifan Zhang

    2011-01-01

    In this article, a wavelet-based Bayesian fusion framework is presented, in which a low spatial resolution hyperspectral (HS) image is fused with a high spatial resolution multispectral (MS) image by accounting for the joint statistics. Particularly, a zero-mean heavy-tailed model, Gaussian scale mixture model, is employed as the prior, which is believed to be capable of modelling the distribution of

  7. Mid-infrared hyperspectral imaging for the detection of explosive compounds

    NASA Astrophysics Data System (ADS)

    Ruxton, K.; Robertson, G.; Miller, W.; Malcolm, G. P. A.; Maker, G. T.

    2012-10-01

    Active hyperspectral imaging is a valuable tool in a wide range of applications. A developing market is the detection and identification of energetic compounds through analysis of the resulting absorption spectrum. This work presents a selection of results from a prototype mid-infrared (MWIR) hyperspectral imaging instrument that has successfully been used for compound detection at a range of standoff distances. Active hyperspectral imaging utilises a broadly tunable laser source to illuminate the scene with light over a range of wavelengths. While there are a number of illumination methods, this work illuminates the scene by raster scanning the laser beam using a pair of galvanometric mirrors. The resulting backscattered light from the scene is collected by the same mirrors and directed and focussed onto a suitable single-point detector, where the image is constructed pixel by pixel. The imaging instrument that was developed in this work is based around a MWIR optical parametric oscillator (OPO) source with broad tunability, operating at 2.6 ?m to 3.7 ?m. Due to material handling procedures associated with explosive compounds, experimental work was undertaken initially using simulant compounds. A second set of compounds that was tested alongside the simulant compounds is a range of confusion compounds. By having the broad wavelength tunability of the OPO, extended absorption spectra of the compounds could be obtained to aid in compound identification. The prototype imager instrument has successfully been used to record the absorption spectra for a range of compounds from the simulant and confusion sets and current work is now investigating actual explosive compounds. The authors see a very promising outlook for the MWIR hyperspectral imager. From an applications point of view this format of imaging instrument could be used for a range of standoff, improvised explosive device (IED) detection applications and potential incident scene forensic investigation.

  8. Passive Standoff Detection of RDX Residues on Metal Surfaces via Infrared Hyperspectral Imaging

    SciTech Connect

    Blake, Thomas A.; Kelly, James F.; Gallagher, Neal B.; Gassman, Paul L.; Johnson, Timothy J.

    2009-09-01

    Hyperspectral images of galvanized steel plates, each containing a stain of RDX, were recorded using a commercial longwave infrared imaging spectrometer. Demonstrations of passive RDX chemical detection at areal dosages between 16 and 90 µg / cm2 were carried out over practical stand-off ranges between 14 and 50 m. Efforts to develop better chemical anomaly and target detection through chemometric analyses are described.

  9. Confocal Raman microscopy and hyperspectral dark field microscopy imaging of chemical and biological systems

    NASA Astrophysics Data System (ADS)

    Toma, Henrique E.; da Silva Shinohara, Jorge; Grasseschi, Daniel

    2015-03-01

    Hyperspectral imaging can provide accurate information on the distribution of the chemical species in materials and biological samples, based on the analysis of their electronic and vibrational profiles. In special, confocal Raman microscopy is one of the best ways to access the chemical distribution of molecules, especially under resonance Raman or SERS conditions. On the other hand, enhanced dark field optical microscopy can be employed for hyperspectral imaging in the visible and near-IR region, while extending the optical resolution up to the nanoscale dimension. It allows the detection of gold or silver single nanoparticles, as well as spectral monitoring from the characteristic surface plasmon bands. These two hyperspectral microscopies can be conveniently combined to provide nanoscale electronic and vibrational information of the species present in a wide variety of chemical and biological systems. A case study focusing on the improvement of the classical spot-test analysis of nickel(II) ions with dithizone is here detailed. A great enhancement of sensitivity in the detection of nickel(II) ions, by at least 4 orders of magnitude, has been observed in this work. Hyperspectral measurements allowed the mapping of the gold nanoparticles (AuNP) distribution on cellulose fibers and on glass, and the evaluation of their extinction and SERS spectra for analytical purposes.

  10. SENSIVITY ANALYSIS OF A HYPERSPECTRAL INVERSION MODEL FOR REMOTE SENSING OF SHALLOW COASTAL ECOSYSTEMS

    Microsoft Academic Search

    Carolina Gerardino-Neira; James Goodman; Miguel Vélez-Reyes; Wilson Rivera-Gallego; Bernard M. Gordon

    2000-01-01

    Hyperspectral remote sensing provides a robust analytical tool for the subsurface analysis of shallow aquatic ecosystems. The high spectral resolution offered by hyperspectral sensors provides the capacity for simultaneously deriving multiple environmental parameters from a single image. This ability is particularly beneficial for the spatial analysis of complex ecosystems, such as coastal benthic habitats, which are inherently heterogeneous. Recent years

  11. DEVELOPMENT OF HYPERSPECTRAL IMAGING TECHNIQUE FOR THE DETECTION OF CHILLING INJURY IN CUCUMBERS: SPECTRAL AND IMAGE ANALYSIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral images of cucumbers were acquired before and during cold storage treatment as well as during subsequent room temperature (RT) storage to explore their potential use for the detection of chilling induced damage in whole cucumbers. Region of interest (ROI) spectral features of chilling i...

  12. Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An algorithm has been developed to identify spots generated in hyperspectral images of mangoes infested with fruit fly larvae. The algorithm incorporates background removal, application of a Gaussian blur, thresholding, and particle count analysis to identify locations of infestations. Each of the f...

  13. Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics

    NASA Astrophysics Data System (ADS)

    Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya

    2014-09-01

    Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.

  14. Rapid, nondestructive denim fiber bundle characterization using luminescence hyperspectral image analysis.

    PubMed

    Deuro, Randi E; Leiker, Kristen M; Wang, Yanhui; Deuro, Nicholas J; Milillo, Tammy M; Bright, Frank V

    2015-01-01

    An investigation into the performance of luminescence-based hyperspectral imaging (LHSI) for denim fiber bundle discrimination has been conducted. We also explore the potential of nitromethane (CH3NO2) -based quenching to improve discrimination, and we determine the quenching mechanism. The luminescence spectra (450-850 nm) and images from the denim fiber bundles were obtained with excitation at 325 or 405 nm. LHSI data were recorded in less than 5 s and subsequently assessed by principal component analysis or rendered as red, green, blue (RGB) component histograms. The results show that LHSI data can be used to rapidly and uniquely discriminate between all the fiber bundle types studied in this research. These non-destructive techniques eliminate extensive sample preparation and allow for rapid hyperspectral image collection, analysis, and assessment. The quenching data also revealed that the dye molecules within the individual fiber bundles exhibit dramatically different accessibilities to CH3NO2. PMID:25506790

  15. CMOS foveal image sensor chip

    NASA Technical Reports Server (NTRS)

    Bandera, Cesar (Inventor); Scott, Peter (Inventor); Sridhar, Ramalingam (Inventor); Xia, Shu (Inventor)

    2002-01-01

    A foveal image sensor integrated circuit comprising a plurality of CMOS active pixel sensors arranged both within and about a central fovea region of the chip. The pixels in the central fovea region have a smaller size than the pixels arranged in peripheral rings about the central region. A new photocharge normalization scheme and associated circuitry normalizes the output signals from the different size pixels in the array. The pixels are assembled into a multi-resolution rectilinear foveal image sensor chip using a novel access scheme to reduce the number of analog RAM cells needed. Localized spatial resolution declines monotonically with offset from the imager's optical axis, analogous to biological foveal vision.

  16. Construction of filter vectors for the information-efficient spectral imaging sensor

    SciTech Connect

    Stallard, B.R.; Gentry, S.M.

    1998-12-01

    The information-efficient spectral imaging sensor (ISIS) seeks to improve system performance by processing hyperspectral information in the optical hardware. Its output may be a gray scale image in which one attempts to maximize the contrast between a given target and the background. Alternatively, its output may be a small number of images, rather than a full data cube, that retain the essential information required in the application. The principal advantage of ISIS is that it offers the discrimination of hyperspectral imaging while achieving the signal-to-noise ratio of multispectral imaging. The paper focuses on construction of the filter vectors that are needed to program ISIS. The instrument produces an image which is essentially a dot product of the scene and the filter vector. Both single vector and multiple vector approaches are considered. Also, they discuss some subtle points related to optimizing the filter vectors.

  17. Estimating growth status of winter wheat based on aerial images and hyperspectral data

    NASA Astrophysics Data System (ADS)

    Han, Yunxia; Li, Minzan; Jia, Liangliang; Zhang, Xijie; Zhang, Fusuo

    2005-08-01

    The aim of this paper is to estimate the growth status and yield of winter wheat using aerial images and hyperspectral data obtained by unmanned aircraft, and then to perform precision management to the crop. The test farm was divided into 48 cells. Twenty-four cells were selected as variable rate fertilization area, and the other 24 cells were used as contrast area with low fertilization in growth season. In 2004, the aerial images of winter wheat canopy were measured from an unmanned aircraft. The SPAD value of crop leaf was acquired using a SPAD-502 chlorophyll meter, and then the hyperspectral reflectance of the crop canopy was measured by a handheld spectroradiometer. The vegetation indices, NDVI and DVI, were calculated from the hyperspectral data. The characteristics of the aerial images were used to evaluate the growth status. The RGB values of all cells were calculated from aerial images. The result showed that total nitrogen had better correlation with SPAD, NDVI, DVI, and RGB. NDVI and DVI had high correlation with the growth condition, and R/(R+G+B) and G/(R+G+B) had good correlation with the growth status and yield. The variable rate fertilization based on aerial images and NDVI was executed in the experimental cells. The yield map showed that the spatial variation of the yield was reduced and the total yield was increased. While in contrast cells, the spatial variation of the yield is greater than in experimental cells because of the spatial variation of the field nutrition. Therefore, it is practical to use aerial images and hyperspectral data of the crop canopy in estimation of the crop growth status.

  18. Characterizing Hyperspectral Imagery (AVIRIS) Using Fractal Technique

    NASA Technical Reports Server (NTRS)

    Qiu, Hong-Lie; Lam, Nina Siu-Ngan; Quattrochi, Dale

    1997-01-01

    With the rapid increase in hyperspectral data acquired by various experimental hyperspectral imaging sensors, it is necessary to develop efficient and innovative tools to handle and analyze these data. The objective of this study is to seek effective spatial analytical tools for summarizing the spatial patterns of hyperspectral imaging data. In this paper, we (1) examine how fractal dimension D changes across spectral bands of hyperspectral imaging data and (2) determine the relationships between fractal dimension and image content. It has been documented that fractal dimension changes across spectral bands for the Landsat-TM data and its value [(D)] is largely a function of the complexity of the landscape under study. The newly available hyperspectral imaging data such as that from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) which has 224 bands, covers a wider spectral range with a much finer spectral resolution. Our preliminary result shows that fractal dimension values of AVIRIS scenes from the Santa Monica Mountains in California vary between 2.25 and 2.99. However, high fractal dimension values (D > 2.8) are found only from spectral bands with high noise level and bands with good image quality have a fairly stable dimension value (D = 2.5 - 2.6). This suggests that D can also be used as a summary statistics to represent the image quality or content of spectral bands.

  19. Hyperspectral and broadband FLIR data fusion

    NASA Astrophysics Data System (ADS)

    Nicholas, Mike; James, Matt; Nothard, Jo

    2005-10-01

    Future targeting systems aim to extend the range of air-ground target search, acquisition, temporal tracking and identification exceeding those currently afforded by forward looking infrared sensors. One technology option that has the potential to fulfil this requirement is hyperspectral imaging. Therefore a solution to detection and identification at longer ranges is the fusion of data from broadband and hyperspectral sensors. QinetiQ, under the Data & Information Fusion Defense Technology Centre, aims to develop a fully integrated spatial/spectral and temporal target detection/ identification air- ground tracking environment. This will build upon current capabilities in target tracking, synthetic scene generation, sensor modelling, hyperspectral and broadband target detection and identification algorithms into a tool that can be used to evaluate data fusion architectures.

  20. Adaptive sensitivity CCD image sensor

    Microsoft Academic Search

    Sarit Chen; Ran Ginosar

    1995-01-01

    The design of an adaptive sensitivity CCD image sensor is described. The sensitivity of each pixel is individually controlled (by changing its exposure time) to assure that it is operating in the linear range of the CCD response, and not in the cut-off or saturation regions. Thus, even though an individual CCD sensor is limited in its dynamic range, the