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1

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

Microsoft Academic Search

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

Scott D. Briles

1997-01-01

2

Methods for gas detection using stationary hyperspectral imaging sensors  

DOEpatents

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

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

2012-04-24

3

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

Microsoft Academic Search

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

Scott D. Briles

1996-01-01

4

Retrieval of spectral response functions for the hyperspectral sensor of HISUI (Hyperspectral Imager SUIte) by means of onboard calibration sources  

NASA Astrophysics Data System (ADS)

HISUI (Hyper-spectral Imager SUIte), which is the next Japanese earth observation project, has been developed under the contract with Ministry of Economy, Trade and Industry(METI) and New Energy and Industrial Technology Development Organization(NEDO). HISUI is composed of hyper-spectral sensor and multi-spectral sensor. The hyperspectral sensor is an imaging spectrometer with two separate spectral channels: one for the VNIR range from 400 to 970 nm and the other for the SWIR range from 900 to 2500 nm. Ground sampling distance is 30 m with spatial swath width of 30 km. The spectral sampling will be better than 10 nm in the VNIR and 12.5 nm in the SWIR. The multi-spectral sensor has four VNIR spectral bands with spatial resolution of 5m and swath width of 90 km. HISUI will be installed in ALOS-3 that is an earth observing satellite in the project formation phase by JAXA in FY 2015. This paper is concerned with the retrieval of spectral response functions (SRF) for the hyper-spectral sensor. The center wavelength and bandwidth of spectral response functions of hyper-spectral sensor may shift and broaden due to the distortion in the spectrometer, the optics and the detector assembly. Therefore it is necessary to measure or estimate the deviation of the wavelength and the bandwidth broadening of the SRFs. In this paper, we describe the methods of retrieval of the SRF's parameters (Gaussian functions assumed) by means of onboard calibration sources and we show some simulation's results and the usefulness of this method.

Tatsumi, Kenji; Ohgi, Nagamitsu; Harada, Hisashi; Kawanishi, Toneo; Sakuma, Fumihiro; Inada, Hitomi; Kawashima, Takahiro; Iwasaki, Akira

2011-10-01

5

Parametric methodologies and tools for first-order hyperspectral imaging sensor system design  

Microsoft Academic Search

Aircraft and space-based hyperspectral imaging (HSI) sensors tailored for the reflective or emissive spectral regimes are being designed and developed for a wide variety of military, civil and science applications. Key sensor-level HSI system performance requirements dictate the optical, spectrometer, focal plane and data processing design parameters for a given choice of spectral instrument design and platform altitude. A detailed

Terrence S. Lomheim; Eric A. Nussbaumer; Jeffrey A. Lang; David W. Warren; Nemesio Caraballo

2004-01-01

6

Performance of the FIRST, a Longwave Infrared Hyperspectral Imaging Sensor  

Microsoft Academic Search

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state are fundamental needs in several fields of applications. Imaging spectrometers have unmatched capabilities to meet the

Vincent Farley; Alexandre Vallières; Martin Chamberland; André Villemaire

7

Handheld hyperspectral imager  

NASA Astrophysics Data System (ADS)

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.

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

2010-04-01

8

Low-light hyperspectral imager for characterization of biological samples based on an sCMOS image sensor  

NASA Astrophysics Data System (ADS)

The new "scientific CMOS" (sCMOS) sensor technology has been tested for use in hyperspectral imaging. The sCMOS offers extremely low readout noise combined with high resolution and high speed, making it attractive for hyperspectral imaging applications. A commercial HySpex hyperspectral camera has been modified to be used in low light conditions integrating an sCMOS sensor array. Initial tests of fluorescence imaging in challenging light settings have been performed. The imaged objects are layered phantoms labelled with controlled location and concentration of fluorophore. The camera has been compared to a state of the art spectral imager based on CCD technology. The image quality of the sCMOS-based camera suffers from artifacts due to a high density of pixels with excessive noise, attributed to the high operating temperature of the array. Image processing results illustrate some of the benefits and challenges of the new sCMOS technology.

Hernandez-Palacios, J.; Randeberg, L. L.; Haug, I. J.; Baarstad, I.; Løke, T.; Skauli, T.

2011-02-01

9

Sensor noise informed representation of hyperspectral data, with benefits for image storage and processing.  

PubMed

Many types of hyperspectral image processing can benefit from knowledge of noise levels in the data, which can be derived from sensor physics. Surprisingly, such information is rarely provided or exploited. Usually, the image data are represented as radiance values, but this representation can lead to suboptimal results, for example in spectral difference metrics. Also, radiance data do not provide an appropriate baseline for calculation of image compression ratios. This paper defines two alternative representations of hyperspectral image data, aiming to make sensor noise accessible to image processing. A "corrected raw data" representation is proportional to the photoelectron count and can be processed like radiance data, while also offering simpler estimation of noise and somewhat more compact storage. A variance-stabilized representation is obtained by square-root transformation of the photodetector signal to make the noise signal-independent and constant across all bands while also reducing data volume by almost a factor 2. Then the data size is comparable to the fundamental information capacity of the sensor, giving a more appropriate measure of uncompressed data size. It is noted that the variance-stabilized representation has parallels in other fields of imaging. The alternative data representations provide an opportunity to reformulate hyperspectral processing algorithms to take actual sensor noise into account. PMID:21747455

Skauli, Torbjørn

2011-07-01

10

Airborne measurements in the longwave infrared using an imaging hyperspectral sensor  

NASA Astrophysics Data System (ADS)

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state is one important application. Analysis of the surface emissivity as a means to classify ground properties and usage is another one. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on the Fourier Transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320×256 pixels at 0.35mrad spatial resolution over the 8-12 ?m spectral range at spectral resolutions of up to 0.25cm -1. The FIRST has been used in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, an airborne system integrating the FIRST has been developed to provide airborne hyperspectral measurement capabilities. The airborne system and its capabilities are presented in this paper. The FIRST sensor modularity enables operation in various configurations such as tripod-mounted and airborne. In the airborne configuration, the FIRST can be operated in push-broom mode, or in staring mode with image motion compensation. This paper focuses on the airborne operation of the FIRST sensor.

Allard, Jean-Pierre; Chamberland, Martin; Farley, Vincent; Marcotte, Frédérick; Rolland, Matthias; Vallières, Alexandre; Villemaire, André

2008-05-01

11

Airborne measurements in the longwave infrared using an imaging hyperspectral sensor  

NASA Astrophysics Data System (ADS)

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state is one important application. Analysis of the surface emissivity as a means to classify ground properties and usage is another one. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on the Fourier Transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320x256 pixels at 0.35mrad spatial resolution over the 8-12 ?m spectral range at spectral resolutions of up to 0.25cm-1. The FIRST has been used in several field campaigns, including the demonstration of standoff chemical agent detection [http://dx.doi.org/10.1117/12.795119.1]. More recently, an airborne system integrating the FIRST has been developed to provide airborne hyperspectral measurement capabilities. The airborne system and its capabilities are presented in this paper. The FIRST sensor modularity enables operation in various configurations such as tripod-mounted and airborne. In the airborne configuration, the FIRST can be operated in push-broom mode, or in staring mode with image motion compensation. This paper focuses on the airborne operation of the FIRST sensor.

Allard, Jean-Pierre; Chamberland, Martin; Farley, Vincent; Marcotte, Frédérick; Rolland, Matthias; Vallières, Alexandre; Villemaire, André

2008-08-01

12

Airborne measurements in the longwave infrared using an imaging hyperspectral sensor  

NASA Astrophysics Data System (ADS)

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state is one important application. Analysis of the surface emissivity as a means to classify ground properties and usage is another one. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on the Fourier Transform technology yielding high spectral resolution and enabling high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320×256 pixels at 0.35mrad spatial resolution over the 8-12 ?m spectral range at spectral resolutions of up to 0.25cm-1. The FIRST has been used in several field campaigns, including the demonstration of standoff chemical agent detection [http://dx.doi.org/10.1117/12.788027.1]. More recently, an airborne system integrating the FIRST has been developed to provide airborne hyperspectral measurement capabilities. The airborne system and its capabilities are presented in this paper. The FIRST sensor modularity enables operation in various configurations such as tripod-mounted and airborne. In the airborne configuration, the FIRST can be operated in push-broom mode, or in staring mode with image motion compensation. This paper focuses on the airborne operation of the FIRST sensor.

Allard, Jean-Pierre; Chamberland, Martin; Farley, Vincent; Marcotte, Frédérick; Rolland, Matthias; Vallières, Alexandre; Villemaire, André

2008-08-01

13

Diffused Matrix Format: a new storage and processing format for airborne hyperspectral sensor images.  

PubMed

At present, hyperspectral images are mainly obtained with airborne sensors that are subject to turbulences while the spectrometer is acquiring the data. Therefore, geometric corrections are required to produce spatially correct images for visual interpretation and change detection analysis. This paper analyzes the data acquisition process of airborne sensors. The main objective is to propose a new data format called Diffused Matrix Format (DMF) adapted to the sensor's characteristics including its spectral and spatial information. The second objective is to compare the accuracy of the quantitative maps derived by using the DMF data structure with those obtained from raster images based on traditional data structures. Results show that DMF processing is more accurate and straightforward than conventional image processing of remotely sensed data with the advantage that the DMF file structure requires less storage space than other data formats. In addition the data processing time does not increase when DMF is used. PMID:22399919

Martínez, Pablo; Cristo, Alejandro; Koch, Magaly; Pérez, Rosa Ma; Schmid, Thomas; Hernández, Luz M

2010-01-01

14

Diffused Matrix Format: A New Storage and Processing Format for Airborne Hyperspectral Sensor Images  

PubMed Central

At present, hyperspectral images are mainly obtained with airborne sensors that are subject to turbulences while the spectrometer is acquiring the data. Therefore, geometric corrections are required to produce spatially correct images for visual interpretation and change detection analysis. This paper analyzes the data acquisition process of airborne sensors. The main objective is to propose a new data format called Diffused Matrix Format (DMF) adapted to the sensor's characteristics including its spectral and spatial information. The second objective is to compare the accuracy of the quantitative maps derived by using the DMF data structure with those obtained from raster images based on traditional data structures. Results show that DMF processing is more accurate and straightforward than conventional image processing of remotely sensed data with the advantage that the DMF file structure requires less storage space than other data formats. In addition the data processing time does not increase when DMF is used.

Martinez, Pablo; Cristo, Alejandro; Koch, Magaly; Perez, Rosa M?.; Schmid, Thomas; Hernandez, Luz M.

2010-01-01

15

A small, low-cost, hyperspectral imaging FTIR sensor design for standoff detection applications  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging (HSI) sensors allow standoff visualization and identification of chemical vapor plumes; however, currently available COTS sensors, which produce very high quality data, are expensive(>$750k), large(>100 L), and massive( >30 kg). Man-portable and UAV based hyperspectral sensor applications require smaller and lighter weight designs. An approach using new technologies, including a microbolometer IR camera, a piezo-electric linear actuator, a FPGA/LAN board, and an embedded multi-core CPU, is presented that seeks to produce similar quality hyperspectral data at a 10x cost reduction, 3x size reduction (<30 L), and a 3x mass reduction (<10 kg for optics and electronics). The design challenges, system overview, and initial performance data measurements from the new spectrometer designs are presented. An overview of the data cube signal processing, including spatial co-adding, re-sampling of the interferogram data point spacing, phase correction, and detection algorithms, is presented. The spectrometer optical design was also tested by temporarily installing a single pixel MCT detector in order to make spectral resolution comparisons with a traditional FTIR spectrometer.

Gruber, Thomas, Jr.; Moore, Brad; Tercha, Brian; Bowe, Ryan

2012-05-01

16

Hyperspectral Systems Increase Imaging Capabilities  

NASA Technical Reports Server (NTRS)

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

2010-01-01

17

Comparison of infrared imaging hyperspectral sensors for military target detection applications  

NASA Astrophysics Data System (ADS)

Recent studies have demonstrated the potential for exploring spectral discriminates in the thermal infrared for day/night surveillance and targeting of military targets in situations where the thermal contrast is low. Although the spectral discriminates have been found to be very subtle in most cases, good detection performance is achievable due to the generally high band-to-band spectral correlation of the background. This, however, presents a challenging set of requirements for infrared multispectral and hyperspectral sensors designed for this application. In this paper, we examine the merits and limitations of various design approaches, including imaging Michelson interferometers, dispersive spectrometers, and spatial Fourier transform spectrometers. The comparison is based on detailed sensor modeling as well as laboratory and field measurements of state-of-the-art instruments: a dispersive spectrometers and a n imaging Fourier transform spectrometer. The primary emphasis of this paper is the design of a hyperspectral sensor for tower-based and subsequent airborne data collection. Implications for operational multispectral sensor designs are also given.

Eismann, Michael T.; Schwartz, Craig R.; Cederquist, Jack N.; Hackwell, John A.; Huppi, Ronald J.

1996-11-01

18

Detection of surface mines using hyperspectral sensors  

Microsoft Academic Search

Hyperspectral imaging is an important technology for the detection of surface and buried land mines from an airborne platform. For this reason, hyperspectral was included in the two experiments that were executed by the Army RDECOM Night Vision and Electronic Sensors Directorate (NVESD) in Fall 2002 and in Spring 2003. The purpose of these experiments was to bring together a

Edwin M. Winter

2004-01-01

19

Mine detection experiments using hyperspectral sensors  

Microsoft Academic Search

Hyperspectral imaging is an important technology for the detection of surface and buried land mines from an airborne platform. For this reason, hyperspectral was included with SAR sensors in the two deployments that were executed by the CECOM RDEC Night Vision and Electronic Systems Directorate (NVESD) in Fall 2002 and in Spring 2003. The purpose of these deployments was to

Edwin M. Winter; Miranda A. Miller; Christopher G. Simi; Anthony B. Hill; Timothy J. Williams; David Hampton; Mark Wood; Jerry Zadnick; Marc D. Sviland

2004-01-01

20

Hyperspectral image compression with modified 3D SPECK  

Microsoft Academic Search

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

Ruzelita Ngadiran; Said Boussakta; Ahmed Bouridane; Bayan Syarif

2010-01-01

21

High-definition hyperspectral imaging system  

US Patent & Trademark Office Database

A compact high-definition hyperspectral imaging system (HDHIS) for light aircraft remote sensing to perform concurrent pushbroom hyperspectral imaging and high-resolution photographic imaging. The HDHIS comprises a sensor head having a hyperspectral scanner and a CCD digital camera. An airborne computer interfaces with the sensor head to provide data acquisition including hyperspectral quick view images and control functions. An alternative embodiment includes combining the HDHIS with a computerized airborne multi-camera imaging system (CAMIS) which comprises four progressive scan (CCD) cameras attached to a set of interchangeable, interference filters, to provide a triple spectral imaging system that can be operated by one person on a light aircraft.

2006-12-12

22

Hyperspectral Image Compression  

Microsoft Academic Search

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

Stephanie Wright; Jason Ashbach

2008-01-01

23

Performance of the FIRST: a long-wave infrared hyperspectral imaging sensor  

NASA Astrophysics Data System (ADS)

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state are fundamental needs in several fields of applications. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on FTIR technology to provide high spectral resolution and to enable high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320x256 pixels at 0.35 mrad spatial resolution over the 8-12 ?m spectral range at spectral resolutions of up to 0.25 cm -1. The FIRST has been used in several field measurements, including demonstration of standoff chemical agent detection. One key feature of the FIRST is its ability to give calibrated measurements. The quality of the calibrated measurements will be presented in this paper. Sensitivity, spectral resolution and radiometric stability as obtained during field and laboratory measurements will be presented. Finally, images of chemical releases detected with the FIRST will be shown.

Farley, Vincent; Vallières, Alexandre; Chamberland, Martin; Villemaire, André; Legault, Jean-François

2006-09-01

24

Radiometric calibration stability of the FIRST: a longwave infrared hyperspectral imaging sensor  

NASA Astrophysics Data System (ADS)

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state are fundamental needs in several fields of applications. Imaging spectrometers have unmatched capabilities to meet the requirements of these applications. Telops has developed the FIRST, a LWIR hyperspectral imager. The FIRST is based on FTIR technology to yield high spectral resolution and to enable high accuracy radiometric calibration. The FIRST, a man portable sensor, provides datacubes of up to 320x256 pixels at 0.35 mrad spatial resolution over the 8-12 ?m spectral range at spectral resolutions of up to 0.25 cm -1. The FIRST has been used in several field measurements, including demonstration of standoff chemical agent detection. One key feature of the FIRST is its ability to give calibrated measurements. The quality of the radiometric and spectral calibration will be presented in this paper. During the field measurements, the FIRST operated under changing environmental conditions while many calibration measurements were taken. In this paper, we will present the stability of the calibration of the FIRST obtained during the field campaigns.

Farley, Vincent; Chamberland, Martin; Vallières, Alexandre; Villemaire, André; Legault, Jean-François

2006-06-01

25

Hyperspectral Image Compression Method Based on Spectral Statistical Correlation  

Microsoft Academic Search

The hyperspectral imaging technology is one of the most important focuses of the remote sensing domain. Research on hyperspectral image compression method has important practical significance. Compared with other traditional remote sensors' data, hyperspectral images include both spatial and spectral redundancies. Most popular image coding algorithms attempt to transform the image data so that the transformed coefficients are largely uncorrelated.

Wenjie Wang; Zhongming Zhao; Haiqing Zhu

2009-01-01

26

Mine detection experiments using hyperspectral sensors  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging is an important technology for the detection of surface and buried land mines from an airborne platform. For this reason, hyperspectral was included with SAR sensors in the two deployments that were executed by the CECOM RDEC Night Vision and Electronic Systems Directorate (NVESD) in Fall 2002 and in Spring 2003. The purpose of these deployments was to bring together a wide variety of airborne sensors for the detection of mines, with well ground-truthed targets. The hyperspectral sensors included the Airborne Hyperspectral Imager (AHI), a University of Hawaii LWIR HSI sensor and the Compact Airborne Spectral Sensor (COMPASS), an NVESD VNIR/SWIR sensor. Both a high frequency SAR and a ground penetrating radar were also flown. These experiments were carried out at sites where an extensive array of buried and surface mines were deployed. At the first location, on the east coast, the mines were deployed against several different backgrounds ranging from bare dirt to long grass. At the second location in the desert southwest, the mines were placed on backgrounds ranging from loose sand to mixed sand and vegetation. The COMPASS and AHI sensors were both placed on the Twin Otter aircraft, and data was collected with the airplane as low as 700 ft and as high as 4000 ft. In this paper, the data collected on surface mines will be reviewed, and specific examples from each background type presented. Spectral detection algorithms will be applied to the data and the results of the algorithm processing will be presented.

Winter, Edwin M.; Miller, Miranda A.; Simi, Christopher G.; Hill, Anthony B.; Williams, Timothy J.; Hampton, David; Wood, Mark; Zadnick, Jerry; Sviland, Marc D.

2004-09-01

27

Fast compression implementation for hyperspectral sensor  

NASA Astrophysics Data System (ADS)

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.

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

2010-10-01

28

DMD diffraction measurements to support design of projectors for test and evaluation of multispectral and hyperspectral imaging sensors  

NASA Astrophysics Data System (ADS)

We describe our use of Digital Micromirror Devices (DMDs) for the performance testing, characterization, calibration, and system-level data product validation of multispectral and hyperspectral imaging sensors. We have developed a visible Hyperspectral Image Projector (HIP), which is capable of projecting any combination of many different arbitrarily programmable basis spectra into each image pixel at up to video frame rates. For the full HIP, we use a scheme whereby one DMD array is used in a spectrally programmable source, to produce light having the spectra of materials in the scene (i.e. grass, ocean, target, etc), and a second DMD, optically in series with the first, reflects any combination of these programmable spectra into the pixels of a 1024 ×768 element spatial image, thereby producing temporally-integrated 2D images having spectrally-mixed pixels. The HIP goes beyond conventional Digital Light Processing (DLP) projectors in that each spatial pixel can have an arbitrary spectrum, not just an arbitrary color. As such, the resulting spectral and spatial content of the projected image can simulate realistic scenes that a sensor system must acquire during its use, and can be calibrated using NIST reference instruments. Here we discuss our current HIP developments that span the visible/infrared spectral range of 380 nm through 5400 nm, with particular emphasis on DMD diffraction efficiency measurements in the infrared part of this range.

Rice, Joseph P.; Neira, Jorge E.; Kehoe, Michael; Swanson, Rand

2009-02-01

29

Hyperspectral Image Compression  

NASA Astrophysics Data System (ADS)

Hyperspectral images gathered by satellites or aerial means provide a vast amount of data for geophysicists. A few applications include the exploration of minerals, research of land pollution, and military surveillance. NASA and other agencies are producing gigabytes of hyperspectral images which need to be transmitted and stored daily. As these images require high compression rates and preservation of data integrity, we are presented with an intriguing compression problem. In our research we investigate two compression algorithms: a near-lossless technique based on minimizing maximum absolute distortion (MAD) and a lossy based algorithm which minimizes mean squared error (MSE). Near-lossless algorithms provide high compression rates and a uniform distribution of error. Whereas MSE based algorithms yield high compression rates but a non-uniform distribution of error. Our goal is to determine which algorithm yields high compression rates and minimal data loss without modifying post processing of hyperspectral data. In order to compare these two compression algorithms and determine their effect on post processing we used ENVI's image processing tools. We classified the decompressed images for each algorithm and compared them to the classified original image.

Wright, Stephanie; Miguel, Agnieszka, , Dr.; Ashbach, Jason

2008-05-01

30

Quantitative Hyperspectral Reflectance Imaging  

PubMed Central

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

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

2008-01-01

31

Scalable Hyperspectral Image Coding  

Microsoft Academic Search

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

Xiaoli Tang; William A. Pearlman

2005-01-01

32

Hyperspectral image compressive projection algorithm  

Microsoft Academic Search

We describe a compressive projection algorithm and experimentally assess its performance when used with a Hyperspectral Image Projector (HIP). The HIP is being developed by NIST for system-level performance testing of hyperspectral and multispectral imagers. It projects a two-dimensional image into the unit under test (UUT), whereby each pixel can have an independently programmable arbitrary spectrum. To efficiently project a

Joseph P. Rice; David W. Allen

2009-01-01

33

Performance of the FIRST: a long-wave infrared hyperspectral imaging sensor  

Microsoft Academic Search

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state are fundamental needs in several fields of applications. Imaging spectrometers have unmatched capabilities to meet the

Vincent Farley; Alexandre Vallières; Martin Chamberland; André Villemaire; Jean-François Legault

2006-01-01

34

Radiometric calibration stability of the FIRST: a longwave infrared hyperspectral imaging sensor  

Microsoft Academic Search

Emerging applications in Defense and Security require sensors with state-of-the-art sensitivity and capabilities. Among these sensors, the imaging spectrometer is an instrument yielding a large amount of rich information about the measured scene. Standoff detection, identification and quantification of chemicals in the gaseous state are fundamental needs in several fields of applications. Imaging spectrometers have unmatched capabilities to meet the

Vincent Farley; Martin Chamberland; Alexandre Vallières; André Villemaire; Jean-François Legault

2006-01-01

35

Simulation of Hyperspectral Images  

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

36

Novel hyperspectral imager for lightweight UAVs  

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

37

Airborne Hyperspectral Imaging System  

NASA Technical Reports Server (NTRS)

A document discusses a hyperspectral imaging instrument package designed to be carried aboard a helicopter. It was developed to map the depths of Greenland's supraglacial lakes. The instrument is capable of telescoping to twice its original length, allowing it to be retracted with the door closed during takeoff and landing, and manually extended in mid-flight. While extended, the instrument platform provides the attached hyperspectral imager a nadir-centered and unobstructed view of the ground. Before flight, the instrument mount is retracted and securely strapped down to existing anchor points on the floor of the helicopter. When the helicopter reaches the destination lake, the door is opened and the instrument mount is manually extended. Power to the instrument package is turned on, and the data acquisition computer is commanded via a serial cable from an onboard user-operated laptop to begin data collection. After data collection is complete, the instrument package is powered down and the mount retracted, allowing the door to be closed in preparation for landing. The present design for the instrument mount consists of a three-segment telescoping cantilever to allow for a sufficient extended length to see around the landing struts and provide a nadir-centered and unobstructed field of view for the hyperspectral imager. This instrument works on the premise that water preferentially absorbs light with longer wavelengths on the red side of the visible spectrum. This property can be exploited in order to remotely determine the depths of bodies of pure freshwater. An imager flying over such a lake receives light scattered from the surface, the bulk of the water column, and from the lake bottom. The strength of absorption of longer-wavelength light depends on the depth of the water column. Through calibration with in situ measurements of the water depths, a depth-determining algorithm may be developed to determine lake depth from these spectral properties of the reflected sunlight.

Behar, Alberto E.; Cooper, Moogega; Adler, John; Jacobson, Tobias

2012-01-01

38

Thermal hyperspectral chemical imaging  

NASA Astrophysics Data System (ADS)

Several chemical compounds have their strongest spectral signatures in the thermal region. This paper presents three push-broom thermal hyperspectral imagers. The first operates in MWIR (2.8-5 ?m) with 35 nm spectral resolution. It consists of uncooled imaging spectrograph and cryogenically cooled InSb camera, with spatial resolution of 320/640 pixels and image rate to 400 Hz. The second imager covers LWIR in 7.6-12 ?m with 32 spectral bands. It employs an uncooled microbolometer array and spectrograph. These imagers have been designed for chemical mapping in reflection mode in industry and laboratory. An efficient line-illumination source has been developed, and it makes possible thermal hyperspectral imaging in reflection with much higher signal and SNR than is obtained from room temperature emission. Application demonstrations including sorting of dark plastics and mineralogical mapping of drill cores are presented. The third imager utilizes a cryo-cooled MCT array with precisely temperature stabilized optics. The optics is not cooled, but instrument radiation is suppressed by special filtering and corrected by BMC (Background-Monitoring-on-Chip) method. The approach provides excellent sensitivity in an instrument which is portable and compact enough for installation in UAVs. The imager has been verified in 7.6 to 12.3 ?m to provide NESR of 18 mW/(m2 sr ?m) at 10 ?m for 300 K target with 100 spectral bands and 384 spatial samples. It results in SNR of higher than 500. The performance makes possible various applications from gas detection to mineral exploration and vegetation surveys. Results from outdoor and airborne experiments are shown.

Holma, Hannu; Hyvärinen, Timo; Mattila, Antti-Jussi; Kormano, Ilkka

2012-05-01

39

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

Microsoft Academic Search

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

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

2008-01-01

40

Hyperspectral Imaging of River Systems.  

National Technical Information Service (NTIS)

The objective of this work is to put a hyperspectral imager in space to demonstrate the ability to covertly acquire data on shallow water bathymetry, bottom types, hazards to navigation, water clarity and beach and shore trafficability. The proposed activ...

C. O. Davis

2011-01-01

41

Image Segmentation of Hyperspectral Imagery.  

National Technical Information Service (NTIS)

Hyperspectral imagery (HSI), a passive technique creating a large collection of images of fine resolution across the infrared spectrum is currently being considered for U.S. Army tactical applications. An important tactical application of infrared (IR) hy...

M. Wellman N. Nasrabadi

2003-01-01

42

Advanced pushbroom hyperspectral LWIR imagers  

Microsoft Academic Search

Performance studies and instrument designs for hyperspectral pushbroom imagers in thermal wavelength region are introduced. The studies involve imaging systems based on both MCT and microbolometer detector. All the systems employ pushbroom imaging spectrograph with transmission grating and on-axis optics. The aim of the work was to design high performance instruments with good image quality and compact size for various

Hannu Holma; Timo Hyvärinen; Jarmo Lehtomaa; Harri Karjalainen; Risto Jaskari

2009-01-01

43

Common hyperspectral image database design  

Microsoft Academic Search

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

Lixun Tian; Ningfang Liao; Ali Chai

2009-01-01

44

Development of the hyperspectral image decorrelation  

Microsoft Academic Search

The hyperspectral imaging spectrometer can supply hundreds of narrow band spectral data, which has high spatial and spectral resolution, and meanwhile the amount of data becomes huge. Therefore, the efficient compression algorithms become necessary. According to the characteristics of hyperspectral images, spatial and spectral decorrelation is necessary before compression. In this paper, the characteristics of hyperspectral images are presented firstly.

Hai-ping Wai; Bao-jun Zhao; Pei-kun He

2008-01-01

45

Hyperspectral Image Analysis for Skin Tumor Detection  

NASA Astrophysics Data System (ADS)

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

Kong, Seong G.; Park, Lae-Jeong

46

Miniaturization of a SWIR hyperspectral imager  

NASA Astrophysics Data System (ADS)

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 here, resulting in a microHSITM SWIR Hyperspectral sensor, capable of operating in the 850-1700 nm wavelength range. The microHSI spectrometer weighs 910 g from slit input to camera output. This spectrometer can accommodate custom foreoptics to adapt to a wide range of fields-of-view (FOV). The current application calls for a 15 degree FOV, and utilizes an InGaAs image sensor with a spatial format of 640 x 25 micron pixels. This results in a slit length of 16 mm, and a foreoptics focal length of 61 mm, operating at F# = 2.8. The resulting IFOV is 417 ?rad for this application, and a spectral dispersion of 4.17 nm/pixel. A prototype SWIR microHSI was fabricated, and the blazed diffraction grating was embedded within the optical blocks, resulting in a 72% diffraction efficiency at the wavelength of 1020 nm. This spectrometer design is capable of accommodating slit lengths of up to 25.6 mm, which opens up a wide variety of applications. The microHSI concepts can be extended to other wavelength regions, and a miniaturized LWIR microHSI sensor is in the conceptual design stage.

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

2011-05-01

47

Fiber optic snapshot hyperspectral imager  

NASA Astrophysics Data System (ADS)

OPTRA is developing a snapshot hyperspectral imager (HSI) employing a fiber optic bundle and dispersive spectrometer. The fiber optic bundle converts a broadband spatial image to an array of fiber columns which serve as multiple entrance slits to a prism spectrometer. The dispersed spatially resolved spectra are then sampled by a two-dimensional focal plane array (FPA) at a greater than 30 Hz update rate, thereby qualifying the system as snapshot. Unlike snapshot HSI systems based on computed tomography or coded apertures, our approach requires only the remapping of the FPA frame into hyperspectral cubes rather than a complex reconstruction. Our system has high radiometric efficiency and throughput supporting sufficient signal to noise for hyperspectral imaging measurements made over very short integration times (< 33 ms). The overall approach is compact, low cost, and contains no moving parts, making it ideal for unmanned airborne surveillance. In this paper we present a preliminary design for the fiber optic snapshot HSI system.

Mansur, David J.; Rentz Dupuis, Julia; Vaillancourt, Robert

2012-05-01

48

Adaptive MWIR spectral imaging sensor  

Microsoft Academic Search

An MWIR spectral imaging sensor based on dual direct vision prism (DVP) architecture is described. This sensor represents a third generation of the Chromotomographic Hyperspectral Imaging Sensor (CTHIS). In the new sensor, a direct vision prism is synthesized by the vector addition of the spectral response of two matched, but independently aligned DVP's. The resulting sensor dispersion varies from zero

F. D. Shepherd; J. M. Mooney; T. E. Reeves; P. Dumont; S. DiSalvo

2008-01-01

49

Hyperspectral Image Exploitation SBIR Phase 2.  

National Technical Information Service (NTIS)

The primary goal of the Hyperspectral Image Exploitation project is the development of a prototype software system for the processing and analyzing of hyperspectral data sets. This software system will be used by the Topographic Engineering Center, (TEC) ...

1991-01-01

50

Hyperspectral imaging in the coastal ocean  

NASA Astrophysics Data System (ADS)

Data from moderate resolution ocean color sensors, such as SeaWiFS and MODIS have greatly enhanced our understanding of the open ocean and shelf waters. However, the spatial and spectral complexity of the near coastal ocean, require higher resolution systems for the littoral zone. Recent experiments with aircraft imaging spectrometers have demonstrated their potential to be powerful tools for the characterization of the coastal ocan. Using the continuous spectral signature it is possible to measure shallow water bathymetry and bottom characteristics, and to gain insight into the distribution of phytoplankton and ot her optically active constituents. To demonstrate this I present recent results using AVIRIS and PHILLS data from the coastal environment. To obtain large area, repeated coverage of the coastal ocean two spaceborne hyperspectral imagers are planned. The Navy has joined in a partnership with industry to build and fly the Naval EarthMap Observer (NEMO). The NEMO spacecraft has the Coastal Ocean Imaging Spectrometer (COIS) a hyperspectral imager with adequate spectral and spatial resolution and a high signal-to-noise ratio to provide long-term monitoring and real-time characterization of the coastal environment. Additionally, the Integrated Program Office is considering a Coastal Ocean Imager (COI) as part of an Ocean Observer Spacecraft. COI is a hyperspectral imager in the visible with a two band thermal-IR imager for sea surface temperature. COI would provide 100 m resolution imagery over a 150 km wide swath of the coastal ocean.

Davis, Curtiss O.

2002-09-01

51

Hyperspectral pixels in 2D imaging FPAs?  

NASA Astrophysics Data System (ADS)

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 spectral information at the pixel level without the need for external, dispersive optical elements. A variation on this approach, described here, uses detector material of fixed composition, with waveband sensitivity achieved as a function of depth, made possible by the spectral dependence of the absorption coefficient. An increase in the number of wavebands provides hyperspectral capability at the pixel level, hereafter denoted hyperspectral pixel. This technology may someday become possible through advanced detector array architectures, with photons of different wavelength continuously absorbed at different depths, and their resulting photocurrents isolated with a vertical grid of contacts or an equivalent mechanism for transporting depth-dependent signal photocurrent to a read-out circuit unit cell.

Levan, Paul D.; Beecken, Brian P.

2009-08-01

52

SWIR hyperspectral imaging detector for surface residues  

NASA Astrophysics Data System (ADS)

ChemImage has developed a SWIR Hyperspectral Imaging (HSI) sensor which uses hyperspectral imaging for wide area surveillance and standoff detection of surface residues. Existing detection technologies often require close proximity for sensing or detecting, endangering operators and costly equipment. Furthermore, most of the existing sensors do not support autonomous, real-time, mobile platform based detection of threats. The SWIR HSI sensor provides real-time standoff detection of surface residues. The SWIR HSI sensor provides wide area surveillance and HSI capability enabled by liquid crystal tunable filter technology. Easy-to-use detection software with a simple, intuitive user interface produces automated alarms and real-time display of threat and type. The system has potential to be used for the detection of variety of threats including chemicals and illicit drug substances and allows for easy updates in the field for detection of new hazardous materials. SWIR HSI technology could be used by law enforcement for standoff screening of suspicious locations and vehicles in pursuit of illegal labs or combat engineers to support route-clearance applications- ultimately to save the lives of soldiers and civilians. In this paper, results from a SWIR HSI sensor, which include detection of various materials in bulk form, as well as residue amounts on vehicles, people and other surfaces, will be discussed.

Nelson, Matthew P.; Mangold, Paul; Gomer, Nathaniel; Klueva, Oksana; Treado, Patrick

2013-05-01

53

Curvelet based hyperspectral image fusion  

NASA Astrophysics Data System (ADS)

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

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

2013-08-01

54

Enhanced Visualization of Hyperspectral Images  

Microsoft Academic Search

We present an enhanced visualization algorithm for hyperspectral images (HSIs). The visualization is based on the projection onto color matching functions of the human vision system. A contrast enhancement procedure is introduced by the fusion of the gradient information of the individual HSI bands. Both visualization and enhancement are combined into a multires- olution framework using wavelets. The HSI is

Zahid Mahmood; Paul Scheunders

2011-01-01

55

Enhanced visualization of hyperspectral images  

Microsoft Academic Search

An enhanced visualization algorithm for hyperspectral images (HSI) is presented in this paper. The visualization is based on the projection onto color matching functions of the human vision system. A contrast enhancement procedure is introduced making use of multiband gradient information. Both visualization and enhancement are combined into a multiresolution framework using wavelets. The HSI is transformed into a specific

Zahid Mahmood; Paul Scheunders

2010-01-01

56

Hyperspectral sensor HSC3000 for nano-satellite TAIKI  

NASA Astrophysics Data System (ADS)

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

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

2008-11-01

57

Synergetics Framework for Hyperspectral Image Classification  

NASA Astrophysics Data System (ADS)

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.

Müller, R.; Cerra, D.; Reinartz, P.

2013-05-01

58

Hyperspectral image compressive projection algorithm  

NASA Astrophysics Data System (ADS)

We describe a compressive projection algorithm and experimentally assess its performance when used with a Hyperspectral Image Projector (HIP). The HIP is being developed by NIST for system-level performance testing of hyperspectral and multispectral imagers. It projects a two-dimensional image into the unit under test (UUT), whereby each pixel can have an independently programmable arbitrary spectrum. To efficiently project a single frame of dynamic realistic hyperspectral imagery through the collimator into the UUT, a compression algorithm has been developed whereby the series of abundance images and corresponding endmember spectra that comprise the image cube of that frame are first computed using an automated endmember-finding algorithm such as the Sequential Maximum Angle Convex Cone (SMACC) endmember model. Then these endmember spectra are projected sequentially on the HIP spectral engine in sync with the projection of the abundance images on the HIP spatial engine, during the singleframe exposure time of the UUT. The integrated spatial image captured by the UUT is the endmember-weighted sum of the abundance images, which results in the formation of a datacube for that frame. Compressive projection enables a much smaller set of broadband spectra to be projected than monochromatic projection, and thus utilizes the inherent multiplex advantage of the HIP spectral engine. As a result, radiometric brightness and projection frame rate are enhanced. In this paper, we use a visible breadboard HIP to experimentally assess the compressive projection algorithm performance.

Rice, Joseph P.; Allen, David W.

2009-05-01

59

Advanced pushbroom hyperspectral LWIR imagers  

NASA Astrophysics Data System (ADS)

Performance studies and instrument designs for hyperspectral pushbroom imagers in thermal wavelength region are introduced. The studies involve imaging systems based on both MCT and microbolometer detector. All the systems employ pushbroom imaging spectrograph with transmission grating and on-axis optics. The aim of the work was to design high performance instruments with good image quality and compact size for various application requirements. A big challenge in realizing these goals without considerable cooling of the whole instrument is to control the instrument radiation from all the surfaces of the instrument itself. This challenge is even bigger in hyperspectral instruments, where the optical power from the target is spread spectrally over tens of pixels, but the instrument radiation is not dispersed. Without any suppression, the instrument radiation can overwhelm the radiation from the target by 1000 times. In the first imager design, BMC-technique (background monitoring on-chip), background suppression and temperature stabilization have been combined with cryo-cooled MCT-detector. The performance of a very compact hyperspectral imager with 84 spectral bands and 384 spatial samples has been studied and NESR of 18 mW/(m2sr?m) at 10 ?m wavelength for 300 K target has been achieved. This leads to SNR of 580. These results are based on a simulation model. The second version of the imager with an uncooled microbolometer detector and optics in ambient temperature aims at imaging targets at higher temperatures or with illumination. Heater rods with ellipsoidal reflectors can be used to illuminate the swath line of the hyperspectral imager on a target or sample, like drill core in mineralogical analysis. Performance characteristics for microbolometer version have been experimentally verified.

Holma, Hannu; Hyvärinen, Timo; Lehtomaa, Jarmo; Karjalainen, Harri; Jaskari, Risto

2009-05-01

60

Sonification of hyperspectral image data  

NASA Astrophysics Data System (ADS)

There are many reconnaissance tasks which involve an image analyst viewing data from hyperspectral imaging systems and attempting to interpret it. Hyperspectral image data is intrinsically hard to understand, even when armed with mathematical knowledge and a range of current processing algorithms. This research is motivated by the search for new ways to convey information about the spectral content of imagery to people. In order to develop and assess the novel algorithms proposed, we have developed a tool for transforming different aspects of spectral imagery into sounds that an analyst can hear. Trials have been conducted which show that the use of these sonic mappings can assist a user in tasks such as rejecting false alarms generated by automatic detection algorithms. This paper describes some of the techniques used and reports on the results of user trials.

Bernhardt, Mark; Cowell, Catherine; Oxford, William

2007-04-01

61

Hyperspectral imaging of ischemic wounds  

NASA Astrophysics Data System (ADS)

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.

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

2012-02-01

62

The application of hyperspectral sensors to the detection of land mines  

Microsoft Academic Search

Hyperspectral imaging is an important technology for the detection of surface and buried land mines from an airborne platform. For this reason, hyperspectral was included in the three experiments that were executed by the Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) in Fall 2002, Spring 2003 and Summer 2004. The purpose of these experiments was to bring

Edwin M. Winter

2005-01-01

63

Compact visible/near-infrared hyperspectral imager  

NASA Astrophysics Data System (ADS)

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 is mounted on a bearing so that it can be rotated on the optical axis of the telescope. As the prism is rotated, the projected image is multiplexed on elements of the focal plane array. Computational methods are used to reconstruct the scene at each wavelength; an approach similar to the limited-angle tomography techniques used in medicine. The sensor covers the visible through near infrared spectrum of silicon photodiodes. The sensor weighs less than 6 pounds has under 300 in3 volume and requires 20 watts. It produces image cubes, with 64 spectral bands, at rates up to 10 Hz. By operating in relatively fast framing mode, the sensor allows characterization of transient events. We will describe the sensor configuration and method of operation. We also present examples of sensor spectral image data.

Murguia, James E.; Reeves, Toby D.; Mooney, Jonathan M.; Ewing, William S.; Shepherd, Freeman D.; Brodzik, Andrzej K.

2000-07-01

64

Development of the hyperspectral image decorrelation  

NASA Astrophysics Data System (ADS)

The hyperspectral imaging spectrometer can supply hundreds of narrow band spectral data, which has high spatial and spectral resolution, and meanwhile the amount of data becomes huge. Therefore, the efficient compression algorithms become necessary. According to the characteristics of hyperspectral images, spatial and spectral decorrelation is necessary before compression. In this paper, the characteristics of hyperspectral images are presented firstly. Secondly, the research on hyperspectral image decorrelation is summarized. Techniques based on prediction, techniques based on vector quantization, and techniques based on transform coding are presented here. Finally, the future development is referred.

Wai, Hai-ping; Zhao, Bao-jun; He, Pei-kun

2008-03-01

65

Hyperspectral projection of a coral reef scene using the NIST hyperspectral image projector  

NASA Astrophysics Data System (ADS)

Improving the understanding of the optical scene components associated with coral reef imagery will advance the ability to map and monitor coral reefs using remote sensing. One tool that can aid in understanding the components in these scenes is the NIST Hyperspectral Image Projector (HIP). In this paper a hyperspectral scene is reformatted for projection using the HIP by first unmixing image spectra into endmembers. The abundance images representing each of the endmembers are then projected using the NIST HIP and collected by a hyperspectral imager. Since the scene is from a digital source, it can be used repeatedly without concern for changing measurement conditions. This work represents one of the first steps in developing scene projection capabilities that can be used for sensor characterization, algorithm testing or to have optical components changed independently in order to better understand the overall effects on the total observed scene.

Allen, David W.; Rice, Joseph P.; Goodman, James A.

2009-05-01

66

Supervised hyperspectral image segmentation using active learning  

Microsoft Academic Search

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

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

2010-01-01

67

Segmentation for Hyperspectral Images with Priors  

Microsoft Academic Search

\\u000a In this paper, we extend the Chan-Vese model for image segmentation in [1] to hyperspectral image segmentation with shape\\u000a and signal priors. The use of the Split Bregman algorithm makes our method very efficient compared to other existing segmentation\\u000a methods incorporating priors. We demonstrate our results on aerial hyperspectral images.

Jian Ye; Todd Wittman; Xavier Bresson; Stanley Osher

2010-01-01

68

Supercontinuum-source-based facility for evaluation of hyperspectral imagers  

NASA Astrophysics Data System (ADS)

The next Japanese earth observing hyperspectral/multispectral imager mission, the HISUI (Hyper-spectral Imager SUIte) mission, is currently underway. In order to guarantee the hyperspectral images with a high spatial and wavelength resolution, it is necessary to evaluate the difference of the spectral sensitivities among the detector devices arrayed twodimensionally and correct spectral and spatial misregistrations and the effect of stray light. Since there are tens of thousands of detectors in the two-dimensional-array sensor, they have to be evaluated in parallel, instead of point by point, with the special technique for hyperspectral imagers. Hence, the new calibration system which has high radiance with the spatial uniformity and widely tunable wavelength range is required instead of conventional lamp systems which have poor power to calibrate arrayed devices at once. In this presentation, a supercontinuum-source-based system for calibration of hyperspectral imagers and its preliminary performance are described. Supercontinuum light is white light with continuous and broad spectra, which is generated by nonlinear optical effects of ultrashort pulse lasers in photonic crystal fibers. Using the system, the relative spectral responsivity and spectral misregistration of the hyperspectral imager, which is consist of a polychromator and twodimensionally arrayed CCD, are measured.

Yamaguchi, Yu; Yamada, Yoshiro; Ishii, Juntaro

2013-10-01

69

Highly parallel CMOS lock-in optical sensor array for hyperspectral recording in scanned imaging systems  

NASA Astrophysics Data System (ADS)

Many optical measurements that are subject to high levels of background illumination rely on phase sensitive lock-in detection to extract the useful signal. If modulation is applied to the portion of the signal that contains information, lockin detection can perform very narrowband (and hence low noise) detection at frequencies well away from noise sources such as 1/f and instrumental drift. Lock-in detection is therefore used in many optical imaging and measurement techniques, including optical coherence tomography, heterodyne interferometry, optoacoustic tomography and a range of pump-probe techniques. Phase sensitive imaging is generally performed sequentially with a single photodetector and a lock-in amplifier. However, this approach severely limits the rate of multi-dimensional image acquisition. We present a novel linear array chip that can perform phase sensitive, shot-noise limited optical detection in up to 256 parallel channels. This has been achieved by employing four independent wells in each pixel, and massively enhancing the intrinsic well depth to suppress the effect of optical shot noise. Thus the array can reduce the number of dimensions that need to be sequentially scanned and greatly speed up acquisition. Results demonstrating spatial and spectral parallelism in pump-probe experiments are presented where the a.c. amplitude to background ratio approaches 1 part in one million.

Light, Roger A.; Smith, Richard J.; Johnston, Nicholas S.; Sharples, Steve D.; Somekh, Michael G.; Pitter, Mark C.

2010-02-01

70

Hyperspectral Image Analysis Program  

NASA Technical Reports Server (NTRS)

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.

1985-01-01

71

Multiband Lossless Compression of Hyperspectral Images  

Microsoft Academic Search

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

Enrico Magli

2009-01-01

72

Structured Gaussian Components for Hyperspectral Image Classification  

Microsoft Academic Search

The large number of bands in hyperspectral images leads to a large number of parameters to estimate. It has been argued in the literature that class-conditional distributions of hyperspectral images are non-Gaussian; thus, multiple components might be needed to describe the classes accurately. In this paper, we propose to represent the Gaussian components in the classifier with a smaller number

Asbjørn Berge; Anne H. Schistad Solberg

2006-01-01

73

Hyperspectral image data compression based on DSP  

Microsoft Academic Search

The huge data volume of hyperspectral image challenges its transportation and store. It is necessary to find an effective method to compress the hyperspectral image. Through analysis and comparison of current various algorithms, a mixed compression algorithm based on prediction, integer wavelet transform and embedded zero-tree wavelet (EZW) is proposed in this paper. We adopt a high-powered Digital Signal Processor

Jiming Fan; Jiankang Zhou; Xinhua Chen; Weimin Shen

2010-01-01

74

Novel miniaturized hyperspectral sensor for UAV and space applications  

NASA Astrophysics Data System (ADS)

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.

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

2009-09-01

75

Eigen wavelet: hyperspectral image compression algorithm  

Microsoft Academic Search

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

S. Srinivasan; L. N. Kanal

1999-01-01

76

Anomaly clustering in hyperspectral images  

NASA Astrophysics Data System (ADS)

The topological anomaly detection algorithm (TAD) differs from other anomaly detection algorithms in that it uses a topological/graph-theoretic model for the image background instead of modeling the image with a Gaussian normal distribution. In the construction of the model, TAD produces a hard threshold separating anomalous pixels from background in the image. We build on this feature of TAD by extending the algorithm so that it gives a measure of the number of anomalous objects, rather than the number of anomalous pixels, in a hyperspectral image. This is done by identifying, and integrating, clusters of anomalous pixels via a graph theoretical method combining spatial and spectral information. The method is applied to a cluttered HyMap image and combines small groups of pixels containing like materials, such as those corresponding to rooftops and cars, into individual clusters. This improves visualization and interpretation of objects.

Doster, Timothy J.; Ross, David S.; Messinger, David W.; Basener, William F.

2009-05-01

77

Infrared hyperspectral imaging stokes polarimeter  

NASA Astrophysics Data System (ADS)

This work presents the design, development, and testing of a field portable imaging spectropolarimeter that operates over the short-wavelength and middle-wavelength portion of the infrared spectrum. The sensor includes a pair of sapphire Wollaston prisms and several high order retarders to produce the first infrared implementation of an imaging Fourier transform spectropolarimeter, providing for the measurement of the complete spectropolarimetric datacube over the passband. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration when compared to an unequal path interferometer, such as a Michelson. Polarimetric data are acquired through the use of channeled spectropolarimetry to modulate the spectrum with the Stokes parameter information. The collected interferogram is Fourier filtered and reconstructed to recover the spatially and spectrally varying Stokes vector data across the image. The intent of this dissertation is to provide the reader with a detailed understanding of the steps involved in the development of this infrared hyperspectral imaging polarimeter (IHIP) instrument. First, Chapter 1 provides an overview of the fundamental concepts relevant to this research. These include imaging spectrometers, polarimeters, and spectropolarimeters. A detailed discussion of channeled spectropolarimetry, including a historical study of previous implementations, is also presented. Next a few of the design alternatives that are possible for this work are outlined and discussed in Chapter 2. The configuration that was selected for the IHIP is then presented in detail, including the optical layout, design, and operation. Chapter 3 then presents an artifact reduction technique (ART) that was developed to improve the IHIP's spectropolarimetric reconstructions by reducing errors associated with non-band-limited spectral features. ART is experimentally verified in the infrared using a commercial Fourier transform spectrometer in combination with Yttrium Vanadate as well as Cadmium Sulfide retarders. The remainder of this dissertation then details the testing and analysis of the IHIP instrument. Implementation of ART with the IHIP as well as the employed calibration techniques are described in Chapter 4. Complete calibration of the IHIP includes three distinct processes to provide radiometric, spectral, and polarimetric calibration. With the instrument assembled and calibrated, results and error analyses are presented in Chapter 5. Spectropolarimetric results are obtained in the laboratory as well as outdoors to test the IHIP's real world functionality. The performance of the instrument is also assessed, including experimental measurement of signal-to-noise ratio (SNR), and an analysis of the potential sources of systematic error (such as retarder misalignment and finite polarizer extinction ratio). Chapter 6 presents the design and experimental results for a variable Wollaston prism that can be added to the IHIP to vary the fringe contrast across the field of view. Finally, Chapter 7 includes brief closing remarks summarizing this work and a few observations which may be useful for future infrared imaging Fourier transform channeled spectropolarimeter instruments.

Jones, Julia Craven

78

Common hyperspectral image database design  

NASA Astrophysics Data System (ADS)

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

Tian, Lixun; Liao, Ningfang; Chai, Ali

2009-11-01

79

A Compact Visible\\/Near Infrared Hyperspectral Imager  

Microsoft Academic Search

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

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

2000-01-01

80

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

NASA Astrophysics Data System (ADS)

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.

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

2013-05-01

81

Decorrelate hyperspectral images using spectral correlation  

NASA Astrophysics Data System (ADS)

This paper proposes a new algorithm for lossless compression of hyperspectral images. In our work we found hyperspectral data have unique characteristic based on spectral context and adjacent pixel spectral vectors (curves) highly correlate with each other. Pearson correlation coefficient is an effective measure of spectral similarity between spectral curves to detect horizontal and vertical spectral edge. Thus, spectral correlation is used to prediction in spectral direction for decorrelation of lossless compression of hyperspectral images. Experiments show the proposed algorithm is effective, and it's more important that it has much lower complexity than other algorithms.

Chen, Liang; Liu, Daizhi; Huang, Shiqi

2007-01-01

82

Hyperspectral image fusion by the similarity measure-based variational method  

Microsoft Academic Search

Hyperspectral remote sensing is widely used in many fields suchas agriculture, military detection, mineral exploration, and so on. Hyperspectral data has very high spectral resolution, but much lower spatial resolution than the data obtained by other types of sensors. The low spatial resolution restrains its wide applications. On the contrary, we easily obtain images with high spatial resolution but insufficient

Zhenwei Shi; Zhenyu An; Zhiguo Jiang

2011-01-01

83

Passive shortwave infrared technology and hyperspectral imaging for maritime applications  

NASA Astrophysics Data System (ADS)

We present image data and discuss naval sensing applications of SWIR and Hyperspectral SWIR imaging in littoral and marine environments under various light conditions. These environments prove to be challenging for persistent surveillance applications as light levels may vary over several orders of magnitude within and from scene to scene. Additional difficulties include imaging over long water paths where marine haze and turbulence tend to degrade radiation transmission, and discrimination of low contrast objects under low-light and night imaging. Image data obtained from two separate passive sensor systems, both of which are built around an RVS large format (1280 x 1024) InGaAs FPA with high dynamic range and low noise electronics, are presented. The SWIR camera imager is equipped with a custom 300 mm focal length f/2 narrow field-of-view (6° diagonal) refractive telescope. The Hyperspectral imager has a custom selectable 900/1800 mm focal length telescope with corresponding 1.55°/0.79° field-of-view and fnumbers of 3/6 respectively. The sensor uses 1280 pixels in the spatial direction and a window of 192 are used for the spectral and operates at a nominal frame rate of 120 Hz. To assess field performance of the SWIR/Hyperspectral imagers, comparison is made to output from a scientific grade VNIR camera and two state-of-the-art low-light sensors.

Judd, K. Peter; Waterman, James R.; Nichols, J. M.

2010-04-01

84

Hyperspectral imaging of atherosclerotic plaques in vitro  

NASA Astrophysics Data System (ADS)

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.

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

2011-02-01

85

Parallel Implementation of Hyperspectral Image Processing Algorithms  

Microsoft Academic Search

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.

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

2006-01-01

86

ANOMALY-BASED HYPERSPECTRAL IMAGE COMPRESSION  

Microsoft Academic Search

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-

Qian Du; Wei Zhu; James E. Fowler

2009-01-01

87

Anomaly-Based Hyperspectral Image Compression  

Microsoft Academic Search

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

Qian Du; Wei Zhu; James E. Fowler

2008-01-01

88

Compression of hyperspectral images with enhanced discriminant features  

Microsoft Academic Search

We propose compression algorithms for hyperspectral images with enhanced discriminant features. As the dimension of remotely sensed images increases, the need for efficient compression algorithms for hyperspectral images also increases. However, when hyperspectral images are compressed with conventional image compression algorithms, which have been developed to minimize mean squared errors, discriminant features of the original data may be lost during

Chulhee Lee; Euisun Choi

2003-01-01

89

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

Microsoft Academic Search

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

T. Jitsufuchi

2007-01-01

90

Spectral Decomposition Methods for Hyperspectral Image Compression  

Microsoft Academic Search

The Spectral Image Decomposition (SPID) compres- sor uses techniques borrowed from spectral image analysis to achieve a high degree of compression on hyperspectral images. The purpose of this compressor is to provide real-time compres- sion for images captured one line at a time using a \\

Paul Jacobs; Christian Miller; Jared Wolff; Xiuhong Sun; Patrick L. Coronado; Guo-Qiang Zhang

2006-01-01

91

Infrared hyperspectral imaging polarimeter using birefringent prisms.  

PubMed

A compact short-wavelength and middle-wavelength infrared hyperspectral imaging polarimeter (IHIP) is introduced. The sensor includes a pair of sapphire Wollaston prisms and several high-order retarders to form an imaging Fourier transform spectropolarimeter. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration versus an unequal path interferometer, such as a Michelson. Polarimetric data are acquired through the use of channeled spectropolarimetry to modulate the spectrum with the Stokes parameter information. The collected interferogram is Fourier filtered and reconstructed to recover the spatially and spectrally varying Stokes vector data across the image. The IHIP operates over a ±5° field of view and implements a dual-scan false signature reduction technique to suppress polarimetric aliasing artifacts. In this paper, the optical layout and operation of the IHIP sensor are presented in addition to the radiometric, spectral, and polarimetric calibration techniques used with the system. Spectral and spectropolarimetric results from the laboratory and outdoor tests with the instrument are also presented. PMID:21394189

Craven-Jones, Julia; Kudenov, Michael W; Stapelbroek, Maryn G; Dereniak, Eustace L

2011-03-10

92

The HyperSpectral Image Compression System Based on DSP  

Microsoft Academic Search

The hyper-spectral image compression is one of the front technologies in the remote sensing. The hyper-spectral image has enormous data quantity, so it is important to research on the hyper-spectral image compression. Based on the spectral LOCO-I prediction algorithm, the hyper-spectral image compression system is completed with the DSP+CPLD technology. The result shows that the system can compress the image

Liu Qianwen; Hu Bingliang

2008-01-01

93

Portable Hyperspectral Imaging Broadens Sensing Horizons  

NASA Technical Reports Server (NTRS)

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.

2007-01-01

94

Lossless Compression of Hyperspectral Image Based on 3DLMS Prediction  

Microsoft Academic Search

This aiming at improving the lossless compression ratio of hyperspectral image, a three-dimensional LMS (3DLMS) algorithm is first deduced and applied into the field of hyperspectral image compression. A novel adaptive prediction model based on 3DLMS algorithm for lossless compression of hyperspectral image is proposed and optimized by the local casual set mean subtraction method. Experimental results on AVIRIS images

Yonghong Chen; Zelin Shi; Deqiang Li

2009-01-01

95

Designing microarray phantoms for hyperspectral imaging validation  

PubMed Central

The design and fabrication of custom-tailored microarrays for use as phantoms in the characterization of hyperspectral imaging systems is described. Corresponding analysis methods for biologically relevant samples are also discussed. An image-based phantom design was used to program a microarrayer robot to print prescribed mixtures of dyes onto microscope slides. The resulting arrays were imaged by a hyperspectral imaging microscope. The shape of the spots results in significant scattering signals, which can be used to test image analysis algorithms. Separation of the scattering signals allowed elucidation of individual dye spectra. In addition, spectral fitting of the absorbance spectra of complex dye mixtures was performed in order to determine local dye concentrations. Such microarray phantoms provide a robust testing platform for comparisons of hyperspectral imaging acquisition and analysis methods.

Clarke, Matthew L.; Lee, Ji Youn; Samarov, Daniel V.; Allen, David W.; Litorja, Maritoni; Nossal, Ralph; Hwang, Jeeseong

2012-01-01

96

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

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

97

Pansharpening of Hyperspectral Images in Urban Areas  

NASA Astrophysics Data System (ADS)

Pansharpening has proven to be a valuable method for resolution enhancement of multi-band images when spatially high-resolving panchromatic images are available in addition. In principle, pansharpening can beneficially be applied to hyperspectral images as well. But whereas the grey values of multi-spectral images comprise at most relative information about the registered intensities, calibrated hyperspectral images are supposed to provide absolute reflectivity values of the respective material surfaces. This physical significance of the hyperspectral data should be preserved within the pansharpening process as much as possible. In this paper we compare several common pansharpening methods such as Principal Component Fusion, Wavelet Fusion, Gram-Schmidt transform and investigate their applicability for hyperspectral data. Our focus is on the impact of the pansharpening on material classifications. Apart from applying common quality measures, we compare the results of material classifications from hyperspectral data, which were pansharpened by different methods. In addition we propose an alternative pansharpening method which is based on an initial segmentation of the panchromatic image with an additional use of map vector data.

Chisense, C.; Engels, J.; Hahn, M.; Gülch, E.

2012-08-01

98

High-resolution hyperspectral imaging via matrix factorization  

Microsoft Academic Search

Hyperspectral imaging is a promising tool for applications in geosensing, cultural heritage and beyond. However, compared to current RGB cameras, existing hyperspectral cameras are severely limited in spatial resolution. In this paper, we introduce a simple new technique for reconstructing a very high-resolution hyperspectral image from two readily obtained measurements: A lower-resolution hyperspectral image and a high-resolution RGB image. Our

Rei Kawakami; Yasuyuki Matsushita; John Wright; Moshe Ben-Ezra; Yu-Wing Tai; Katsushi Ikeuchi

2011-01-01

99

Hyperspectral Imaging of River Systems.  

National Technical Information Service (NTIS)

The Navy has a requirement to rapidly and covertly characterize the coastal environment in support of Joint Strike Initiatives. Over the past 15 years we have demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acqui...

C. O. Davis

2010-01-01

100

Hyperspectral Imaging of River Systems.  

National Technical Information Service (NTIS)

The Navy has a requirement to rapidly and covertly characterize the coastal environment in support of Joint Strike Initiatives. Over the past 16 years we have demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acqui...

C. O. Davis

2012-01-01

101

Learning Conditional Random Fields for Classification of Hyperspectral Images  

Microsoft Academic Search

Hyperspectral images exhibit strong dependencies across spatial and spectral neighbors, which have been proved to be very useful for hyperspectral image classification. State-of-the-art hyperspectral image classification algorithms use the dependencies in a heuristic way or in probabilistic frameworks but impose unreasonable assumptions on observed data. In this paper, we formulate a conditional random field (CRF) to replace such heuristics and

Ping Zhong; Runsheng Wang

2010-01-01

102

Lossless Hyperspectral Image Compression Using Context-Based Conditional Averages  

Microsoft Academic Search

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

Hongqiang Wang; S. Derin Babacan; Khalid Sayood

2005-01-01

103

On Endmember Identification in Hyperspectral Images Without Pure Pixels: A Comparison of Algorithms  

Microsoft Academic Search

Hyperspectral imaging is an active area of research in Earth and planetary observation. One of the most important techniques\\u000a for analyzing hyperspectral images is spectral unmixing, in which mixed pixels (resulting from insufficient spatial resolution\\u000a of the imaging sensor) are decomposed into a collection of spectrally pure constituent spectra, called endmembers weighted by their correspondent fractions, or abundances. Over the

Javier Plaza; Eligius M. T. Hendrix; Inmaculada García; Gabriel Martín; Antonio Plaza

2012-01-01

104

Tongue Tumor Detection in Medical Hyperspectral Images  

PubMed Central

A hyperspectral imaging system to measure and analyze the reflectance spectra of the human tongue with high spatial resolution is proposed for tongue tumor detection. To achieve fast and accurate performance for detecting tongue tumors, reflectance data were collected using spectral acousto-optic tunable filters and a spectral adapter, and sparse representation was used for the data analysis algorithm. Based on the tumor image database, a recognition rate of 96.5% was achieved. The experimental results show that hyperspectral imaging for tongue tumor diagnosis, together with the spectroscopic classification method provide a new approach for the noninvasive computer-aided diagnosis of tongue tumors.

Liu, Zhi; Wang, Hongjun; Li, Qingli

2012-01-01

105

Preliminary results from an infrared hyperspectral imaging polarimeter  

NASA Astrophysics Data System (ADS)

We present results from a SWIR/MWIR infrared hyperspectral imaging polarimeter (IHIP). The sensor includes a pair of sapphire Wollaston prisms and several high order retarders to form an imaging Fourier transform spectropolarimeter. The Wollaston prisms serve as a birefringent interferometer with reduced sensitivity to vibration versus an unequal path interferometer, such as a Michelson. Polarimetric data are acquired through the use of channeled spectropolarimetry to modulate the spectrum with the Stokes parameter information. We discuss the operation of the IHIP sensor, in addition to our calibration techniques. Lastly, spectropolarimetric results from the laboratory and outdoor tests are presented.

Craven-Jones, Julia; Kudenov, Michael W.; Stapelbroek, Maryn G.; Dereniak, Eustace L.

2011-09-01

106

[Design of hyperspectral imaging system based on LCTF].  

PubMed

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

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

2008-10-01

107

Hyperspectral image feature extraction accelerated by GPU  

NASA Astrophysics Data System (ADS)

PCA (principal components analysis) algorithm is the most basic method of dimension reduction for high-dimensional data1, which plays a significant role in hyperspectral data compression, decorrelation, denoising and feature extraction. With the development of imaging technology, the number of spectral bands in a hyperspectral image is getting larger and larger, and the data cube becomes bigger in these years. As a consequence, operation of dimension reduction is more and more time-consuming nowadays. Fortunately, GPU-based high-performance computing has opened up a novel approach for hyperspectral data processing6. This paper is concerning on the two main processes in hyperspectral image feature extraction: (1) calculation of transformation matrix; (2) transformation in spectrum dimension. These two processes belong to computationally intensive and data-intensive data processing respectively. Through the introduction of GPU parallel computing technology, an algorithm containing PCA transformation based on eigenvalue decomposition 8(EVD) and feature matching identification is implemented, which is aimed to explore the characteristics of the GPU parallel computing and the prospects of GPU application in hyperspectral image processing by analysing thread invoking and speedup of the algorithm. At last, the result of the experiment shows that the algorithm has reached a 12x speedup in total, in which some certain step reaches higher speedups up to 270 times.

Qu, HaiCheng; Zhang, Ye; Lin, Zhouhan; Chen, Hao

2012-10-01

108

Phase congruency assesses hyperspectral image quality  

NASA Astrophysics Data System (ADS)

Blind image quality assessment (QA) is a tough task especially for hyperspectral imagery which is degraded by noise, distortion, defocus, and other complex factors. Subjective hyperspectral imagery QA methods are basically measured the degradation of image from human perceptual visual quality. As the most important image quality measurement features, noise and blur, determined the image quality greatly, are employed to predict the objective hyperspectral imagery quality of each band. We demonstrate a novel no-reference hyperspectral imagery QA model based on phase congruency (PC), which is a dimensionless quantity and provides an absolute measure of the significance of feature point. First, Log Gabor wavelet is used to calculate the phase congruency of frequencies of each band image. The relationship between noise and PC can be derived from above transformation under the assumption that noise is additive. Second, PC focus measure evaluation model is proposed to evaluate blur caused by different amounts of defocus. The ratio and mean factors of edge blur level and noise is defined to assess the quality of each band image. This image QA method obtains excellent correlation with subjective image quality score without any reference. Finally, the PC information is utilized to improve the quality of some bands images.

Shao, Xiaopeng; Zhong, Cheng

2012-10-01

109

Signal processing algorithms for staring single pixel hyperspectral sensors  

Microsoft Academic Search

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

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

2006-01-01

110

Distributed source coding of hyperspectral images  

Microsoft Academic Search

A first attempt to exploit distributed source coding (DSC) principles for the lossless compression of hyperspectral images is presented. The DSC paradigm is exploited to design a very light coder which minimizes the exploitation of the correlation between the image bands. In this way we managed to move the computational complexity from the encoder to the decoder, thus matching the

M. Barni; D. Papini; A. Abrardo; E. Magli

2005-01-01

111

Hyperspectral imaging and diagnosis of intestinal ischemia  

Microsoft Academic Search

Intestinal ischemia results from a variety of disorders that cause insufficient blood flow to the intestine. The type and prognosis of ischemic injury depends on the blood vessels involved, the underlying medical condition, and the swiftness with which the problem is brought to medical attention for diagnosis and treatment. Hyperspectral imaging has developed as a compact imaging and spectroscopic tool

Hamed Akbari; Yukio Kosugi; Kazuyuki Kojima; Naofumi Tanaka

2008-01-01

112

Massively parallel processing of remotely sensed hyperspectral images  

Microsoft Academic Search

In this paper, we develop several parallel techniques for hyperspectral image processing that have been specifically designed to be run on massively parallel systems. The techniques developed cover the three relevant areas of hyperspectral image processing: 1) spectral mixture analysis, a popular approach to characterize mixed pixels in hyperspectral data addressed in this work via efficient implementation of a morphological

Javier Plaza; Antonio Plaza; David Valencia; Abel Paz

2009-01-01

113

Landmine detection using passive hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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 - the visible/near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) - to detect surface-laid and buried mines. The phenomenology that determines performance in the different bands is discussed. Hyperspectral imagers have usually been designed and built for general purpose remote sensing applications and often do not meet the requirements of mine detection. The DRDC mine detection research program has sponsored the development by Itres Research of VNIR, SWIR and TIR instruments specifically intended for mine detection. The requirements for such imagers are described, as well as the instruments. Some results of mine detection experiments are presented. To date, reliable day time detection of surface-laid mines in non-real-time, independent of solar angle, time of day and season has been demonstrated in the VNIR and SWIR. Real-time analysis, necessary for military applications, has been demonstrated from low speed ground vehicles and recently from airborne platforms. Reliable, repeatable detection of buried mines has yet to be demonstrated, although a recently completed TIR hyperspectral imager will soon be tested for such a capability.

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

2007-05-01

114

Classification of hyperspectral images with support vector machines: multiclass strategies  

NASA Astrophysics Data System (ADS)

This paper addresses the problem of the classification of hyperspectral remote-sensing images by means of Support Vector Machines (SVMs). In a first step, we propose a theoretical and experimental analysis that aims at assessing the properties of SVM classifiers in hyperdimensional feature spaces which are compared with those of other nonparametric classifiers. In a second step, we face the multiclass problem involved by SVM classifiers when applied to hyperspectral data. In particular, four different multiclass strategies are analyzed and compared: the one-against-all, the one-against-one and two hierarchical tree-based strategies. The experimental analysis has been carried out by using hyperspectral images acquired by the AVIRIS sensor on the Indian Pine area. Different performance indicators have been used to support our experimental studies, i.e., the classification accuracy, the computational time, the stability to parameter setting, and the complexity of the multiclass architecture adopted. The obtained results confirm the effectiveness of SVMs in hyperspectral data classification with respect to conventional classifiers.

Bruzzone, Lorenzo; Melgani, Farid

2004-02-01

115

Surface emissivity and temperature retrieval for a hyperspectral sensor  

SciTech Connect

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

Borel, C.C.

1998-12-01

116

Flight evaluation of hyperspectral and multipolarizable imaging spectropolarimeter at JAXA  

NASA Astrophysics Data System (ADS)

The demand for airborne remote sensing based on the Earth environment observation has been growing, motivated by the need to protect the Earth's environment. Attention has been focused on hyperspectral sensors as new type of Earth observation sensor for measuring the surface conditions from the air. The Japan Aerospace Exploration Agency (JAXA) has developed an LCTF hyper-spectral imaging spectropolarimeter with selectable plane of polarization which senses radiation in the 400-720 nm visible light wavelength band, and has constructed an airborne optical observation system based on the sensor. Flight evaluation of this sensor using JAXA's Beechcraft 65 research airplane has been continuing over the past few years, and this paper first outlines this flight evaluation. Next, we report on current aerial observations of water contamination in the rivers or lakes and the growth stages of crops are shown, with spectral images taken at various wavelengths and polarization angles presented as the analyzed results of flight experiment data. The flight experiments have confirmed that spectral images of targets with differing characteristics do indeed show different spectropolarimetric properties. Plans for future flight evaluations are also described. Finally it is concluded that the way has been paved for applying the visible light sensor to airborne remote sensing, aiming at the determination of surface conditions.

Homma, Kohzo; Shingu, Hirokimi; Yamamoto, Hiromichi; Shibayama, Michio; Sugahara, Kazuo

2005-01-01

117

Compressive Hyperspectral Imaging and Anomaly Detection.  

National Technical Information Service (NTIS)

We have developed and tested state-of-the-art target detection/template matching methods based on LI minimization. Given the spectral signature of a material, we are able to identify the pixels in a hyperspectral image, even for very noisy data, that cont...

K. Kelly P. Thiyanaratnam S. Chen S. Osher W. Yin

2010-01-01

118

Semi-supervised hyperspectral image segmentation  

Microsoft Academic Search

This paper presents a new semi-supervised segmentation algorithm, suited to high dimensional data, of which hyperspectral images are an example. The algorithm implements two main steps: (a) semi-supervised learning, used to infer the class distributions, followed by (b) segmentation, by inferring the labels from a posterior density built on the learned class distributions and on a Markov random field. The

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

2009-01-01

119

Hyperspectral image compression through spectral clustering  

Microsoft Academic Search

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.

K. Siala; A. Benazza-Benyahia

2004-01-01

120

Prior important band hyperspectral image compression  

Microsoft Academic Search

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

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

2003-01-01

121

New AOTF Technology for IR Hyperspectral Imaging.  

National Technical Information Service (NTIS)

We have developed a new Acousto-Optic Tunable Filter (AOTF) for implementation as a spectrally selective element for hyperspectral imaging applications in the NIR (.8 - 1.7 micron) and MWIR (2.5 - 4.5 micron) ranges of the optical spectrum. The new AOTF h...

V. Pelekhaty X. Wang D. E. Paulsen

1998-01-01

122

Accurate reconstruction of hyperspectral images from compressive sensing measurements  

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

123

Distributed lossless coding of hyperspectral images  

Microsoft Academic Search

In this paper we propose a novel distributed lossless compression scheme for hyperspectral images. All the images\\/bands are encoded independently, and the spectral correlation is exploited using distributed coding technologies in order to achieve low encoding complexity. At the encoder, sub-sampled images are successively encoded and transmitted. At the decoder, side information is generated with the knowledge of decoded sub-sampled

Wei Zhang; Qiwei Liu; Houqiang Li

2010-01-01

124

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

PubMed

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

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

2013-02-01

125

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

NASA Astrophysics Data System (ADS)

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 mitigate volcanic disasters. ARTS is a pushbroom imaging spectrometer covering wavelengths from 380 to 2450nm and 8000 to 11500nm with 421 bands. The ARTS imaging spectrometer consists of three sensor head units (SHUs). These SHUs are the visible - near infrared (VNIR) SHU, the shortwave infrared (SWIR) SHU, and the long-wave infrared (LWIR) SHU. These sensor head units operate as a line scanner in the pushbroom mode from an aircraft. The VNIR SHU covers wavelengths from 380 to 1050nm with 288 spectrum bands. The field of view (FOV) is 40 degrees, and the image of this SHU is 1500 pixels wide cross-track, making the instantaneous field of view (IFOV) 0.49mrad. The SWIR SHU covers wavelengths from 900 to 2450nm with 101 spectrum bands. The LWIR SHU covers wavelengths from 8000 to 11500nm with 32 spectrum bands. SWIR SHU and LWIR SHU have FOVs of 40 degrees and 600-pixel-wide images cross-track, giving them an IFOV of 1.2mrad. ARTS has precise position and attitude measurement systems (GPS/IMU). Direct, accurate geo-corrections of each SHU image can be made using the GPS/IMU systems. ARTS will be used for the operational volcano observation beginning in 2008. We are now validating the in-flight performance of this sensor. In this study, we describe the ARTS optical, electrical, and mechanical systems; its data acquisition and system design; and present some preliminary in- flight performance test results obtained from measurements acquired aboard the Beechcraft King Air B200 aircraft. The validation results indicate that the geo-correction accuracy is typically less than a 2-pixel difference (RMS) for each SHU, and there was the good agreement between the predicted radiance at the sensor and the measured radiance at the sensor at a flight altitude of 1000m AGL. We expect that ARTS will be a well-calibrated instrument for assessing volcanic activity.

Jitsufuchi, T.

2007-12-01

126

Hyperspectral Imaging of fecal contamination on chickens  

NASA Technical Reports Server (NTRS)

ProVision Technologies, a NASA research partnership center at Sternis Space Center in Mississippi, has developed a new hyperspectral imaging (HSI) system that is much smaller than the original large units used aboard remote sensing aircraft and satellites. The new apparatus is about the size of a breadbox. Health-related applications of HSI include 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.

2003-01-01

127

Resolution study of a Hyperspectral Sensor using Computed Tomography in the presence of Noise  

NASA Astrophysics Data System (ADS)

A new type of hyperspectral imaging sensor is proposed, simulated and tested, which records both spectral and 2-dimensional spatial information. Dispersive imaging spectrometers typically measure multiple wavelengths and a single spatial dimension. Unlike dispersive imaging spectrometers, chromo-tomographic hyperspectral imaging sensors (CTHIS) record two spatial dimensions, as well as a spectral dimension, using computed tomography (CT) techniques with only a finite number of diverse images. CTHIS require a reconstruction algorithm in order to yield a usable hyperspectral data cube, and assume that the point spread function (PSF) is known. To date, the factors affecting resolution of these sensors have not been examined. Lens-based CTHIS sensors use chromatic aberration of a lens and multiple images in varying levels of defocus to determine the chromatic scene of an object. This type of CTHIS sensor has many practical advantages including simplicity of its design and dual use as a broad band imager with no additional processing. The lens-based CTHIS concept has been largely unexplored up to this time. The results of this research effort serve to examine factors affecting the spectral and spatial resolution of a lens-based CTHIS sensor, specifically showing how many frames are needed to reconstruct the spectral cube of a simple object using a theoretical lower bound. In this research a new algorithm is derived and is used to successfully reconstruct a hyperspectral object in the presence of noise and background. This new algorithm is used to verify the number of frames predicted from the theoretical bound calculation using laboratory data, thereby demonstrating the validity of the bound calculation. Finally, a simple method is proposed and tested to use this sensor in the presence of atmospheric turbulence. This method is shown in simulation to successfully remove the effects of atmospheric turbulence and estimate the atmospheric seeing conditions blindly from raw lens-based CTHIS data.

Mantravadi, Samuel V.

128

Airborne Hyperspectral Imaging of Seagrass and Coral Reef  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

129

Metric Learning to Enhance Hyperspectral Image Segmentation  

NASA Technical Reports Server (NTRS)

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

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

2013-01-01

130

Mapping Soil Organic Matter with Hyperspectral Imaging  

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

131

Multivariate hyperspectral Raman imaging using compressive detection.  

PubMed

A multivariate hyperspectral imaging (MHI) instrument has been designed and constructed to achieve greatly increased Raman imaging speeds by utilizing a compressive spectral detection strategy. The instrument may be viewed as a generalized spectrometer, which can function either as a conventional monochromator or in a wide variety of other hyperspectral modalities. The MHI utilizes a spatial light modulator (SLM) to produce programmable optical filters to rapidly detect and map particular sample components. A sequence of Hadamard-transform or random filter functions may be used to regenerate full Raman spectra. Compressive detection is achieved either using multivariate signal processing filter functions or the actual component spectra. Compressive detection is shown to be capable of achieving sampling speeds exceeding 1 ms per image pixel and the collection of chemical images in less than a minute. PMID:21604741

Davis, Brandon M; Hemphill, Amanda J; Malta?, Derya Cebeci; Zipper, Michael A; Wang, Ping; Ben-Amotz, Dor

2011-07-01

132

Hyperspectral image data compression based on DSP  

NASA Astrophysics Data System (ADS)

The huge data volume of hyperspectral image challenges its transportation and store. It is necessary to find an effective method to compress the hyperspectral image. Through analysis and comparison of current various algorithms, a mixed compression algorithm based on prediction, integer wavelet transform and embedded zero-tree wavelet (EZW) is proposed in this paper. We adopt a high-powered Digital Signal Processor (DSP) of TMS320DM642 to realize the proposed algorithm. Through modifying the mixed algorithm and optimizing its algorithmic language, the processing efficiency of the program was significantly improved, compared the non-optimized one. Our experiment show that the mixed algorithm based on DSP runs much faster than the algorithm on personal computer. The proposed method can achieve the nearly real-time compression with excellent image quality and compression performance.

Fan, Jiming; Zhou, Jiankang; Chen, Xinhua; Shen, Weimin

2010-11-01

133

A collection of hyperspectral images for imaging systems research  

NASA Astrophysics Data System (ADS)

A set of hyperspectral image data are made available, intended for use in modeling of imaging systems. The set contains images of faces, landscapes and buildings. The data cover wavelengths from 0.4 to 2.5 micrometers, spanning the visible, NIR and SWIR electromagnetic spectral ranges. The images have been recorded with two HySpex line-scan imaging spectrometers covering the spectral ranges 0.4 to 1 micrometers and 1 to 2.5 micrometers. The hyperspectral data set includes measured illuminants and software for converting the radiance data to estimated reflectance. The images are being made available for download at http://scien.stanford.edu

Skauli, Torbjørn; Farrell, Joyce

2013-01-01

134

Infrared hyperspectral imaging for chemical vapour detection  

NASA Astrophysics Data System (ADS)

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.

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

2012-10-01

135

Hyperspectral image compression using bands combination wavelet transformation  

Microsoft Academic Search

Hyperspectral imaging technology is the foreland of the remote sensing development in the 21st century and is one of the most important focuses of the remote sensing domain. Hyperspectral images can provide much more information than multispectral images do and can solve many problems which can't be solved by multispectral imaging technology. However this advantage is at the cost of

Wenjie Wang; Zhongming Zhao; Haiqing Zhu

2009-01-01

136

Hyperspectral imaging of blood perfusion and chromophore distribution in skin  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging is a modality which combines spatial resolution and spectroscopy in one technique. Analysis of hyperspectral data from biological samples is a demanding task due to the large amount of data, and due to the complex optical properties of biological tissue. In this study it was investigated if depth information could be revealed from hyperspectral images using a combination of image analysis and analytic simulations of skin reflectance. It was also investigated if hyperspectral imaging could be utilized to monitor changes in the distribution of hemoglobin species after smoking. Hyperspectral data in the wavelength range 400-1000nm were collected from the forearm of 15 non-smokers and 5 smokers. The hyperspectral images were analyzed with respect to the distribution of hemoglobin species and vascular structures. Changes in the vascular system due to smoking were also evaluated. Principal component analysis (PCA), Spectral angle mapping (SAM), and Mixture tuned matched filtering (MTMF) were used to enhance vascular structures. Emphasis was put on identifying apparent and true absorption spectra for the present chromophores by combining image analysis and an analytical photon transport model. The results show that the depth resolution of hyperspectral images can be better understood using analytical simulations. Modulation of the chromophore spectra by the optical properties of overlying tissue was found to be an important mechanism causing the depth resolution in hyperspectral images. It was also found that hyperspectral imaging and image analysis can be successfully applied to quantify skin changes following smoking.

Randeberg, Lise L.; Larsen, Eivind L. P.; Svaasand, Lars O.

2009-02-01

137

Assessment of hyperspectral MIVIS sensor capability for heterogeneous landscape classification  

NASA Astrophysics Data System (ADS)

The potential and limitations of the hyperspectral remote sensing MIVIS sensor (Multispectral Infrared Visible Imaging Spectrometer) in classifying heterogeneous landscapes are explored in this study. In order to quantify the discriminant information derived from selected MIVIS subsets we classified a monitored scenario by progressively increasing the feature space dimensionality. The hyperspectral subsets are defined through the Sequential Forward Selection algorithm, while mapping processes have been performed through the Maximum Likelihood, Spectral Angle Mapper and Spectral Information Divergence classifiers. Impacts of spectral bands on the overall classification accuracies and single land cover-scale reliability, as well as possible dimensionality effects (Hughes phenomenon) are investigated. The analysis is tested on a 20-km stretch of the Marecchia River (Emilia Romagna, Italy) by using MIVIS data acquired in autumn 2009 and 2010 for a 17-class mapping including complex urban/rural areas. For the considered dataset, the MIVIS sensor showed an equipment failure: of the nominal 102-band MIVIS dataset, only the first 24 bands, spanning within the 0.441-1.319 ?m spectral range, were exploitable. Nevertheless, the available information provided valuable discriminant contributions in land cover mapping (Maximum Likelihood Overall Accuracy ˜85%) with encouraging reliability on mixed forests, croplands, and no-vegetated floodplain patterns, whereas riparian vegetation and urban zones exhibited low classification accuracies. The relationship between the spectral space dimensionality and the minimum training-set size that is necessary to achieve a given inter-class separability has also been experimentally investigated by progressively under-sampling the original training set. The maximum under-sampling factor that avoided a decrease in the overall accuracy turned out to be, at maximum, 15 for the considered data set.

Forzieri, Giovanni; Moser, Gabriele; Catani, Filippo

2012-11-01

138

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

NASA Astrophysics Data System (ADS)

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

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

2014-03-01

139

Multiple instance learning for hyperspectral image analysis  

Microsoft Academic Search

Multiple instance learning is a recently researched learning paradigm that allows a machine learning algorithm to learn target concepts with uncertainty in the class labels of training data. In the following, this approach is assessed for use in hyperspectral image analysis. Two leading MIL algorithms are used in a classification experiment and results are compared to a state-of-the-art context-based classifier.

Jeremy Bolton; Paul D. Gader

2010-01-01

140

Hyperspectral image coding using 3D transforms  

Microsoft Academic Search

This work considers the efficient coding of hyperspectral images. The shape-adaptive DCT is extended to the three-dimensional case. Both the 3D-SA-DCT and the conventional 3D-DCT are combined with either of two alternative techniques for coding the transform coefficients. The proposed schemes are compared with two state of the art coding algorithms, which serve as benchmarks, and are found to have

Dmitry Markman; David Malah

2001-01-01

141

Advances in hyperspectral LWIR pushbroom imagers  

NASA Astrophysics Data System (ADS)

Two long-wave infrared (LWIR) hyperspectral imagers have been under extensive development. The first one utilizes a microbolometer focal plane array (FPA) and the second one is based on an Mercury Cadmium Telluride (MCT) FPA. Both imagers employ a pushbroom imaging spectrograph with a transmission grating and on-axis optics. The main target has been to develop high performance instruments with good image quality and compact size for various industrial and remote sensing application requirements. A big challenge in realizing these goals without considerable cooling of the whole instrument is to control the instrument radiation. The challenge is much bigger in a hyperspectral instrument than in a broadband camera, because the optical signal from the target is spread spectrally, but the instrument radiation is not dispersed. Without any suppression, the instrument radiation can overwhelm the radiation from the target even by 1000 times. The means to handle the instrument radiation in the MCT imager include precise instrument temperature stabilization (but not cooling), efficient optical background suppression and the use of background-monitoring-on-chip (BMC) method. This approach has made possible the implementation of a high performance, extremely compact spectral imager in the 7.7 to 12.4 ?m spectral range. The imager performance with 84 spectral bands and 384 spatial pixels has been experimentally verified and an excellent NESR of 14 mW/(m2sr?m) at 10 ?m wavelength with a 300 K target has been achieved. This results in SNR of more than 700. The LWIR imager based on a microbolometer detector array, first time introduced in 2009, has been upgraded. The sensitivity of the imager has improved drastically by a factor of 3 and SNR by about 15 %. It provides a rugged hyperspectral camera for chemical imaging applications in reflection mode in laboratory and industry.

Holma, Hannu; Mattila, Antti-Jussi; Hyvärinen, Timo; Weatherbee, Oliver

2011-05-01

142

Hyperspectral projection of a coral reef scene using the NIST hyperspectral image projector  

Microsoft Academic Search

Improving the understanding of the optical scene components associated with coral reef imagery will advance the ability to map and monitor coral reefs using remote sensing. One tool that can aid in understanding the components in these scenes is the NIST Hyperspectral Image Projector (HIP). In this paper a hyperspectral scene is reformatted for projection using the HIP by first

David W. Allen; Joseph P. Rice; James A. Goodman

2009-01-01

143

Fusion of hyperspectral images based on feature images extraction and contourlet analysis  

Microsoft Academic Search

Because of the high data dimensionality of hyperspectral data, it is somehow difficult to directly apply hyperspectral images in classification and target detection. A fusion method of hyperspectral images based on feature images extraction and contourlet analysis is proposed. The algorithm firstly extracts feature images using subspace partition and principal components analysis (PCA), then these feature images are fused using

Chang Weiwei; Guo Lei; Liu Kun; Fu Zhaoyang

2009-01-01

144

Compression of hyperspectral images with pre-emphasis  

Microsoft Academic Search

In this paper, we propose compression algorithms for hyperspectral images with pre-emphasizing discriminantly dominant features. When hyperspectral images are compressed using a conventional image compression algorithm, which has been developed to minimize mean squared errors, discriminant features of the original data may be lost during compression process since such discriminant features may not be large in energies. In order to

Chulhee Lee; Euisun Choi

2004-01-01

145

GPU implementation of JPEG2000 for hyperspectral image compression  

Microsoft Academic Search

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

Milosz Ciznicki; Krzysztof Kurowski; Antonio Plaza

2011-01-01

146

Compression of hyperspectral images with discriminant features enhanced  

Microsoft Academic Search

In this paper, we propose two compression methods for hyperspectral images with discriminant features enhanced. Generally, when hyperspectral images are compressed with conventional image compression algorithms, which mainly minimize mean squared errors, discriminant features of the original data may not be well preserved since they may not be necessarily large in energy. In this paper, we propose two compression methods

Chulhee Lee; Euisun Choi; Taeuk Jeong; Sangwook Lee; Jonghwa Lee

2010-01-01

147

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

Microsoft Academic Search

Advances in Hyperspectral imaging (HSI) sensor offer new avenues for precise detection, identification and characterization of materials or targets of military interest. HSI technologies are capable of exploiting 10s to 100s of images of a scene collected at contiguous or selective spectral bands to seek out mission-critical objects. In this paper, we develop and analyze several HSI algorithms for detection,

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

2007-01-01

148

Unsupervised data fusion for hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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 makes unsupervised classification a challenge that requires new techniques. Thus, alternative methods are needed to take advantage of the information provided by the hyperdimensional data. Data fusion is an alternative when dealing with such large data sets in order to improve classification accuracy. Data fusion is an important process in the areas of environmental systems, surveillance, automation, medical imaging, and robotics. The uses of this technique in Remote Sensing have been recently expanding. A relevant application is to adapt the data fusion approaches to be used on hyperspectral imagery taking into consideration the special characteristics of such data. The approach of this paper is to presents a scheme that integrates information from most of the hyperspectral narrow-bands in order to increase the discrimination accuracy in unsupervised classification.

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

2002-01-01

149

Hyperspectral imaging in earth road construction planning  

NASA Astrophysics Data System (ADS)

Some types of clay, esp. montmorillonite, become slippery when getting wet. Clay movement is very harmful for various constructions and can also cause trouble for both wheeled and tracked vehicles in military operations at some rural areas when raining. We present a summary of a project using hyperspectral imaging in assisting earth roads construction planning and cross-country trafficability analysis. Spectral signature libraries are used to help identify materials and define those areas to be avoided, which have significant montmorillonite content. We perform a case study in this kind of application; some methods of data processing and analyzing are discussed. We also discussed the problems we met in this application. Hyperspectral sensing is a relatively new but mature technology; development of applications and corresponding analyzing procedures will be the major impetus of this technology.

Nie, Yixiang; Gomez, Richard B.; Kafatos, Menas; Yang, Ruixin

2001-06-01

150

Hyper-Cam automated calibration method for continuous hyperspectral imaging measurements  

NASA Astrophysics Data System (ADS)

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.

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

2010-04-01

151

Instrumental error in chromotomosynthetic hyperspectral imaging.  

PubMed

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

Bostick, Randall L; Perram, Glen P

2012-07-20

152

ACTIVE-EYES: an adaptive pixel-by-pixel image-segmentation sensor architecture for high-dynamic-range hyperspectral imaging  

NASA Astrophysics Data System (ADS)

The ACTIVE-EYES (adaptive control for thermal imagers via electro-optic elements to yield an enhanced sensor) architecture, an adaptive image-segmentation and processing architecture, based on digital micromirror (DMD) array technology, is described. The concept provides efficient front-end processing of multispectral image data by adaptively segmenting and routing portions of the scene data concurrently to an imager and a spectrometer. The goal is to provide a large reduction in the amount of data required to be sensed in a multispectral imager by means of preprocessing the data to extract the most useful spatial and spectral information during detection. The DMD array provides the flexibility to perform a wide range of spatial and spectral analyses on the scene data. The spatial and spectral processing for different portions of the input scene can be tailored in real time to achieve a variety of preprocessing functions. Since the detected intensity of individual pixels may be controlled, the spatial image can be analyzed with gain varied on a pixel-by-pixel basis to enhance dynamic range. Coarse or fine spectral resolution can be achieved in the spectrometer by use of dynamically controllable or addressable dispersion elements. An experimental prototype, which demonstrated the segmentation between an imager and a grating spectrometer, was demonstrated and shown to achieve programmable pixelated intensity control. An information theoretic analysis of the dynamic-range control aspect was conducted to predict the performance enhancements that might be achieved with this architecture. The results indicate that, with a properly configured algorithm, the concept achieves the greatest relative information recovery from a detected image when the scene is made up of a relatively large area of moderate-dynamic-range pixels and a relatively smaller area of strong pixels that would tend to saturate a conventional sensor.

Christensen, Marc P.; Euliss, Gary W.; McFadden, Michael J.; Coyle, Kevin M.; Milojkovic, Predrag; Haney, Michael W.; van der Gracht, Joeseph; Athale, Ravindra A.

2002-10-01

153

A low cost thermal infrared hyperspectral imager for small satellites  

NASA Astrophysics Data System (ADS)

The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small satellite market and launch opportunities for these satellites. These low-cost, short-lived missions provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off the shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCOR), to demonstrate the ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable the use of COTS electronics, and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230-meter pixels with 20 wavenumber spectral resolution from a 400-km orbit.

Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.

2011-05-01

154

A low cost thermal infrared hyperspectral imager for small satellites  

NASA Astrophysics Data System (ADS)

The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.; Wood, M.

2012-05-01

155

Design of FPGA ICA for hyperspectral imaging processing  

Microsoft Academic Search

The remote sensing problem which uses hyperspectral imaging can be transformed into a blind source separation problem. Using this model, hyperspectral imagery can be de-mixed into sub-pixel spectra which indicate the different material present in the pixel. This can be further used to deduce areas which contain forest, water or biomass, without even knowing the sources which constitute the image.

Anis Nordin; Charles C. Hsu; Harold H. Szu

2001-01-01

156

Spatially Coherent Nonlinear Dimensionality Reduction and Segmentation of Hyperspectral Images  

Microsoft Academic Search

The nonlinear dimensionality reduction and its effects on vector classification and segmentation of hyperspectral images are investigated in this letter. In particular, the way dimensionality reduction influences and helps classification and segmentation is studied. The proposed framework takes into account the nonlinear nature of high-dimensional hyperspectral images and projects onto a lower dimensional space via a novel spatially coherent locally

Anish Mohan; Guillermo Sapiro; Edward Bosch

2007-01-01

157

Integration of Hyperspectral Image Classification and Unmixing for Active Learning  

Microsoft Academic Search

Spectral unmixing is a growing area in remotely sensed hyperspectral image analysis. Many algorithms have been developed to retrieve pure spectral components and determine their sub-pixel abundance fractions in this kind of data. However, possible connections between spectral unmixing concepts and classification algorithms have been rarely investigated. In this work, we propose a new method to perform semi-supervised hyperspectral image

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

2011-01-01

158

Multiscale windowed denoising and segmentation of hyperspectral images  

Microsoft Academic Search

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

Gökhan Bilgin; Sarp Ertürk; T. Yildirim

2008-01-01

159

Interactive Visualization of Hyperspectral Images of Historical Documents  

Microsoft Academic Search

This paper presents an interactive visualization tool to study and analyze hyperspectral images (HSI) of historical documents. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for old and fragile documents. The NAN is actively capturing HSI of historical documents for use in

Seon Joo Kim; Shaojie Zhuo; Fanbo Deng; Chi-Wing Fu; Michael S. Brown

2010-01-01

160

Swarm Intelligence Approach to Wavelet Design for Hyperspectral Image Classification  

Microsoft Academic Search

Wavelets are known to be a valuable tool for analyzing hyperspectral images. In this letter, we propose to further improve their performance by means of a novel classification-driven design scheme that aims at deriving a wavelet that best represents in terms of between-class discrimination capability the spectral signatures conveyed by a given hyperspectral image. This is achieved by adopting a

Abdelhamid Daamouche; Farid Melgani

2009-01-01

161

Downscaling of satellite hyperspectral images for monitoring croplands  

Microsoft Academic Search

Remote sensing has potential to provide a cost-efficient and fast tool to map soil properties across large areas. Especially, hyperspectral image can potentially discriminate between crop residues and soils as well as vegetation. Satellite hyperspectral image has very narrow spectral bands but a coarse spatial resolution to detect soil properties and vegetation in small parcels of croplands. This study focused

Eunyoung Choe; SukYoung Hong; YiHyun Kim

2010-01-01

162

Hyperspectral image lossless compression algorithm based on adaptive band regrouping  

Microsoft Academic Search

Hyperspectral image has weak spatial correlation and strong spectral correlation. As to exploit spectrum redundancy sufficiently, it must be pre-processed. In this paper, a new algorithm for lossless compression of hyperspectral images based on adaptive band regrouping is proposed. Firstly, the affinity propagation clustering algorithm (AP) is chosen for band regrouping according to interband correlation. Then a linear prediction algorithm

Mingyi He; Lin Bai; Yuchao Dai; Jing Zhang

2009-01-01

163

Hyperspectral image classification using Support Vector Machine  

NASA Astrophysics Data System (ADS)

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

Moughal, T. A.

2013-06-01

164

Ore minerals textural characterization by hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

Bonifazi, Giuseppe; Picone, Nicoletta; Serranti, Silvia

2013-02-01

165

Extending the fractional order Darwinian particle swarm optimization to segmentation of hyperspectral images  

NASA Astrophysics Data System (ADS)

Hyperspectral sensors generate detailed information about the earth's surface and climate in numerous contiguous narrow spectral bands, being widely used in resource management, agriculture, environmental monitoring, and others. However, due to the high dimensionality of hyperspectral data, it is difficult to design accurate and efficient image segmentation algorithms for hyperspectral imagery. In this paper a new multilevel thresholding method for segmentation of hyperspectral images into different homogenous regions is proposed. The new method is based on the Fractional-Order Darwinian Particle Swarm Optimization (FODPSO) which exploits the many swarms of test solutions that may exist at any time. In addition, the concept of fractional derivative is used to control the convergence rate of particles. The FODPSO is used to solve the so-called Otsu problem for each channel of the hyperspectral data as a grayscale image that indicates the spectral response to a particular frequency in the electromagnetic spectrum. In other words, the problem of n-level thresholding is reduced to an optimization problem in order to search for the thresholds that maximize the between-class variance. Experimental results successfully compare the FODPSO with the traditional PSO for multi-level segmentation of hyperspectral images. The FODPSO acts better than the other method in terms of both CPU time and fitness, thus being able to find the optimal set of thresholds with a larger between-class variance in less computational time.

Ghamisi, Pedram; Couceiro, Micael S.; Benediktsson, Jon Atli

2012-11-01

166

Potential roles of satellite hyperspectral IR sensors in monitoring greenhouse effects  

Microsoft Academic Search

As we enter a new era of using satellite hyperspectral sensors for weather and other environmental applications, this paper discusses the applicability of using IR hyperspectral data for climate change monitoring; in particular, for quantifying the greenhouse effects. While broadband 1st order statistics quantify radiative forcings, the IR hyperspectral data provides a means of monitoring feedback processes. Radiative transfer modeling

Hsiao-hua Burke; Bill Snow; Kris Farrar

2005-01-01

167

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

Microsoft Academic Search

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

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

2006-01-01

168

Detection and Analysis of the Intestinal Ischemia Using Visible and Invisible Hyperspectral Imaging  

Microsoft Academic Search

Intestinal ischemia, or inadequate blood flow to the intestine, is caused by a variety of disorders and conditions. The quickness with which the problem is brought to medical attention for diagnosis and treatment has great effects on the outcome of ischemic injury. Recently, hyperspectral sensors have advanced and emerged as compact imaging tools that can be utilized in medical diagnostics.

Hamed Akbari; Yukio Kosugi; Kazuyuki Kojima; Naofumi Tanaka

2010-01-01

169

Calibration of a fluorescence hyperspectral imaging system for agricultural inspection and detection  

NASA Astrophysics Data System (ADS)

Fluorescence hyperspectral imaging is increasingly being used for food quality inspection and detection of potential food safety concerns. The flexible nature of a self-scanning pushbroom hyperspectral imager lends itself to these kinds of applications, among others. To increase the use of this technique there has been a tendency to use low cost off-the-shelf hyperspectral sensors which are typically not radiometrically calibrated. To ensure that these systems are optimized for response and repeatability, it is imperative that the systems be both radiometrically and spectrally calibrated specifically for fluorescence imaging. Fluorescence imaging provides several challenges such as low signal, stray light and a low signal dynamic range that are improved with careful radiometric calibration. A radiometric and spectral approach that includes flat fielding and the conversion of digital number responses to radiance for calibrating this imaging system and other types of hyperspectral imagers is described in this paper. Results show that this method can be adopted for calibrating fluorescence and reflective hyperspectral imaging systems in the visible and near infra-red domains.

Ononye, Ambrose E.; Yao, Haibo; Hruska, Zuzana; Kincaid, Russell

2010-04-01

170

Reconstruction of Chromotomographic Imaging System Infrared Hyperspectral Scenes.  

National Technical Information Service (NTIS)

Hyperspectral imagery providing both spatial and spectral information has diverse applications in remote sensing and scientific imaging scenarios. The development of the Chromotomographic Imaging System (CTIS) allows simultaneous collection of both spatia...

M. G. Gould

2005-01-01

171

Construction of a small and lightweight hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

The analysis of the reflected sunlight offers great opportunity to gain information about the environment, including vegetation and soil. In the case of plants the wavelength ratio of the reflected light usually undergoes a change if the state of growth or state of health changes. So the measurement of the reflected light allows drawing conclusions about the state of, amongst others, vegetation. Using a hyperspectral imaging system for data acquisition leads to a large dataset, which can be evaluated with respect to several different questions to obtain various information by one measurement. Based on commercially available plain optical components we developed a small and lightweight hyperspectral imaging system within the INTERREG IV A-Project SMART INSPECTORS. The project SMART INSPECTORS [Smart Aerial Test Rigs with Infrared Spectrometers and Radar] deals with the fusion of airborne visible and infrared imaging remote sensing instruments and wireless sensor networks for precision agriculture and environmental research. A high performance camera was required in terms of good signal, good wavelength resolution and good spatial resolution, while severe constraints of size, proportions and mass had to be met due to the intended use on small unmanned aerial vehicles. The detector was chosen to operate without additional cooling. The refractive and focusing optical components were identified by supporting works with an optical raytracing software and a self-developed program. We present details of design and construction of our camera system, test results to confirm the optical simulation predictions as well as our first measurements.

Vogel, Britta; Hünniger, Dirk; Bastian, Georg

2014-05-01

172

Dimensionality reduction of hyperspectral images using kernel ICA  

NASA Astrophysics Data System (ADS)

Computational burden due to high dimensionality of Hyperspectral images is an obstacle in efficient analysis and processing of Hyperspectral images. In this paper, we use Kernel Independent Component Analysis (KICA) for dimensionality reduction of Hyperspectraql images based on band selection. Commonly used ICA and PCA based dimensionality reduction methods do not consider non linear transformations and assumes that data has non-gaussian distribution. When the relation of source signals (pure materials) and observed Hyperspectral images is nonlinear then these methods drop a lot of information during dimensionality reduction process. Recent research shows that kernel-based methods are effective in nonlinear transformations. KICA is robust technique of blind source separation and can even work on near-gaussina data. We use Kernel Independent Component Analysis (KICA) for the selection of minimum number of bands that contain maximum information for detection in Hyperspectral images. The reduction of bands is basd on the evaluation of weight matrix generated by KICA. From the selected lower number of bands, we generate a new spectral image with reduced dimension and use it for hyperspectral image analysis. We use this technique as preprocessing step in detection and classification of poultry skin tumors. The hyperspectral iamge samples of chicken tumors used contain 65 spectral bands of fluorescence in the visible region of the spectrum. Experimental results show that KICA based band selection has high accuracy than that of fastICA based band selection for dimensionality reduction and analysis for Hyperspectral images.

Khan, Asif; Kim, Intaek; Kong, Seong G.

2009-05-01

173

Benefits of textural characterization for the classification of hyperspectral images  

Microsoft Academic Search

Several spatial features are compared for the spatial\\/spectral classification of hyperspectral data. These features are extracted from texture spectra, co-occurrence matrices and morphological profiles. First, a PCA (Principal Components Analysis) is carried out on the hyperspectral image and textural features are computed on the first principal components. These textural features are concatenated together with spectral features (the principal components previously

Guillaume Roussel; V. Achard; A. Alakian; J.-C. Fort

2010-01-01

174

Active Volcano Monitoring using a Space-based Hyperspectral Imager  

Microsoft Academic Search

Active volcanoes occur on every continent, often in close proximity to heavily populated areas. While ground-based studies are essential for scientific research and disaster mitigation, remote sensing from space can provide rapid and continuous monitoring of active and potentially active volcanoes [Ramsey and Flynn, 2004]. In this paper, we report on hyperspectral measurements of Kilauea volcano, Hawaii. Hyperspectral images obtained

J. J. Cipar; R. Dunn; T. Cooley

2010-01-01

175

Compression of Hyperspectral Images with LVQ-SPECK  

Microsoft Academic Search

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

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

2008-01-01

176

Level Set Hyperspectral Image Classification Using Best Band Analysis  

Microsoft Academic Search

We present a supervised hyperspectral classification procedure consisting of an initial distance-based segmentation method that uses best band analysis (BBA), followed by a level set enhancement that forces localized region homogeneity. The proposed method is tested on two hyperspectral images of an urban and rural nature. The proposed method is compared to the maximum likelihood (ML) method using BBA. Quantitative

John E. Ball; Lori Mann Bruce

2007-01-01

177

Recent results of integrated sensing and processing with hyperspectral imager  

NASA Astrophysics Data System (ADS)

In this paper we present an information sensing system which integrates sensing and processing resulting in the direct collection of data which is relevant to the exploitation application. Broadly, integrated sensing and processing (ISP) considers algorithms that are integrated with the collection of data. We demonstrate an ISP system which utilizes a near Infrared (NIR) Hadamard multiplexing imaging sensor. This prototype sensor incorporates a digital mirror array (DMA) device in order to realize a Hadamard multiplexed imaging system. Specific Hadamard codes can be sent to the sensor to realize inner products of the underlying scene rather than the scene itself. The developed ISP algorithm incorporates the exploitation tasks into the sensing by computing an ATR metric which directs the sensor to collect only the information relevant to the ATR problem. The result is a multiple resolution hyperspectral cube with full resolution where targets are present and less than full resolution where there are no targets. We demonstrate this algorithm fully integrated with the sensor and running in real time on a test case to demonstrate feasibility.

Muise, Robert; Mahalanobis, Abhijit

2007-04-01

178

Hyperspectral image compression using three-dimensional wavelet coding  

Microsoft Academic Search

A Hyperspectral image is a sequence of images generated by collecting contiguously spaced spectral bands of data. One can view such an image sequence as a three-dimensional array of intensity values (pixels) within a rectangular prism. We present a Three-Dimensional Set Partitioned Embedded bloCK (3DSPECK) algorithm based on the observation that hyperspectral images are contiguous in the spectrum axis (this

Xiaoli Tang; William A. Pearlman; James W. Modestino

2003-01-01

179

Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms  

NASA Astrophysics Data System (ADS)

The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

Plaza, Antonio; Chang, Chein-I.; Plaza, Javier; Valencia, David

2006-06-01

180

Multi-FOV hyperspectral imager concept  

NASA Astrophysics Data System (ADS)

There is increasing interest in imaging spectrometers working in the SWIR and LWIR wavelength bands. Commercially available detectors are not only expensive, but have a limited number of pixels, compared with visible band detectors. Typical push broom hyperspectral imaging systems consist of a fore optic imager, a slit, a line spectrometer, and a two dimensional focal plane with a spatial and spectral direction. To improve the spatial field coverage at a particular resolution, multiple systems are incorporated, where the "linear fields of view" of the systems are aligned end to end. This solution is prohibitive for many applications due to the costs of the multiple detectors, coolers, spectrometers, or the space, weight, or power constraints. Corning will present a cost effective solution utilizing existing detectors combined with innovative design and manufacturing techniques.

Comstock, Lovell E.; Wiggins, Richard L.

2011-05-01

181

Active Volcano Monitoring using a Space-based Hyperspectral Imager  

NASA Astrophysics Data System (ADS)

Active volcanoes occur on every continent, often in close proximity to heavily populated areas. While ground-based studies are essential for scientific research and disaster mitigation, remote sensing from space can provide rapid and continuous monitoring of active and potentially active volcanoes [Ramsey and Flynn, 2004]. In this paper, we report on hyperspectral measurements of Kilauea volcano, Hawaii. Hyperspectral images obtained by the US Air Force TacSat-3/ARTEMIS sensor [Lockwood et al, 2006] are used to obtain estimates of the surface temperatures for the volcano. ARTEMIS measures surface-reflected light in the visible, near-infrared, and short-wave infrared bands (VNIR-SWIR). The SWIR bands are known to be sensitive to thermal radiation [Green, 1996]. For example, images from the NASA Hyperion hyperspectral sensor have shown the extent of wildfires and active volcanoes [Young, 2009]. We employ the methodology described by Dennison et al, (2006) to obtain an estimate of the temperature of the active region of Kilauea. Both day and night-time images were used in the analysis. To improve the estimate, we aggregated neighboring pixels. The active rim of the lava lake is clearly discernable in the temperature image, with a measured temperature exceeding 1100o C. The temperature decreases markedly on the exterior of the summit crater. While a long-wave infrared (LWIR) sensor would be ideal for volcano monitoring, we have shown that the thermal state of an active volcano can be monitored using the SWIR channels of a reflective hyperspectral imager. References: Dennison, Philip E., Kraivut Charoensiri, Dar A. Roberts, Seth H. Peterson, and Robert O. Green (2006). Wildfire temperature and land cover modeling using hyperspectral data, Remote Sens. Environ., vol. 100, pp. 212-222. Green, R. O. (1996). Estimation of biomass fire temperature and areal extent from calibrated AVIRIS spectra, in Summaries of the 6th Annual JPL Airborne Earth Science Workshop, Pasadena, CA JPL Publ. 96-4, vol. 1, pp. 105-113. Lockwood, Ronald B., Thomas W. Cooley, Richard M. Nadile, James A. Gardner, Peter S. Armstrong, Abraham M. Payton, Thom M. Davis, Stanley D. Straight, Thomas G. Chrien, Edward L. Gussin, and David Makowski (2006). Advanced Responsive Tactically-Effective Military Imaging Spectrometer (ARTEMIS) Design, in Proceedings of the 2006 IEEE International Geoscience and Remote Sensing Symposium, 31 July-4 August 2006, Denver, Colorado. Ramsey, Michael S., and Luke P. Flynn (2004). Strategies, insights, and the recent advances in volcanic monitoring and mapping with data from NASA’s Earth Observing System, Jour. of Volcanology and Geothermal Research, vol. 135, pp. 1-11. Young, Joseph (2009). EO-1 Weekly status report for September 24-30, 2009, Earth Science Mission Operations (ESMO) Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771.

Cipar, J. J.; Dunn, R.; Cooley, T.

2010-12-01

182

Development of Chinese pushbroom hyperspectral imager (PHI)  

NASA Astrophysics Data System (ADS)

As a remote sensing instrument, pushbroom hyperspectral imager demonstrates its advantages in many application operations. It brings people better spectral resolution with high signal-to-noise-ratio. As increase of the demand of environment study and city planning. In 1997 Pushbroom Hyperspectral Imager (PHI) was built in Shanghai. It has a refractive optical system with reflective grading as spectral divergence device and area array silicon CCD as detector. It upgrades SAIS with optimized optical system, 12 bit digitizer and PENTIUM in-bed computer. Special efforts are mae on parallel data recording to save more information with an inexpensive hardware configuration. The system can be easily mounted on gyro stabilize platform and work with dynamic GPS. PHI has succeeded in remote sensing operation for city planning of Beihai, Guangxi province. This paper will introduce the development of PHI, including system design, calibration and performance in operation. Plans for further studies, including real-time data process for pixel binning and data bus improvement for data rate speeding, are also introduced.

Shao, Hui; Xue, Yongqi; Wang, Jianyu

1998-08-01

183

Feature reduction and morphological processing for hyperspectral image data  

NASA Astrophysics Data System (ADS)

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

Casasent, David; Chen, Xue-Wen

2004-01-01

184

Massively parallel processing of remotely sensed hyperspectral images  

NASA Astrophysics Data System (ADS)

In this paper, we develop several parallel techniques for hyperspectral image processing that have been specifically designed to be run on massively parallel systems. The techniques developed cover the three relevant areas of hyperspectral image processing: 1) spectral mixture analysis, a popular approach to characterize mixed pixels in hyperspectral data addressed in this work via efficient implementation of a morphological algorithm for automatic identification of pure spectral signatures or endmembers from the input data; 2) supervised classification of hyperspectral data using multi-layer perceptron neural networks with back-propagation learning; and 3) automatic target detection in the hyperspectral data using orthogonal subspace projection concepts. The scalability of the proposed parallel techniques is investigated using Barcelona Supercomputing Center's MareNostrum facility, one of the most powerful supercomputers in Europe.

Plaza, Javier; Plaza, Antonio; Valencia, David; Paz, Abel

2009-08-01

185

Point-and-stare operation and high-speed image acquisition in real-time hyperspectral imaging  

NASA Astrophysics Data System (ADS)

The design and optical performance of a small-footprint, low-power, turnkey, Point-And-Stare hyperspectral analyzer, capable of fully automated field deployment in remote and harsh environments, is described. The unit is packaged for outdoor operation in an IP56 protected air-conditioned enclosure and includes a mechanically ruggedized fully reflective, aberration-corrected hyperspectral VNIR (400-1000 nm) spectrometer with a board-level detector optimized for point and stare operation, an on-board computer capable of full system data-acquisition and control, and a fully functioning internal hyperspectral calibration system for in-situ system spectral calibration and verification. Performance data on the unit under extremes of real-time survey operation and high spatial and high spectral resolution will be discussed. Hyperspectral acquisition including full parameter tracking is achieved by the addition of a fiber-optic based downwelling spectral channel for solar illumination tracking during hyperspectral acquisition and the use of other sensors for spatial and directional tracking to pinpoint view location. The system is mounted on a Pan-And-Tilt device, automatically controlled from the analyzer's on-board computer, making the HyperspecTM particularly adaptable for base security, border protection and remote deployments. A hyperspectral macro library has been developed to control hyperspectral image acquisition, system calibration and scene location control. The software allows the system to be operated in a fully automatic mode or under direct operator control through a GigE interface.

Driver, Richard D.; Bannon, David P.; Ciccone, Domenic; Hill, Sam L.

2010-04-01

186

Egg embryo development detection with hyperspectral imaging  

NASA Astrophysics Data System (ADS)

In the U. S. egg industry, anywhere from 130 million to over one billion infertile eggs are incubated each year. Some of these infertile eggs explode in the hatching cabinet and can potentially spread molds or bacteria to all the eggs in the cabinet. A method to detect the embryo development of incubated eggs was developed. Twelve brown-shell hatching eggs from two replicates (n=24) were incubated and imaged to identify embryo development. A hyperspectral imaging system was used to collect transmission images from 420 to 840 nm of brown-shell eggs positioned with the air cell vertical and normal to the camera lens. Raw transmission images from about 400 to 900 nm were collected for every egg on days 0, 1, 2, and 3 of incubation. A total of 96 images were collected and eggs were broken out on day 6 to determine fertility. After breakout, all eggs were found to be fertile. Therefore, this paper presents results for egg embryo development, not fertility. The original hyperspectral data and spectral means for each egg were both used to create embryo development models. With the hyperspectral data range reduced to about 500 to 700 nm, a minimum noise fraction transformation was used, along with a Mahalanobis Distance classification model, to predict development. Days 2 and 3 were all correctly classified (100%), while day 0 and day 1 were classified at 95.8% and 91.7%, respectively. Alternatively, the mean spectra from each egg were used to develop a partial least squares regression (PLSR) model. First, a PLSR model was developed with all eggs and all days. The data were multiplicative scatter corrected, spectrally smoothed, and the wavelength range was reduced to 539 - 770 nm. With a one-out cross validation, all eggs for all days were correctly classified (100%). Second, a PLSR model was developed with data from day 0 and day 3, and the model was validated with data from day 1 and 2. For day 1, 22 of 24 eggs were correctly classified (91.7%) and for day 2, all eggs were correctly classified (100%). Although the results are based on relatively small sample sizes, they are encouraging. However, larger sample sizes, from multiple flocks, will be needed to fully validate and verify these models. Additionally, future experiments must also include non-fertile eggs so the fertile / non-fertile effect can be determined.

Lawrence, Kurt C.; Smith, Douglas P.; Windham, William R.; Heitschmidt, Gerald W.; Park, Bosoon

2006-10-01

187

Hyperspectral image lossless compression algorithm based on adaptive band regrouping  

NASA Astrophysics Data System (ADS)

Hyperspectral image has weak spatial correlation and strong spectral correlation. As to exploit spectrum redundancy sufficiently, it must be pre-processed. In this paper, a new algorithm for lossless compression of hyperspectral images based on adaptive band regrouping is proposed. Firstly, the affinity propagation clustering algorithm (AP) is chosen for band regrouping according to interband correlation. Then a linear prediction algorithm based on context prediction is applied to the hyperspectral images in different groups. Finally, the experimental results show that the proposed algorithm achieves performance gains of 1.12bpp over the conventional algorithm.

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

2009-08-01

188

Hyperspectral Imaging in Diabetic Foot Wound Care  

PubMed Central

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

Yudovsky, Dmitry; Nouvong, Aksone; Pilon, Laurent

2010-01-01

189

Detection of chemical pollutants by passive LWIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

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

2012-09-01

190

LWIR hyperspectral imaging application and detection of chemical precursors  

NASA Astrophysics Data System (ADS)

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

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

2012-10-01

191

[Calibration of the detection performance for hyperspectral imager].  

PubMed

As an image-spectrum merging technology, hyperspectral imaging has been used in battlefield reconnaissance rapidly. The calibration of hyperspectral imager is a process that corrects itself's output. An UV/Vis/NIR hyperspectral military detection system based on BTCCD and concave grating parts is analyzed, and it's spectral resolution is 3.3 nm. Some calibration and evaluation methods are discussed for hyperspectral imaging system which operates at 0.25-1.1 mm waveband. Image quality assessment based on an uniform radiation source with target, spectral quality assessment based on laser and Hg lamp, and radiation performance calibration based on high accuracy standard are researched detailedly. After several steps of radiation calibration and spectral fidelity verification, the reflective curve which represents the objective spectral character was obtained, satisfying the requirement of 0.2 mrad spatial resolution and +/-0.5% dispersive linearity. Finally, satisfactory results were obtained with these methods in a military detection system. PMID:18051502

Xu, Qiang; Jin, Wei-Qi; Fu, Lian-Qiu

2007-09-01

192

Hypercomplex Quality Assessment of Multi\\/Hyperspectral Images  

Microsoft Academic Search

This letter presents a novel image quality index which extends the Universal Image Quality Index for monochrome images to multispectral and hyperspectral images through hypercomplex numbers. The proposed index is based on the computation of the hypercomplex correlation coefficient between the reference and tested images, which jointly measures spectral and spatial distortions. Experimental results, both from true and simulated images,

Andrea Garzelli; Filippo Nencini

2009-01-01

193

Food quality assessment by NIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

194

Development of image mappers for hyperspectral biomedical imaging applications  

PubMed Central

A new design and fabrication method is presented for creating large-format (>100 mirror facets) image mappers for a snapshot hyperspectral biomedical imaging system called an image mapping spectrometer (IMS). To verify this approach a 250 facet image mapper with 25 multiple-tilt angles is designed for a compact IMS that groups the 25 subpupils in a 5 × 5 matrix residing within a single collecting objective's pupil. The image mapper is fabricated by precision diamond raster fly cutting using surface-shaped tools. The individual mirror facets have minimal edge eating, tilt errors of <1 mrad, and an average roughness of 5.4 nm.

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

2010-01-01

195

Hyperspectral Image Analysis Using Genetic Programming  

Microsoft Academic Search

Genetic programming is used to evolve min- eral identication functions for hyperspec- tral images.1 The input image set comprises 168 images from dierent wavelengths rang- ing from 428 nm (visible blue) to 2507 nm (invisible shortwave in the infrared), taken over Cuprite, Nevada, with the AVIRIS hy- perspectral sensor. A composite mineral im- age indicating the overall reectance

Brian J. Ross; Anthony G. Gualtieri; Frank Fueten; Paul Budkewitsch

2002-01-01

196

GPU implementation of JPEG2000 for hyperspectral image compression  

NASA Astrophysics Data System (ADS)

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.

Ciznicki, Milosz; Kurowski, Krzysztof; Plaza, Antonio

2011-10-01

197

Hyperspectral image analysis workbench for environmental science applications.  

National Technical Information Service (NTIS)

A significant challenge to the information sciences is to provide more powerful and accessible means to exploit the enormous wealth of data available from high-resolution imaging spectrometry, or ''hyperspectral'' imagery, for analysis, for mapping purpos...

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

1992-01-01

198

Decision fusion strategy for target recognition in hyperspectral images  

NASA Astrophysics Data System (ADS)

Hyperspectral sensors allow a considerable improvement in the performance of a target recognition process to be achieved. This characteristic is particular interesting in a lot of military and civilian remote sensing applications, such as automatic target recognition (ATR) and surveillance of wide areas. In this framework, real time processing of the observed scenario is becoming a key issue, because it permits the operator to provide immediate assessment of the surveyed area. In the literature is presented a line-by-line real time implementation of the widely used Constrained Energy Minimization (CEM) target detector. However, experimental results show that sometimes the CEM filter produces False Alarms (FAs) corresponding to rare objects, whose spectra are angularly very different from the target signature and from the natural background classes in the image. A solution to such a problem is presented in this work: the proposed strategy is based on the decision fusion of the CEM and the SAM algorithms. Only those pixels that pass the CEM-stage are processed by the SAM algorithm. The second stage allows false alarms to be reduced by preserving most of target pixels. The fusion strategy is applied to an experimental hyperspectral data set to recognize a known green target. Detection performance is numerically evaluated and compared to the one of the classical CEM detector.

Acito, N.; Greco, M.; Diani, M.; Corsini, G.

2006-10-01

199

New Method for Atmospheric Correction and Aerosol Optical Property Retrieval for VIS-SWIR Multi- and Hyperspectral Imaging Sensors: QUAC (QUick Atmospheric Correction).  

National Technical Information Service (NTIS)

We describe a new VNIR-SWIR atmospheric correction method for multi- and hyperspectral imagery, dubbed QUAC (QUick Atmospheric Correction) that also enables retrieval of the wavelength-dependent optical depth of the aerosol or haze and molecular absorbers...

L. S. Bernstein S. M. Adler-Golden R. L. Sundberg R. Y. Levine T. C. Perkins

2005-01-01

200

Hyperspectral imaging technology for pharmaceutical analysis  

NASA Astrophysics Data System (ADS)

The sensitivity and spatial resolution of hyperspectral imaging instruments are tested in this paper using pharmaceutical applications. The first experiment tested the hypothesis that a near-IR tunable diode-based remote sensing system is capable of monitoring degradation of hard gelatin capsules at a relatively long distance. Spectra from the capsules were used to differentiate among capsules exposed to an atmosphere containing imaging spectrometry of tablets permits the identification and composition of multiple individual tables to be determined simultaneously. A near-IR camera was used to collect thousands of spectra simultaneously from a field of blister-packaged tablets. The number of tablets that a typical near-IR camera can currently analyze simultaneously form a field of blister- packaged tablets. The number of tablets that a typical near- IR camera can currently analyze simultaneously was estimated to be approximately 1300. The bootstrap error-adjusted single-sample technique chemometric-imaging algorithm was used to draw probability-density contour plots that revealed tablet composition. The single-capsule analysis provides an indication of how far apart the sample and instrumentation can be and still maintain adequate S/N, while the multiple- sample imaging experiment gives an indication of how many samples can be analyzed simultaneously while maintaining an adequate S/N and pixel coverage on each sample.

Hamilton, Sara J.; Lodder, Robert A.

2002-06-01

201

Bayesian Fusion of Multispectral and Hyperspectral Image in Wavelet Domain  

Microsoft Academic Search

In this work, a technique is presented for the fusion of multi-spectral (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

Yifan Zhang; Steve De Backer; Paul Scheunders

2008-01-01

202

Spatial enhancement of hyperion hyperspectral data through ALI panchromatic image  

Microsoft Academic Search

This paper presents two novel image fusion methods, suitable for sharpening of hyperspectral (HS) images by means of a panchromatic (Pan) observation: the HS bands expanded to the finer scale of the Pan image are sharpened by adding the spatial details which are calculated by the PAN image. Since a direct, unconditioned injection of Pan details gives unsatisfactory results, a

Luca Capobianco; Andrea Garzelli; Filippo Nencini; Luciano Alparone; Stefano Baronti

2007-01-01

203

Meat quality evaluation by hyperspectral imaging technique: an overview.  

PubMed

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

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

2012-01-01

204

Low-Complexity Principal Component Analysis for Hyperspectral Image Compression  

Microsoft Academic Search

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

Qian Du; James E. Fowler

2008-01-01

205

AHI: an airborne long-wave infrared hyperspectral imager  

Microsoft Academic Search

The AHI system was designed to detect the presence of buried land mines from the air through detection of along wave IR observable associated with mine installation. The system is a helicopter-borne LWIR hyperspectral imager with real time on-board radiometric calibration and mine detection. It collects hyperspectral imagery from 7.5 to 11.5 micrometers in either 256 or 32 spectral bands.

Paul G. Lucey; Tim J. Williams; Marc Mignard; Jeffrey Julian; Daniel Kobubun; Gregory Allen; David Hampton; William Schaff; Mike J. Schlangen; Edwin M. Winter; William B. Kendall; Alan D. Stocker; Keith A. Horton; Anu P. Bowman

1998-01-01

206

Hyperspectral image compression using bands combination wavelet transformation  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging technology is the foreland of the remote sensing development in the 21st century and is one of the most important focuses of the remote sensing domain. Hyperspectral images can provide much more information than multispectral images do and can solve many problems which can't be solved by multispectral imaging technology. However this advantage is at the cost of massy quantity of data that brings difficulties of images' process, storage and transmission. Research on hyperspectral image compression method has important practical significance. This paper intends to do some improvement of the famous KLT-WT-2DSPECK (Karhunen-Loeve transform+ wavelet transformation+ two-dimensional set partitioning embedded block compression) algorithm and advances KLT + bands combination 2DWT + 2DSPECK algorithm. Experiment proves that this method is effective.

Wang, Wenjie; Zhao, Zhongming; Zhu, Haiqing

2009-10-01

207

Band regrouping-based lossless compression of hyperspectral images  

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

208

Pushbroom NIR hyperspectral imager using MOEMS scanning grating chips  

NASA Astrophysics Data System (ADS)

"NIR Hyperspectral Imaging" is a universal tool to measure and control chemical properties of objects. The combination of digital imaging and molecular spectroscopy exhibits a great benefit, especially for in- and on-line analysis. However, a wide use is impeded at present due to the expensive and complex system approach. One reason is the high cost of two dimensional InGaAs detector arrays, another one is the special glass that is used in the near infrared NIR. In this paper a new approach for a NIR Imaging spectrometer is presented. The base of the new Pushbroom Hyperspectral Imager is a micromechanical scanning device with an integrated diffraction grating. This MOEMS device is made in a standard SOI fabrication process developed at Fraunhofer IPMS. 1 2 3 For the Hyperspectral Imager, a new all-reflective optical system based on a Schiefspiegler setup has been developed. The simulated optical configuration and the achieved performance of the system will be presented.

Grüger, Heinrich; Egloff, Thomas; Scholles, Michael; Zimmer, Fabian; Müller, Michael; Schenk, Harald

2008-02-01

209

Passive shortwave infrared technology and hyperspectral imaging for maritime applications  

Microsoft Academic Search

We present image data and discuss naval sensing applications of SWIR and Hyperspectral SWIR imaging in littoral and marine environments under various light conditions. These environments prove to be challenging for persistent surveillance applications as light levels may vary over several orders of magnitude within and from scene to scene. Additional difficulties include imaging over long water paths where marine

K. Peter Judd; James R. Waterman; J. M. Nichols

2010-01-01

210

Hyperspectral image lossless compression based on prediction tree algorithm  

Microsoft Academic Search

A new hyperspectral image compression algorithm-NMST (Near Min Spanning Tree) is proposed. The near minimum spanning tree is constructed according to the image structure and is taken as a prediction tree in image compression. The result shows the NMST algorithm can improve the compression speed with little decrease of compression ratio.

HengShu Liu; LianQing Huang

2003-01-01

211

Hyperspectral Image Compression with Optimization for Spectral Analysis  

Microsoft Academic Search

Hyperspectral imaging is of interest in a large number of remote sensing applications, such as geology and pollution monitoring, in order to detect and analyze surface and atmospheric composition. The processing of these images, called spectral analysis, allows for the identification of the specific mineralogical and agricultural elements which compose an image. We seek to understand how loss due to

Kameron Romines; Edwin S. Hong

2007-01-01

212

VST-based lossy compression of hyperspectral data for new generation sensors  

NASA Astrophysics Data System (ADS)

This paper addresses lossy compression of hyperspectral images acquired by sensors of new generation for which signaldependent component of the noise is prevailing compared to the noise-independent component. First, for sub-band (component-wise) compression, it is shown that there can exist an optimal operation point (OOP) for which MSE between compressed and noise-free image is minimal, i.e., maximal noise filtering effect is observed. This OOP can be observed for two approaches to lossy compression where the first one presumes direct application of a coder to original data and the second approach deals with applying direct and inverse variance stabilizing transform (VST). Second, it is demonstrated that the second approach is preferable since it usually provides slightly smaller MSE and slightly larger compression ratio (CR) in OOP. One more advantage of the second approach is that the coder parameter that controls CR can be set fixed for all sub-band images. Moreover, CR can be considerably (approximately twice) increased if sub-band images after VST are grouped and lossy compression is applied to a first sub-band image in a group and to "difference" images obtained for this group. The proposed approach is tested for Hyperion hyperspectral images and shown to provide CR about 15 for data compression in the neighborhood of OOP.

Zemliachenko, Alexander N.; Kozhemiakin, Ruslan A.; Uss, Mykhail L.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

2013-10-01

213

Hyperspectral Imaging of the Coastal Ocean.  

National Technical Information Service (NTIS)

The Navy has a requirement to rapidly and covertly characterize the coastal environment in support of Joint Strike Initiatives. Over the past 14 years we have demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acqui...

C. O. Davis

2009-01-01

214

Hyperspectral Imaging of the Coastal Ocean.  

National Technical Information Service (NTIS)

The Navy has a requirement to rapidly and covertly characterize the coastal environment in support of Joint Strike Initiatives. Over the past 12 years we have demonstrated that spaceborne hyperspectral remote sensing is the best approach to covertly acqui...

C. O. Davis

2008-01-01

215

Compressive Hyperspectral Imaging and Anomaly Detection.  

National Technical Information Service (NTIS)

We have developed and applied successfully new algorithms for hyperspectral imagery. These include compressive sensing, anomaly detection, target detection, endmember detection, unmixing and change detection. These were tested on data provided by AFRL wit...

K. Kelly P. Thiyanarantnam S. Chen S. Osher W. Yin

2013-01-01

216

Subspace method for multispectral, hyperspectral, and SAR image classification  

NASA Astrophysics Data System (ADS)

Various types of remotely sensed data (i.e., difference sensors, spatial resolutions, num of bands) collected over a span of years available today require advanced and innovative techniques to extract information and thematic maps useful for observing and characterizing both natural and human-induced changes over large areas. Land cover classification is one of the most important and typical applications of remote sensing. In the last years, new methods based on optimization and neural network algorithms have been proposed, and among them, subspace methods are very promising [1]-[3]. They are particularly useful for high dimensional and multisource data analysis, which is generally difficult to accomplish with classical statistical methods. The objective of subspace methods is to represent high-dimensional data in a low-dimensional subspaces. Classification then takes place on the chosen subspaces. In this paper, we carried out experiments with three types of remote sensing images, a Landsat ETM+ data, the AVIRIS hyperspectral data and CASI-3 hyperspectral data, and a recent lunched fully polarimetric Phased Array-type L-band Synthetic Aperture Radar (PALSAR) data. Experimental results show that subspace method is a valid and effective alternative to other pattern recognition approaches for the classification of various types of remote sensing data. The advantages of the subspace method are: (1) only 3 parameters are required to be set, and these can easily be determined by an automatic procedure; (2) The computational speed is faster than SVM and similar to the MLC; and (3) Could be a promising tool for future land cover classifications. References [1] H. Bagan, et al., "Classification of airborne hyperspectral data based on the average learning subspace method", IEEE Geosci. Remote Sens. Lett., vol. 5, no. 3. 2008. [2] H. Bagan, Y. Yamagata. "Improved subspace classification method for multispectral remote sensing image classification". PE & RS, vol. 76, No.11, 2010. [3] H. Bagan, T. Kinoshita, Y.Yamagata, "Combination of AVNIR-2, PALSAR, and Polarimetric Parameters for Land Cover Classification", IEEE Trans. Geosci. Remote Sens. in press.

Bagan, H.; Yamagata, Y.

2011-12-01

217

In vivo and in vitro hyperspectral imaging of cervical neoplasia  

NASA Astrophysics Data System (ADS)

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

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

2014-02-01

218

Hyperspectral Image Compression Using Three-Dimensional Wavelet Embedded Zeroblock Coding  

Microsoft Academic Search

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

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

2007-01-01

219

Lossless compression of hyperspectral images based on 3D context prediction  

Microsoft Academic Search

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

Lin Bai; Mingyi He; Yuchao Dai

2008-01-01

220

Lossless Hyperspectral-Image Compression Using Context-Based Conditional Average  

Microsoft Academic Search

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,

Hongqiang Wang; S. Derin Babacan; Khalid Sayood

2007-01-01

221

Hyperspectral imaging based techniques in fluff characterization  

NASA Astrophysics Data System (ADS)

Light fractions produced after vehicles dismantling are conventionally defined as "fluff" or Automotive Shredder Residue (ASR). They represent about the 25% of the weight of a car and are usually constituted by materials characterized by intrinsic low specific gravity (i.e. plastics, rubber, synthetic foams, etc.). Fluff is usually polluted by metal contaminants (i.e. copper, aluminum, brass, iron, etc.), that strongly affect, especially in the final fractions, the possibility to utilize such material as fuel in co-combustion process, reducing the waste disposal and increasing at the same time energy production. In this paper, innovative selection-control architectures, based on hyperspectral imaging, in the visible- near infrared (VIS-NIR) field, have been investigated. In order to define suitable inspection strategies for the recognition and separation between useful (fluff) and polluting (metals) materials, samples of light and heavy plastics and metals have been collected in a recycling plant. Reflectance spectra have been acquired in the VIS-NIR field (400-1000 nm). Results showed as the different materials are characterized by different spectral signatures and that recognition of plastics and metals can be obtained adopting a wavelength ratio in the NIR (700-1000 nm) field.

Bonifazi, Giuseppe; Serranti, Silvia

2006-11-01

222

Hyperspectral retinal imaging with a spectrally tunable light source  

NASA Astrophysics Data System (ADS)

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

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

2011-02-01

223

Hyperspectral retinal imaging with a spectrally tunable light source  

NASA Astrophysics Data System (ADS)

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

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

2011-03-01

224

Diagnosis method of cucumber downy mildew with NIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

This study was carried out to develop a hyperspectral imaging system in the near infrared (NIR) region (900-1700 nm) to diagnose cucumber downy mildew. Hyperspectral images were acquired from each diseased cucumber leaf samples with downy mildew and then their spectral data were extracted. Spectral data were analyzed using principal component analysis (PCA) to reduce the high dimensionality of the data and for selecting some important wavelengths. Out of 256 wavelengths, only two wavelengths (1426 and 1626nm) of first PC were selected as the optimum wavelengths for the diagnosis of cucumber downy mildew. The data analysis showed that it is possible to diagnose cucumber downy mildew with few numbers of wavelengths on the basis of their statistical image features and histogram features. The results revealed the potentiality of NIR hyperspectral imaging as an objective and non-destructive method for the authentication and diagnosis of cucumber downy mildew.

Tian, Youwen; Li, Tianlai; Zhang, Lin; Zhang, Xiaodong

2011-11-01

225

Unsupervised segmentation for hyperspectral images using mean shift segmentation  

NASA Astrophysics Data System (ADS)

In this paper, we propose an unsupervised segmentation method for hyperspectral images using mean shift filtering. One major problem of traditional mean shift algorithms is the difficulty of determining kernel bandwidths. We address this problem by using efficient clustering methods. First, PCA (Principal Component Analysis) was applied to hyperspectral images and the first three eigenimages were selected. Then, we applied mean shift filtering to the selected images using a kernel with a small bandwidth. This procedure produced a large number of clusters. In order to merge the homogeneous clusters, we used the Bhattacharyya distance. Experiments showed promising segmentation results without requiring user input.

Lee, Sangwook; Lee, Chulhee

2010-08-01

226

Calibration procedures and measurements for the COMPASS hyperspectral imager  

NASA Astrophysics Data System (ADS)

The COMPact Airborne Spectral Sensor (COMPASS) hyperspectral imager (HSI) developed at the Army Night Vision and Electronic Sensors Directorate (NVESD) operates in the solar reflective region. The fundamental advance of the COMPASS instrument is the ability to capture 400nm to 2350nm on a single focal plane, eliminating boresighting and co-registration issues characteristic of dual FPA instruments for visible and SWIR regions. This paper presents a calibration procedure for COMPASS including spectral band profiles and radiometric calibration. These procedures expand on successful calibration procedures used for the Night Vision Infrared Spectrometer (NVIS) system. A high-resolution monochromator was used to map the band center and bandwidth profiles across the FPA with an accuracy goal of +/-0.5nm using several different illumination configurations. Although optical distortions are below previous measurement capabilities, accurate band profiles provide additional data to map potential distortions within the system. Radiometric calibration was performed with a NIST-traceable flood source. Test results are presented showing a well-behaved system with an average spectral bandwidth of 8.0nm +/-0.5nm over the instrument spectral range.

Zadnik, Jerome; Guerin, Daniel; Moss, Robert; Orbeta, Alan; Dixon, Roberta; Simi, Christopher G.; Dunbar, Susannah; Hill, Anthony

2004-08-01

227

Spatial pattern discovery for hyperspectral images based on multiresolution analysis  

Microsoft Academic Search

A method to discover spatial patterns that are dominant or unique in each spectral band of a hyperspectral image is presented. The approach relies on the multiresolution image fusion framework as well as on exploratory visual data analysis. It is shown that the proportion of dominant details obtained from multiresolution decomposition, and their reconstructed spatial signature, provides valuable clues for

Mario Beauchemin

2012-01-01

228

Spatial pattern discovery for hyperspectral images based on multiresolution analysis  

Microsoft Academic Search

A method to discover spatial patterns that are dominant or unique in each spectral band of a hyperspectral image is presented. The approach relies on the multiresolution image fusion framework as well as on exploratory visual data analysis. It is shown that the proportion of dominant details obtained from multiresolution decomposition, and their reconstructed spatial signature, provides valuable clues for

Mario Beauchemin

2011-01-01

229

Using hyperspectral imaging to characterize the coastal environment  

Microsoft Academic Search

In shallow waters visible remote sensing systems frequently image the bottom including features, such as grass beds and coral reefs. Resolving the bottom features as viewed through the complex and varying optical properties of the water column is the central problem in coastal remote sensing. This requires hyperspectral imaging. There are three factors to estimate: water depth, bottom reflectance, and

C. O. Davis; K. L. Carder; ZhongPing Lee

2002-01-01

230

Multistage Lattice Vector Quantization for Hyperspectral Image Compression  

Microsoft Academic Search

Lattice vector quantization (LVQ) offers substantial reduction in computational load and design complexity due to the lattice regular structure [1]. In this paper, we extended the SPIHT [2] coding algorithm with lattice vector quantization to code hyperspectral images. In the proposed algorithm, multistage lattice vector quantization (MLVQ) is used to exploit correlations between image slices, while offering successive refinement with

Ying Liu; W. A. Pearlman

2007-01-01

231

Compression of hyperspectral image based on three-dimensional SPIHT algorithm  

Microsoft Academic Search

In response to the high data volumes of hyperspectral images and high data rates required for their transmission, many hyperspectral data compression methods have been researched in recent years. In this paper, a new compression algorithm for hyperspectral image is proposed, which pays much more attention to its peculiarity of much higher spectral resolution. The new method combines three-dimensional integer

Shanshan Yu; Yezhang Zhang

2002-01-01

232

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

Microsoft Academic Search

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

Antonio Plaza; David Valencia; Javier Plaza

2006-01-01

233

SHARE 2012: large edge targets for hyperspectral imaging applications  

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

234

Recognition of wheat preharvest sprouting based on hyperspectral imaging  

NASA Astrophysics Data System (ADS)

An imaging spectrometer was used to acquire hyperspectral images of 120 strains of wheat ears and seeds under four different watering treatments. Whether wheat preharvest sprouting occurred could be reflected by spectral characteristics. Therefore, it was possible to judge whether wheat ears sprouted according to changes of spectral curve at 675 nm. According to principal component analysis of mean spectral reflectivity values of wheat seeds, it was found that wheat seeds watered three times every day and wheat seeds watered once every day were significantly different from nonsprouting wheat seeds soaked all day and original dry seeds due to significant sprouting situations, suggesting that imaging spectra can differentiate different extent of wheat preharvest sprouting. Glume had an influence on the hyperspectral images of wheat ears, therefore the hyperspectral images of wheat ears could be used to measure sprouting only when serious sprouting occurred. At an early stage of sprouting, only the hyperspectral images of wheat seeds could be used to analyze the sprouting of wheat.

Wu, Qiong; Zhu, Dazhou; Wang, Cheng; Ma, Zhihong; Wang, Jihua

2012-11-01

235

Feature extraction of hyperspectral images using wavelet and matching pursuit  

NASA Astrophysics Data System (ADS)

Since hyperspectral images contain rich and fine spectral information, an improvement of land use/cover classification accuracy is highly expected from the utilization of such images. However, the traditional statistics-based classification methods which have been successfully applied to multispectral data in the past are not as effective as to hyperspectral data. One major reason is that the number of spectral bands is too large relative to the number of training samples. This problem is caused by curse of dimensionality, which refers to the fact that the sample size required for training a specific classifier grows exponentially with the number of spectral bands. A simple but sometimes very effective way to overcome this problem is to reduce the dimensionality of hyperspectral images. This can be done by feature extraction that a small number of salient features are extracted from the hyperspectral data when confronted with a limited size of training samples. In this paper, a new feature extraction method based on the matching pursuit (MP) is proposed to extract useful features for the classification of hyperspectral images. The matching pursuit algorithm uses a greedy strategy to find an adaptive and optimal representation of the hyperspectral data iteratively from a highly redundant wavelet packets dictionary. An AVIRIS data set was tested to illustrate the classification performance after matching pursuit method was applied. In addition, some existing feature extraction methods based on the wavelet transform are also compared with the matching pursuit method in terms of the classification accuracies. The experiment results showed that the wavelet and matching pursuit method exactly provide an effective tool for feature extraction. The classification problem caused by curse of dimensionality can be avoided by matching pursuit and wavelet-based dimensionality reduction.

Hsu, Pai-Hui

236

Remote sensing for gas plume monitoring using state-of-the-art infrared hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Under contract to the US Air Force and Navy, Pacific Advanced Technology has developed a very sensitive hyperspectral imaging infrared camera that can perform remote imaging spectro-radiometry. One of the most exciting applications for this technology is in the remote monitoring of gas plume emissions. Pacific Advanced Technology (PAT) currently has the technology available to detect and identify chemical species in gas plumes using a small light weight infrared camera the size of a camcorder. Using this technology as a remote sensor can give advanced warning of hazardous chemical vapors undetectable by the human eye as well as monitor the species concentrations in a gas plume from smoke stack and fugitive leaks. Some of the gas plumes that have been measured and species detected using an IMSS imaging spectrometer are refinery smoke stacks plumes with emission of CO2, CO, SO2, NOx. Low concentration vapor unseen by the human eye that has been imaged and measured is acetone vapor evaporating at room temperature. The PAT hyperspectral imaging sensor is called 'Image Multi-spectral Sensing or IMSS.' The IMSS instrument uses defractive optic technology and exploits the chromatic aberrations of such lenses. Using diffractive optics for both imaging and dispersion allows for a very low cost light weight robust imaging spectrometer. PAT has developed imaging spectrometers that span the spectral range from the visible, midwave infrared (3 to 5 microns) and longwave infrared (8 to 12 microns) with this technology. This paper will present the imaging spectral data that we have collected on various targets with our hyperspectral imaging instruments as will also describe the IMSS approach to imaging spectroscopy.

Hinnrichs, Michele

1999-02-01

237

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

PubMed

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

Tang, Fei; Xu, Han-Qiu

2014-04-01

238

Developing digital tissue phantoms for hyperspectral imaging of ischemic wounds  

PubMed Central

Hyperspectral imaging has the potential to achieve high spatial resolution and high functional sensitivity for non-invasive assessment of tissue oxygenation. However, clinical acceptance of hyperspectral imaging in ischemic wound assessment is hampered by its poor reproducibility, low accuracy, and misinterpreted biology. These limitations are partially caused by the lack of a traceable calibration standard. We proposed a digital tissue phantom (DTP) platform for quantitative calibration and performance evaluation of spectral wound imaging devices. The technical feasibility of such a DTP platform was demonstrated by both in vitro and in vivo experiments. The in vitro DTPs were developed based on a liquid blood phantom model. The in vivo DTPs were developed based on a porcine ischemic skin flap model. The DTPs were projected by a Hyperspectral Image Projector (HIP) with high fidelity. A wide-gap 2nd derivative oxygenation algorithm was developed to reconstruct tissue functional parameters from hyperspectral measurements. In this study, we have demonstrated not only the technical feasibility of using DTPs for quantitative calibration, evaluation, and optimization of spectral imaging devices but also its potential for ischemic wound assessment in clinical practice.

Xu, Ronald X.; Allen, David W.; Huang, Jiwei; Gnyawali, Surya; Melvin, James; Elgharably, Haytham; Gordillo, Gayle; Huang, Kun; Bergdall, Valerie; Litorja, Maritoni; Rice, Joseph P.; Hwang, Jeeseong; Sen, Chandan K.

2012-01-01

239

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

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

240

Hyperspectral image fusion by the similarity measure-based variational method  

NASA Astrophysics Data System (ADS)

Hyperspectral remote sensing is widely used in many fields suchas agriculture, military detection, mineral exploration, and so on. Hyperspectral data has very high spectral resolution, but much lower spatial resolution than the data obtained by other types of sensors. The low spatial resolution restrains its wide applications. On the contrary, we easily obtain images with high spatial resolution but insufficient spectral resolution (like panchromatic images). Naturally, people expect to obtain images that have high spatial and spectral resolution at the same time by the hyperspectral image fusion. In this paper, a similarity measure-based variational method is proposed to achieve the fusion process. The main idea is to transform the image fusion problem to an optimization problem based on the variational model. We first establish a fusion model that constrains the spatial and spectral information of the original data at the same time, then use the split bregman iteration to obtain the final fused data. Also, we analyze the convergence of the method. The experiments on the synthetic and real data show that the fusion method preserves the information of the original images efficiently, especially on the spectral information.

Shi, Zhenwei; An, Zhenyu; Jiang, Zhiguo

2011-07-01

241

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

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

242

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images  

NASA Technical Reports Server (NTRS)

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Kiely, Aaron; Xie, Hua; Klimesh, matthew; Aranki, Nazeeh

2010-01-01

243

Fast processing spectral discrimination for hyperspectral imagers based on interferometry  

NASA Astrophysics Data System (ADS)

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

Zucco, M.; Pisani, M.

2014-05-01

244

A fast iterative kernel PCA feature extraction for hyperspectral images  

Microsoft Academic Search

A fast iterative Kernel Principal Component Analysis (KPCA) is proposed to extract features from hyperspectral images. The proposed method is a kernel version of the Candid Covariance-Free Incremental Principal Component Analysis, which solves the eigenvectors through iteration. Without performing eigen decomposition on Gram matrix, our method can reduce the space complexity and time complexity greatly. Experimental results were validated in

Wenzhi Liao; Aleksandra Pizurica; Wilfried Philips; Youguo Pi

2010-01-01

245

Visual enhancement of old documents with hyperspectral imaging  

Microsoft Academic Search

Hyperspectral imaging (HSI) of historical documents is becoming more common at national libraries and archives. HSI is useful for many tasks related to document conservation and management as it provides detailed quantitative measurements of the spectral reflectance of the document that is not limited to the visible spectrum. In this paper, we focus on how to use the invisible spectra,

Seon Joo Kim; Fanbo Deng; Michael S. Brown

2011-01-01

246

Hyperspectral Image Exploitation SBIR Phase 1 Final Report.  

National Technical Information Service (NTIS)

The overall objectives of Phase I were to carry out the necessary research and design and to develop the techniques needed to demonstrate the feasibility of an overall concept and approach to the development of a hyperspectral image processing system. The...

1992-01-01

247

Bayesian Hyperspectral Image Segmentation With Discriminative Class Learning  

Microsoft Academic Search

This paper introduces a new supervised technique to segment hyperspectral images: the Bayesian segmentation based on discriminative classification and on multilevel logistic (MLL) spatial prior. The approach is Bayesian and exploits both spectral and spatial information. Given a spectral vector, the posterior class probability distribution is modeled using multinomial logistic regression (MLR) which, being a discriminative model, allows to learn

Janete S. Borges; José M. Bioucas-Dias; Andre R. S. Marcal

2011-01-01

248

Exploiting spatial information in semi-supervised hyperspectral image segmentation  

Microsoft Academic Search

We present a new semi-supervised segmentation algorithm suited to hyperspectral images, which takes full advantage of the spectral and spatial information available in the scenes. We mainly focus on problems involving very few labeled samples and a larger set of unlabeled samples. A multinomial logistic regression (MLR) is used to model the posterior class probability distributions, whereas a multilevel logistic

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

2010-01-01

249

Notes on reconstructing the data cube in hyperspectral image processing  

Microsoft Academic Search

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

Charles Byrne

250

Application of Multiple-Instance Learning for Hyperspectral Image Analysis  

Microsoft Academic Search

Multiple-instance learning (MIL) is a learning paradigm used for learning a target concept in the presence of noise or with an uncertainty in target information including class labels. Due to the difficult situations in which hyperspectral images (HSIs) are collected, research in this area is extremely relevant and directly applicable. In the following, an MIL framework is proposed for target

Jeremy Bolton; Paul Gader

2011-01-01

251

Classification based Marker Selection for Watershed Transform of Hyperspectral Images  

Microsoft Academic Search

A new method for segmentation and classification of hyper-spectral images is proposed. The method is based on a pixel-wise classification followed by selection of the most reliable classified pixels as markers for watershed segmentation. Furthermore, each marker defined from classification results is associated with a class label. By assigning the class label of each marker to all the pixels within

Yuliya Tarabalka; Jocelyn Chanussot; Jon Atli Benediktsson

2009-01-01

252

Portable hyperspectral imager for assessment of skin disorders: preliminary measurements  

NASA Astrophysics Data System (ADS)

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

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

2005-04-01

253

Hyperspectral imaging for detecting pathogens grown on agar plates  

Microsoft Academic Search

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.

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

2007-01-01

254

Genetic algorithm based reference bands selection in hyperspectral image compression  

Microsoft Academic Search

In this paper, we propose an algorithm for reference bands selection in hyperspectral image (HSI) compression. In HSI compression, many algorithms need to select the reference bands, but all those algorithms uniformly select the reference bands. The uniform selection method isn't optimal, so we propose a genetic algorithm (GA) based reference band selection method to get lower prediction residual. The

Yushi Chen; Aili Wang; Ye Zhang

2008-01-01

255

NIR DLP® hyperspectral imaging system for medical applications  

Microsoft Academic Search

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

Eleanor Wehner; Abhas Thapa; Edward Livingston; Karel Zuzak

2011-01-01

256

CROP CLASSIFICATION WITH HYPERSPECTRAL DATA OF THE HYMAP SENSOR USING DIFFERENT FEATURE EXTRACTION TECHNIQUES  

Microsoft Academic Search

A method is presented to extract a subset of individual bands from a hyperspectral dataset. The method seeks to maximize the information content in a given subset by analyzing the covariances between individual bands of the original dataset. Subsequently, the method is used to reduce the dimensionality of hyperspectral image data prior to maximum likelihood classification. The classification results are

Sebastian Mader; Michael Vohland; Thomas Jarmer; Markus Casper

257

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

NASA Astrophysics Data System (ADS)

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

Zhou, Mandi; Shu, Jiong; Chen, Zhigang

2010-08-01

258

Hyperspectral imaging in a LabVIEW environment  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging has traditionally required sophisticated software and powerful computers. In this paper, we describe an elegant PC-based system that maps multiple fluorescent signatures simultaneously. We present color image examples of the spectral topography of biological materials that exhibit as many as 40 distinct spectral fingerprints. Acquisitions and data processing occur close to real time. Unique coding simplifies memory management and data storage functions and provides accelerated image retrieval and interpretation.

Lerner, Jeremy M.; Drake, Lewis A.

1999-05-01

259

The use of hyperspectral imaging (HSI) in wound healing  

NASA Astrophysics Data System (ADS)

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

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

2014-03-01

260

Hyperspectral imaging in the operating room: what a surgeon wants  

NASA Astrophysics Data System (ADS)

Visualization is the key to surgery, but limiting one's "vision" to visible light images received by the human eye ignores a lot of available data. Imaging technology such as hyperspectral and infrared imaging can greatly expand the amount and type of information available to the surgeon. We propose several areas in which this type of technology can be useful in medicine, paying particular attention to the way in which this technology might be best integrated into current operating room setups.

Best, Sara L.

2012-02-01

261

An adaptive OPD and dislocation prediction used characteristic of interference pattern for interference hyperspectral image compression  

Microsoft Academic Search

According to the imaging principle and characteristic of LASIS (Large Aperture Static Interference Imaging Spectrometer), we discovered that the 3D (three dimensional) image sequences formed by different interference pattern frames, which were formed in the imaging process of LASIS Interference hyperspectral image, had much stronger correlation than the original interference hyperspectral image sequences, either in 2D (two dimensional) spatial domain

Jia Wen; Caiwen Ma; Penglang Shui

2011-01-01

262

Characterisation methods for the hyperspectral sensor HySpex at DLR's calibration home base  

NASA Astrophysics Data System (ADS)

The German Aerospace Center's (DLR) Remote Sensing Technology Institute (IMF) operates a laboratory for the characterisation of imaging spectrometers. Originally designed as Calibration Home Base (CHB) for the imaging spectrometer APEX, the laboratory can be used to characterise nearly every airborne hyperspectral system. Characterisation methods will be demonstrated exemplarily with HySpex, an airborne imaging spectrometer system from Norsk Elektro Optikks A/S (NEO). Consisting of two separate devices (VNIR-1600 and SWIR-320me) the setup covers the spectral range from 400 nm to 2500 nm. Both airborne sensors have been characterised at NEO. This includes measurement of spectral and spatial resolution and misregistration, polarisation sensitivity, signal to noise ratios and the radiometric response. The same parameters have been examined at the CHB and were used to validate the NEO measurements. Additionally, the line spread functions (LSF) in across and along track direction and the spectral response functions (SRF) for certain detector pixels were measured. The high degree of lab automation allows the determination of the SRFs and LSFs for a large amount of sampling points. Despite this, the measurement of these functions for every detector element would be too time-consuming as typical detectors have 105 elements. But with enough sampling points it is possible to interpolate the attributes of the remaining pixels. The knowledge of these properties for every detector element allows the quantification of spectral and spatial misregistration (smile and keystone) and a better calibration of airborne data. Further laboratory measurements are used to validate the models for the spectral and spatial properties of the imaging spectrometers. Compared to the future German spaceborne hyperspectral Imager EnMAP, the HySpex sensors have the same or higher spectral and spatial resolution. Therefore, airborne data will be used to prepare for and validate the spaceborne system's data.

Baumgartner, Andreas; Gege, Peter; Köhler, Claas; Lenhard, Karim; Schwarzmaier, Thomas

2012-09-01

263

Tongue fissure extraction and classification using hyperspectral imaging technology.  

PubMed

Tongue fissures, an important feature on the tongue surface, may be pathologically related to some diseases. Most existing tongue fissure extraction methods use tongue images captured by traditional charge coupled device cameras. However, these conventional methods cannot be used for an accurate analysis of the tongue surface due to limited information from the images. To solve this, a hyperspectral tongue imager is used to capture tongue images instead of a digital camera. New algorithms for automatic tongue fissure extraction and classification, based on hyperspectral images, are presented. Both spectral and spatial information of the tongue surface is used to segment the tongue body and extract tongue fissures. Then a classification algorithm based on a hidden Markov model is used to classify tongue fissures into 12 typical categories. Results of the experiment show that the new method has good performance in terms of the classification rates of correctness. PMID:20389998

Li, Qingli; Wang, Yiting; Liu, Hongying; Sun, Zhen; Liu, Zhi

2010-04-10

264

Unattended imaging sensors  

Microsoft Academic Search

Imaging sensor systems address a broad range of needs, in both the military and commercial sectors, and must meet a demanding set of requirements. The unattended imaging sensor application places particularly stressing demands on the technology. Unattended imaging sensors collect data from a broad field of regard, process the information, and transmit it to the observer or to other sensors

Raymond S. Balcerak

2000-01-01

265

Parallel hyperspectral image processing on distributed multicluster systems  

NASA Astrophysics Data System (ADS)

Computationally efficient processing of hyperspectral image cubes can be greatly beneficial in many application domains, including environmental modeling, risk/hazard prevention and response, and defense/security. As individual cluster computers often cannot satisfy the computational demands of emerging problems in hyperspectral imaging, there is a growing need for distributed supercomputing using multicluster systems. A well-known manner of obtaining speedups in hyperspectral imaging is to apply data parallel approaches, in which commonly used data structures (e.g., the image cubes) are being scattered among the available compute nodes. Such approaches work well for individual compute clusters, but--due to the inherently large wide-area communication overheads--these are generally not applied in distributed multi-cluster systems. Given the nature of many algorithmic approaches in hyperspectral imaging, however, and due to the increasing availability of high-bandwidth optical networks, wide-area data parallel execution may well be a feasible acceleration approach. This paper discusses the wide-area data parallel execution of two realistic and state-of-the-art algorithms for endmember extraction in hyperspectral unmixing applications: automatic morphological endmember extraction and orthogonal subspace projection. It presents experimental results obtained on a real-world multicluster system, and provides a feasibility analysis of the applied parallelization approaches. The two parallel algorithms evaluated in this work had been developed before for single-cluster execution, and were not changed. Because no further implementation efforts were required, the proposed methodology is easy to apply to already available algorithms, thus reducing complexity and enhancing standardization.

Liu, Fangbin; Seinstra, Frank J.; Plaza, Antonio

2011-01-01

266

Hyperspectral image classification by collaboration of spatial and spectral information  

NASA Astrophysics Data System (ADS)

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

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

2009-07-01

267

Identification of inflammation sites in arthritic joints using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Inflammatory arthritic diseases have prevalence between 2 and 3% and may lead to joint destruction and deformation resulting in a loss of function. Patient's quality of life is often severely affected as the disease attacks hands and finger joints. Pathology involved in arthritis includes angiogenesis, hyper-vascularization, hyper-metabolism and relative hypoxia. We have employed hyperspectral imaging to study the hemodynamics of affected- and non-affected joints and tissue. Two hyperspectral, push-broom cameras were used (VNIR-1600, SWIR-320i, Norsk Elektro Optikk AS, Norway). Optical spectra (400nm - 1700nm) of high spectral resolution were collected from 15 patients with visible symptoms of arthritic rheumatic diseases in at least one joint. The control group consisted of 10 healthy individuals. Concentrations of dominant chromophores were calculated based on analytical calculations of light transport in tissue. Image processing was used to analyze hyperspectral data and retrieve information, e.g. blood concentration and tissue oxygenation maps. The obtained results indicate that hyperspectral imaging can be used to quantify changes within affected joints and surrounding tissue. Further improvement of this method will have positive impact on diagnosis of arthritic joints at an early stage. Moreover it will enable development of fast, noninvasive and noncontact diagnostic tool of arthritic joints

Paluchowski, Lukasz A.; Milanic, Matija; Bjorgan, Asgeir; Grandaunet, Berit; Dhainaut, Alvilde; Hoff, Mari; Randeberg, Lise L.

2014-03-01

268

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

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

269

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

NASA Astrophysics Data System (ADS)

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.

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

2008-05-01

270

Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.

Pölönen, I.; Saari, H.; Kaivosoja, J.; Honkavaara, E.; Pesonen, L.

2013-10-01

271

Pansharpening of hyperspectral images: a critical analysis of requirements and assessment on simulated PRISMA data  

NASA Astrophysics Data System (ADS)

In this paper, pansharpening methods suitable for the spatial enhancement of hyperspectral images are critically discussed and assessed on simulated data from the upcoming PRISMA mission, featuring a panchromatic camera mounted on the hyperspectral payload. Since most fusion techniques are limited to the fusion of multispectral (MS) images with panchromatic (Pan) images, the focus shall be on the extension of such methods towards hyperspectral (HS) images. In particular, the impact of the bandwidth of Pan on fusion performances will be analyzed and discussed.

Aiazzi, Bruno; Alparone, Luciano; Baronti, Stefano; Garzelli, Andrea; Selva, Massimo

2013-10-01

272

Hyperspectral Image Compression Employing a Model of Anomalous Pixels  

Microsoft Academic Search

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

Barbara Penna; Tammam Tillo; Enrico Magli; Gabriella Olmo

2007-01-01

273

New-Styled System Based on Hyperspectral Imaging  

Microsoft Academic Search

A new-styled molecular hyperspectral imaging system (MHIS) based on acousto-optic tunable filter (AOTF) was introduced in this paper. This system consists of a Charge-coupled Device (CCD) camera, microscopy, AOTF, and a RF driver. Real-time images are obtained both at multiple, continuous wavelengths and at relatively narrow spectral bandwidths to generate a 3D data including one spectral and two spatial dimensions.

Yana Guan; Qingli Li; Hongying Liu; Liang Xu; Ziqiang Zhu

2011-01-01

274

Hyperspectral image compression using SPIHT based on DCT and DWT  

Microsoft Academic Search

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

Haiping Wei; Baojun Zhao; Peikun He

2007-01-01

275

Hyperspectral image lossless compression using DSC and 2-D CALIC  

Microsoft Academic Search

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

Xueping Yan; Jiaji Wu

2010-01-01

276

Study on the Methods of Detecting Cucumber Downy Mildew Using Hyperspectral Imaging Technology  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging technology, which can integrate the advantages of spectral detection and image detection, meets the need of detecting the cucumber diseases fast and nondestructively. In this paper, hyperspectral imaging technology is adopted to detect the cucumber downy mildew fast and nondestructively. Firstly, hyperspectral images of cucumber leaves infected downy mildew are acquired by the hyperspectral image acquisition system. And optimum wavelengths are collected by the principal component analysis to get the featured images. Then the image fusion technology is adopted to combine collected images with the featured images to form new images by pixel-level image fusion. Finally, the methods of the image enhancement, binarization, corrosion and dilatation treatments are carried out, so the cucumber downy mildew is detected. The result shows that the accuracy rate of the algorithm for detecting cucumber disease can reach nearly 90%. Studies have shown that hyperspectral imaging technology can be used to detect cucumber downy mildew.

Tian, Youwen; Zhang, Lin

277

Hyperspectral imaging of bruises in the SWIR spectral region  

NASA Astrophysics Data System (ADS)

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.

Randeberg, Lise L.; Hernandez-Palacios, Julio

2012-02-01

278

Hyperspectral laser-induced autofluorescence imaging of dental caries  

NASA Astrophysics Data System (ADS)

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

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

2012-02-01

279

Effect of temperature on onboard calibration reference material for spectral response function retrieval of the hyperspectral sensor of HISUI-SWIR spectral case  

NASA Astrophysics Data System (ADS)

HISUI (Hyperspectral Imager SUIte) is the next Japanese earth observation sensor, which consists of hyperspectral and multispectral sensors. The hyperspectral sensor is an imaging spectrometer with the VNIR (400-970nm) and the SWIR (900-2500nm) spectral channels. Spatial resolution is 30 m with swath width of 30km. The spectral resolution will be better than 10nm in the VNIR and 12.5nm in the SWIR. The multispectral sensor has four VNIR spectral bands with spatial resolution of 5m and swath width of 90km. HISUI will be installed in ALOS-3 that is an earth observing satellite by JAXA. It will be launched in FY 2015. This paper is concerned with the effect of temperature on onboard calibration reference material (NIST SRM2065) for spectral response functions (SRFs) retrieval of the hyperspectral sensor. Since the location and intensity of absorption features are sensitive to material temperature, the estimated center wavelength and bandwidth of the SRFs may include the uncertainty. Therefore, it is necessary to estimate the deviation of the wavelength and the bandwidth broadening of the SRFs when the material temperature changes. In this paper we describe the evaluation of uncertainty of the SRF's parameters retrieval and show some simulation's results.

Tatsumi, Kenji; Tanii, Jun; Harada, Hisashi; Kawanishi, Toneo; Sakuma, Fumihiro; Inada, Hitomi; Kawashima, Takahiro; Iwasaki, Akira

2012-09-01

280

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

NASA Astrophysics Data System (ADS)

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

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

2014-03-01

281

Recent Developments in Hyperspectral Imaging for Assessment of Food Quality and Safety  

PubMed Central

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.

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

2014-01-01

282

Efficient Compression of Hyperspectral Images by Grouping around Lines  

NASA Astrophysics Data System (ADS)

In this paper we present a new lossless algorithm for compression of the signals from advanced hyperspectral infrared sensors onboard sun- and geo-synchronous environmental satellites. At each stage, our compression algorithm achieves an efficient grouping of channel data points around a relatively small number of 1-dimensional lines in a large dimensional data space. The parametrization of these lines is very efficient, which leads to efficient descriptions of data points via adaptive clustering. Using one full day's worth (24 h) of global hyperspectral data obtained by the AQUA-EOS Atmospheric Infrared Sounder (AIRS), the mean ratio of compression attainable by the method is shown to be ~= 3.7 to 1.

Gladkova, I.; Nalli, N.; Wolf, W.; Zhou, L.; Goldberg, M.; Roytman, L.

2006-10-01

283

An optimized hybrid encode based compression algorithm for hyperspectral image  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

284

Design of FPGA ICA for hyperspectral imaging processing  

NASA Astrophysics Data System (ADS)

The remote sensing problem which uses hyperspectral imaging can be transformed into a blind source separation problem. Using this model, hyperspectral imagery can be de-mixed into sub-pixel spectra which indicate the different material present in the pixel. This can be further used to deduce areas which contain forest, water or biomass, without even knowing the sources which constitute the image. This form of remote sensing allows previously blurred images to show the specific terrain involved in that region. The blind source separation problem can be implemented using an Independent Component Analysis algorithm. The ICA Algorithm has previously been successfully implemented using software packages such as MATLAB, which has a downloadable version of FastICA. The challenge now lies in implementing it in a form of hardware, or firmware in order to improve its computational speed. Hardware implementation also solves insufficient memory problem encountered by software packages like MATLAB when employing ICA for high resolution images and a large number of channels. Here, a pipelined solution of the firmware, realized using FPGAs are drawn out and simulated using C. Since C code can be translated into HDLs or be used directly on the FPGAs, it can be used to simulate its actual implementation in hardware. The simulated results of the program is presented here, where seven channels are used to model the 200 different channels involved in hyperspectral imaging.

Nordin, Anis; Hsu, Charles C.; Szu, Harold H.

2001-03-01

285

Cosine error for a class of hyperspectral irradiance sensors  

NASA Astrophysics Data System (ADS)

The cosine error of a class of in situ hyperspectral irradiance sensors largely applied for ocean colour investigations has been characterized for both in-air and in-water measurements. Results for in-air measurements indicate a slight wavelength dependence of the cosine error with differences up to 2% in the 412 nm to 865 nm spectral interval at 65° zenith angle (i.e. the angle of incident irradiance with respect to the normal axis of the irradiance collector). However, the dependence of the cosine error on the zenith angle is generally quite marked and significantly varies from radiometer to radiometer with values ranging from -5% up to +7% at 65°. Additionally, apart from the expected increase in the cosine error with the angle of incidence, in-air measurements generally indicate an irregular deviation from the ideal cosine response near the normal angle of incidence. A more pronounced increase in the cosine error is generally observed when radiometers are operated in water with respect to in air.

Mekaoui, S.; Zibordi, G.

2013-06-01

286

Hyperspectral image classification based on NMF Features Selection Method  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

287

CMOS image sensors  

Microsoft Academic Search

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

A. El Gamal; H. Eltoukhy

2005-01-01

288

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

NASA Astrophysics Data System (ADS)

Ocean color remote-sensing systems require highly accurate calibration (<0.5%) for accurate retrieval of water properties. This accuracy is typically achieved by vicarious calibration which is done by comparing the atmospherically corrected remote-sensing data to accurate estimates of the water-leaving radiance. Here we present a new method for vicarious calibration of a hyperspectral sensor that exploits shadows cast by trees and cliffs along coastlines. Hyperspectral Ocean PHILLS imagery was acquired over East Sound and adjacent waters around Orcas Island, Washington, USA, in August, 1998, in concert with field data collection. To vicariously calibrate the PHILLS data, a method was developed employing pixel pairs in tree-shaded and adjacent unshadowed waters, which utilizes the sky radiance dominating the shaded pixel as a known calibration target. Transects extracted from East Sound imagery were calibrated and validated with field data (RMSE = 0.00033 sr-1), providing validation of this approach for acquiring calibration-adjustment data from the image itself.

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

2006-11-01

289

Real-time data processor for the COMPASS hyperspectral sensor system  

NASA Astrophysics Data System (ADS)

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

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

2003-12-01

290

Real-time data processor for the COMPASS hyperspectral sensor system  

NASA Astrophysics Data System (ADS)

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

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

2004-01-01

291

Performance impact of parameter tuning on the CCSDS-123 lossless multi- and hyperspectral image compression standard  

NASA Astrophysics Data System (ADS)

Multi-spectral and hyperspectral image data payloads have large size and may be challenging to download from remote sensors. To alleviate this problem, such images can be effectively compressed using specially designed algorithms. The new CCSDS-123 standard has been developed to address onboard lossless coding of multi-spectral and hyperspectral images. The standard is based on the fast lossless algorithm, which is composed of a causal context-based prediction stage and an entropy-coding stage that utilizes Golomb power-of-two codes. Several parts of each of these two stages have adjustable parameters. CCSDS-123 provides satisfactory performance for a wide set of imagery acquired by various sensors; but end-users of a CCSDS-123 implementation may require assistance to select a suitable combination of parameters for a specific application scenario. To assist end-users, this paper investigates the performance of CCSDS-123 under different parameter combinations and addresses the selection of an adequate combination given a specific sensor. Experimental results suggest that prediction parameters have a greater impact on the compression performance than entropy-coding parameters.

Augé, Estanislau; Sánchez, Jose Enrique; Kiely, Aaron; Blanes, Ian; Serra-Sagristà, Joan

2013-01-01

292

Correction of axial optical aberrations in hyperspectral imaging systems  

NASA Astrophysics Data System (ADS)

In hyper-spectral imaging systems with a wide spectral range, axial optical aberrations may lead to a significant blurring of image intensities in certain parts of the spectral range. Axial optical aberrations arise from the indexof- refraction variations that is dependent on the wavelength of incident light. To correct axial optical aberrations the point-spread function (PSF) of the image acquisition system needs to be identified. We proposed a multiframe joint blur identification and image restoration method that maximizes the likelihood of local image energy distributions between spectral images. Gaussian mixture model based density estimate provides a link between corresponding spatial information shared among spectral images so as to find and restore the image edges via a PSF update. Model of the PSF was assumed to be a linear combination of Gaussian functions, therefore the blur identification process had to find only the corresponding scalar weights of each Gaussian function. Using the identified PSF, image restoration was performed by the iterative Richardson-Lucy algorithm. Experiments were conducted on four different biological samples using a hyper-spectral imaging system based on acousto-optic tunable filter in the visible spectral range (0.55 - 1.0 ?m). By running the proposed method, the quality of raw spectral images was substantially improved. Image quality improvements were quantified by a measure of contrast and demonstrate the potential of the proposed method for the correction of axial optical aberrations.

Špiclin, Žiga; Pernuš, Franjo; Likar, Boštjan

2011-02-01

293

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

PubMed

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

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

2010-05-01

294

Hyperspectral imaging for detecting pathogens grown on agar plates  

NASA Astrophysics Data System (ADS)

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

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

2007-09-01

295

[Lossless compression of hyperspectral image for space-borne application].  

PubMed

In order to resolve the difficulty in hardware implementation, lower compression ratio and time consuming for the whole hyperspectral image lossless compression algorithm based on the prediction, transform, vector quantization and their combination, a hyperspectral image lossless compression algorithm for space-borne application was proposed in the present paper. Firstly, intra-band prediction is used only for the first image along the spectral line using a median predictor. And inter- band prediction is applied to other band images. A two-step and bidirectional prediction algorithm is proposed for the inter-band prediction. In the first step prediction, a bidirectional and second order predictor proposed is used to obtain a prediction reference value. And a improved LUT prediction algorithm proposed is used to obtain four values of LUT prediction. Then the final prediction is obtained through comparison between them and the prediction reference. Finally, the verification experiments for the compression algorithm proposed using compression system test equipment of XX-X space hyperspectral camera were carried out. The experiment results showed that compression system can be fast and stable work. The average compression ratio reached 3.05 bpp. Compared with traditional approaches, the proposed method could improve the average compression ratio by 0.14-2.94 bpp. They effectively improve the lossless compression ratio and solve the difficulty of hardware implementation of the whole wavelet-based compression scheme. PMID:23156795

Li, Jin; Jin, Long-xu; Li, Guo-ning

2012-08-01

296

Sublingual vein extraction algorithm based on hyperspectral tongue imaging technology.  

PubMed

Among the parts of the human tongue surface, the sublingual vein is one of the most important ones which may have pathological relationship with some diseases. To analyze this information quantitatively, one primitive work is to extract sublingual veins accurately from tongue body. In this paper, a hyperspectral tongue imaging system instead of a digital camera is used to capture sublingual images. A hidden Markov model approach is presented to extract the sublingual veins from the hyperspectral sublingual images. This approach characterizes the spectral correlation and the band-to-band variability using a hidden Markov process, where the model parameters are estimated by the spectra of the pixel vectors forming the observation sequences. The proposed algorithm, the pixel-based sublingual vein segmentation algorithm, and the spectral angle mapper algorithm are tested on a total of 150 scenes of hyperspectral sublingual veins images to evaluate the performance of the new method. The experimental results demonstrate that the proposed algorithm can extract the sublingual veins more accurately than the traditional algorithms and can perform well even in a noisy environment. PMID:21030208

Li, Qingli; Wang, Yiting; Liu, Hongying; Guan, Yana; Xu, Liang

2011-04-01

297

Miniaturized hyperspectral imager calibration and UAV flight campaigns  

NASA Astrophysics Data System (ADS)

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.

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

2013-10-01

298

Hyperspectral optical imaging of two different species of lepidoptera  

PubMed Central

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

2011-01-01

299

Interactive visualization of hyperspectral images of historical documents.  

PubMed

This paper presents an interactive visualization tool to study and analyze hyperspectral images (HSI) of historical documents. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for old and fragile documents. The NAN is actively capturing HSI of historical documents for use in a variety of tasks related to the analysis and management of archival collections, from ink and paper analysis to monitoring the effects of environmental aging. To assist their work, we have developed a comprehensive visualization tool that offers an assortment of visualization and analysis methods, including interactive spectral selection, spectral similarity analysis, time-varying data analysis and visualization, and selective spectral band fusion. This paper describes our visualization software and how it is used to facilitate the tasks needed by our collaborators. Evaluation feedback from our collaborators on how this tool benefits their work is included. PMID:20975185

Kim, Seon Joo; Zhuo, Shaojie; Deng, Fanbo; Fu, Chi-Wing; Brown, Michael S

2010-01-01

300

Hyperspectral optical imaging of two different species of lepidoptera  

NASA Astrophysics Data System (ADS)

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

Medina, José Manuel; Nascimento, Sérgio Miguel Cardoso; Vukusic, Pete

2011-05-01

301

Tunable narrow-band filter for LWIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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.

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

2000-04-01

302

Edge-Based Prediction for Lossless Compression of Hyperspectral Images  

Microsoft Academic Search

We present two algorithms for error prediction in lossless compression of hyperspectral images. The algorithms are context-based and non-linear, and use a one-band look-ahead, thus requiring a minimal storage buffer. The first algorithm (NPHI) predicts the pixel in the current band based on the information from its context. Prediction contexts are defined based on the neighboring causal pixels in the

Sushil K. Jain; Donald A. Adjeroh

2007-01-01

303

Hyperspectral image compression using three-dimensional significance tree splitting  

Microsoft Academic Search

A three-dimensional (3D) wavelet coder based on 3D significance tree splitting is proposed for hyperspectral image compression. 3D discrete wavelet transform (DWT) is applied to explore the spatial and spectral correlations. Then the 3D significance tree structure is constructed in 3D wavelet domain, and wavelet coefficients are encoded via 3D significance tree splitting. This proposed algorithm does not need to

Jing Huang; Rihong Zhu; Jianxin Li; Yong He

2007-01-01

304

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

305

Spatial and spectral performance of a chromotomosynthetic hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

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

Bostick, Randall L.; Perram, Glen P.

2012-03-01

306

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

PubMed

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

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

2012-11-01

307

Computationally efficient strategies to perform anomaly detection in hyperspectral images  

NASA Astrophysics Data System (ADS)

In remote sensing, hyperspectral sensors are effectively used for target detection and recognition because of their high spectral resolution that allows discrimination of different materials in the sensed scene. When a priori information about the spectrum of the targets of interest is not available, target detection turns into anomaly detection (AD), i.e. searching for objects that are anomalous with respect to the scene background. In the field of AD, anomalies can be generally associated to observations that statistically move away from background clutter, being this latter intended as a local neighborhood surrounding the observed pixel or as a large part of the image. In this context, many efforts have been put to reduce the computational load of AD algorithms so as to furnish information for real-time decision making. In this work, a sub-class of AD methods is considered that aim at detecting small rare objects that are anomalous with respect to their local background. Such techniques not only are characterized by mathematical tractability but also allow the design of real-time strategies for AD. Within these methods, one of the most-established anomaly detectors is the RX algorithm which is based on a local Gaussian model for background modeling. In the literature, the RX decision rule has been employed to develop computationally efficient algorithms implemented in real-time systems. In this work, a survey of computationally efficient methods to implement the RX detector is presented where advanced algebraic strategies are exploited to speed up the estimate of the covariance matrix and of its inverse. The comparison of the overall number of operations required by the different implementations of the RX algorithms is given and discussed by varying the RX parameters in order to show the computational improvements achieved with the introduced algebraic strategy.

Rossi, Alessandro; Acito, Nicola; Diani, Marco; Corsini, Giovanni

2012-11-01

308

Non-destructive hyperspectral imaging of quarantined Mars Returned Samples  

NASA Astrophysics Data System (ADS)

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

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

309

Intercomparison and Validation of Techniques for Spectral Unmixing of Hyperspectral Images: A Planetary Case Study  

Microsoft Academic Search

As the volume of hyperspectral data for planetary exploration increases, efficient yet accurate algorithms are decisive for their analysis. In this paper, the capability of spectral unmixing for analyzing hyperspectral images from Mars is investigated. For that purpose, we consider the Russell megadune observed by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and the High-Resolution Imaging Science Experiment (HiRISE)

Xavier Ceamanos; Sylvain Doute; Bin Luo; Frédéric Schmidt; Gwenaël Jouannic; Jocelyn Chanussot

2011-01-01

310

Low-complexity hyperspectral image compression algorithm based on bit plan transform  

Microsoft Academic Search

A new hyperspectral image compression algorithm based on bit plane transform is proposed. The main idea of the bit plane transform is to decompose the hyperspectral image into a series of bi-level images which can be compressed more efficient. The gray code and band sequence optimization techniques are adopted to improve the compression performance in the preprocess stage. The main

HengShu Liu; Liping Zhang; LianQing Huang

2003-01-01

311

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

Microsoft Academic Search

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

Zheng Zhou; Jian Liu; Jinwen Tian

2006-01-01

312

Hyperspectral image segmentation using a cooperative nonparametric approach  

NASA Astrophysics Data System (ADS)

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

Taher, Akar; Chehdi, Kacem; Cariou, Claude

2013-10-01

313

Detection of early plant stress responses in hyperspectral images  

NASA Astrophysics Data System (ADS)

Early stress detection in crop plants is highly relevant, but hard to achieve. We hypothesize that close range hyperspectral imaging is able to uncover stress related processes non-destructively in the early stages which are invisible to the human eye. We propose an approach which combines unsupervised and supervised methods in order to identify several stages of progressive stress development from series of hyperspectral images. Stress of an entire plant is detected by stress response levels at pixel scale. The focus is on drought stress in barley (Hordeum vulgare). Unsupervised learning is used to separate hyperspectral signatures into clusters related to different stages of stress response and progressive senescence. Whereas all such signatures may be found in both, well watered and drought stressed plants, their respective distributions differ. Ordinal classification with Support Vector Machines (SVM) is used to quantify and visualize the distribution of progressive stages of senescence and to separate well watered from drought stressed plants. For each senescence stage a distinctive set of most relevant Vegetation Indices (VIs) is identified. The method has been applied on two experiments involving potted barley plants under well watered and drought stress conditions in a greenhouse. Drought stress is detected up to ten days earlier than using NDVI. Furthermore, it is shown that some VIs have overall relevance, while others are specific to particular senescence stages. The transferability of the method to the field is illustrated by an experiment on maize (Zea mays).

Behmann, Jan; Steinrücken, Jörg; Plümer, Lutz

2014-07-01

314

SPECTRAL SMILE CORRECTION IN CRISM HYPERSPECTRAL IMAGES  

NASA Astrophysics Data System (ADS)

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is affected by a common artifact in "push-broom" sensors, the so-called "spectral smile". As a consequence, both central wavelength and spectral width of the spectral response vary along the across-track dimension, thus giving rise to a shifting and smoothing of spectra (see Fig. 1 (left)). In fact, both effects are greater for spectra on the edges, while they are minimum for data acquired by central detectors, the so-called "sweet spot". The prior artifacts become particularly critical for Martian observations which contain steep spectra such as CO2 ice-rich polar images. Fig. 1 (right) shows the horizontal brightness gradient which appears in every band corresponding to a steep portion of spectra. The correction of CRISM spectral smile is addressed using a two-step method which aims at modifying data sensibly in order to mimic the optimal CRISM response. First, all spectra, which are previously interpolated by cubic splines, are resampled to the "sweet spot" wavelengths in order to overcome the spectra shift. Secondly, the non-uniform spectral width is overcome by mimicking an increase of spectral resolution thanks to a spectral sharpening. In order to minimize noise, only bands particularly suffering from smile are selected. First, bands corresponding to the outliers of the Minimum Noise Transformation (MNF) eigenvector, which corresponds to the MNF band related to smile (MNF-smile), are selected. Then, a spectral neighborhood ?i, which takes into account the local spectral convexity or concavity, is defined for every selected band in order to maximize spectral shape preservation. The proposed sharpening technique takes into account both the instrument parameters and the observed spectra. First, every reflectance value belonging to a ?i is reevaluated by a sharpening which depends on a ratio of the spectral width of the current detector and the "sweet spot" one. Then, the optimal degree of sharpening for every ?i is determined thanks to a loop of sharpening procedures, which is assessed by the examination of an estimation of the smile energy (the MNF-smile eigenvalue). As a matter of fact, a higher sharpening is performed on ?i as long as the smile energy decreases. Experiments on CRISM data show remarkable results regarding the decrease of smile energy (up to 80%) and the spectral shape preservation. In fact, initial smile-affected spectra do no longer show shifting nor smoothing (see Fig. 2). Line-averaged spectra and band 155 of FRT5AE3_07 showing spectral smile effects Line-averaged spectra and band 155 of smile-corrected FRT5AE3_07

Ceamanos, X.; Doute, S.

2009-12-01

315

Image mapping spectrometry: a novel hyperspectral platform for rapid snapshot imaging  

NASA Astrophysics Data System (ADS)

This paper presents the Image Mapping Spectrometry a new snapshot hyperspectral imaging platform for variety of applications. These applications span from remote sensing and surveillance use to life cell microscopy implementations and medical diagnostics. The IMS replaces the camera in a digital imaging system, allowing one to add parallel spectrum acquisition capability and to maximize the signal collection (> 80%). As such the IMS allows obtaining full spectral information in the image scene instantaneously at real time imaging rates. Presented implemention provides 350x350x48 datacube (x,y,?) and spectral sampling of 2 to 6 nm in visible spectral range but is easily expandable to larger cube dimensions and other spectral ranges. The operation of the IMS is based on redirecting image zones through the use of a custom-fabricated optical element known as an image mapper. The image mapper is a complex custom optical component comprised of high quality, thin mirror facets with unique 2D tilts. These mirror facets reorganize the original image onto a single large format CCD sensor to create optically "dark" regions between adjacent image lines. The full spectrum from each image line is subsequently dispersed into the void regions on the CCD camera. This mapping method provides a one-to-one correspondence between each voxel in the datacube and pixel on the CCD camera requiring only a simple and fast remapping algorithm. This paper provides fundamentals of IMS operations and describes an example design. Preliminary imaging results for gas detection acquired at 3 frames / second, for 350x350x48 data cubes are being presented. Real time unmixing of spectral signatures is also being discussed. Finally paper draws perspective of future directions and system potential for infrared imaging.

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

2011-05-01

316

MIST Final Report: Multi-sensor Imaging Science and Technology  

SciTech Connect

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

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

2008-03-15

317

Parallel ICA and its hardware implementation in hyperspectral image analysis  

NASA Astrophysics Data System (ADS)

Advances in hyperspectral images have dramatically boosted remote sensing applications by providing abundant information using hundreds of contiguous spectral bands. However, the high volume of information also results in excessive computation burden. Since most materials have specific characteristics only at certain bands, a lot of these information is redundant. This property of hyperspectral images has motivated many researchers to study various dimensionality reduction algorithms, including Projection Pursuit (PP), Principal Component Analysis (PCA), wavelet transform, and Independent Component Analysis (ICA), where ICA is one of the most popular techniques. It searches for a linear or nonlinear transformation which minimizes the statistical dependence between spectral bands. Through this process, ICA can eliminate superfluous but retain practical information given only the observations of hyperspectral images. One hurdle of applying ICA in hyperspectral image (HSI) analysis, however, is its long computation time, especially for high volume hyperspectral data sets. Even the most efficient method, FastICA, is a very time-consuming process. In this paper, we present a parallel ICA (pICA) algorithm derived from FastICA. During the unmixing process, pICA divides the estimation of weight matrix into sub-processes which can be conducted in parallel on multiple processors. The decorrelation process is decomposed into the internal decorrelation and the external decorrelation, which perform weight vector decorrelations within individual processors and between cooperative processors, respectively. In order to further improve the performance of pICA, we seek hardware solutions in the implementation of pICA. Until now, there are very few hardware designs for ICA-related processes due to the complicated and iterant computation. This paper discusses capacity limitation of FPGA implementations for pICA in HSI analysis. A synthesis of Application-Specific Integrated Circuit (ASIC) is designed for pICA-based dimensionality reduction in HSI analysis. The pICA design is implemented using standard-height cells and aimed at TSMC 0.18 micron process. During the synthesis procedure, three ICA-related reconfigurable components are developed for the reuse and retargeting purpose. Preliminary results show that the standard-height cell based ASIC synthesis provide an effective solution for pICA and ICA-related processes in HSI analysis.

Du, Hongtao; Qi, Hairong; Peterson, Gregory D.

2004-04-01

318

FIVQ algorithm for interference hyper-spectral image compression  

NASA Astrophysics Data System (ADS)

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

319

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

PubMed

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

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

2009-05-01

320

Evaluation of a hyperspectral image database for demosaicking purposes  

NASA Astrophysics Data System (ADS)

We present a study on the the applicability of hyperspectral images to evaluate color filter array (CFA) design and the performance of demosaicking algorithms. The aim is to simulate a typical digital still camera processing pipe-line and to compare two different scenarios: evaluate the performance of demosaicking algorithms applied to raw camera RGB values before color rendering to sRGB, and evaluate the performance of demosaicking algorithms applied on the final sRGB color rendered image. The second scenario is the most frequently used one in literature because CFA design and algorithms are usually tested on a set of existing images that are already rendered, such as the Kodak Photo CD set containing the well-known lighthouse image. We simulate the camera processing pipe-line with measured spectral sensitivity functions of a real camera. Modeling a Bayer CFA, we select three linear demosaicking techniques in order to perform the tests. The evaluation is done using CMSE, CPSNR, s-CIELAB and MSSIM metrics to compare demosaicking results. We find that the performance, and especially the difference between demosaicking algorithms, is indeed significant depending if the mosaicking/demosaicking is applied to camera raw values as opposed to already rendered sRGB images. We argue that evaluating the former gives a better indication how a CFA/demosaicking combination will work in practice, and that it is in the interest of the community to create a hyperspectral image dataset dedicated to that effect.

Larabi, Mohamed-Chaker; Süsstrunk, Sabine

2011-01-01

321

Semi-supervised hyperspectral image segmentation using regionalized stochastic watershed  

NASA Astrophysics Data System (ADS)

Stochastic watershed is a robust method to estimate the probability density function (pdf) of contours of a multi-variate image using MonteCarlo simulations of watersheds from random markers. The aim of this paper is to propose a stochastic watershed-based algorithm for segmenting hyperspectral images using a semi-supervised approach. Starting from a training dataset consisting in a selection of representative pixel vectors of each spectral class of the image, the algorithm calculate for each class a membership probability map (MPM). Then, the MPM of class k is considered as a regionalized density function which is used to simulate the random markers for the MonteCarlo estimation of the pdf of contours of the corresponding class k. This pdf favours the spatial regions of the image spectrally close to the class k. After applying the same technique to each class, a series of pdf are obtained for a single image. Finally, the pdf's can be segmented hierarchically either separately for each class or after combination, as a single pdf function. In the results, besides the generic spatial-spectral segmentation of hyperspectral images, the interest of the approach is also illustrated for target segmentation.

Angulo, Jesús; Velasco-Forero, Santiago

2010-04-01

322

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

Microsoft Academic Search

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

Lele Su; Xiangnan Liu; Xiaodong Wang; Nan Jiang

323

Early detection of apple bruises on different background colors using hyperspectral imaging  

Microsoft Academic Search

The potentials of a hyperspectral imaging system were investigated for early detection of bruises on ‘McIntosh’ apples. A hyperspectral imaging system was developed based on a spectral region between 400 and 1000nm. Partial least squares method and stepwise discrimination analysis were used for data dimensionality reduction and selecting the effective wavelengths. Three effective wavelengths in the near infrared region (750,

Gamal ElMasry; Ning Wang; Clément Vigneault; Jun Qiao; Adel ElSayed

2008-01-01

324

Automated threshold determination for a family of matched subspace filters for target detection in hyperspectral images  

Microsoft Academic Search

The detection of subpixel targets in hyperspectral images is complicated by interference arising from other background materials. This paper describes three target detection algorithms implemented in Data Fusion Corporation's HYPERTOOLS, a suite of hyperspectral image analysis tools. The matched subspace filter (MSF) is a generalized likelihood ratio test designed to detect target signatures while suppressing known interference signatures in a

Lewis Reynolds; Woody Kober

2005-01-01

325

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

Microsoft Academic Search

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.

Santiago Velasco-Forero; J. Angulo

2009-01-01

326

Modified Fisher's linear discriminant analysis for hyperspectral image dimension reduction and classification  

Microsoft Academic Search

In this paper, we present a modified Fisher's linear discriminant analysis (FLDA) to hyperspectral remote sensing image dimension reduction and classification. The basic idea of FLDA is to design an optimal transform which can maximize the ratio of between-class scatter matrix to within-class scatter matrix. The practical difficulty of applying the FLDA to hyperspectral images includes the unavailability of enough

Qian Du

2006-01-01

327

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

Microsoft Academic Search

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

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

2012-01-01

328

Next generation miniature simultaneous multi-hyperspectral imaging systems  

NASA Astrophysics Data System (ADS)

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

Hinnrichs, Michele; Gupta, Neelam

2014-03-01

329

Single aflatoxin contaminated corn kernel analysis with fluorescence hyperspectral image  

NASA Astrophysics Data System (ADS)

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.

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

2010-04-01

330

Mine and vehicle detection in hyperspectral image data: waveband selection  

NASA Astrophysics Data System (ADS)

Hyperspectral (HS) data contains spectral response information that provides detailed descriptions of an object. These new sensor data are useful in automatic target recognition applications. However, such high-dimensional data introduces problems due to the curse of dimensionality, the need to reduce the number of features (? responses) used to accommodate realistic small training set sizes, and the need to employ discriminatory features and still achieve good generalization (comparable training and test set performance). HS sensors produce high-dimensional data; this is characterized by a training set size (Ni) per class that is less than the number of input features (NF). A new high-dimensional generalized discriminant (HDGD) feature extraction algorithm and a new modified branch and bound (MBB) feature selection algorithm are described and compared to other feature reduction methods for two HS target detection applications (mine and vehicle detection). Both space and spectral parameters are adapted. A new blob-coloring hit-miss transform is introduced.

Casasent, David P.; Chen, Xue-Wen

2003-09-01

331

ASIC image sensors  

Microsoft Academic Search

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

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

1990-01-01

332

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

NASA Astrophysics Data System (ADS)

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

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

2007-04-01

333

Affinity propagation for large size hyperspectral image classification  

NASA Astrophysics Data System (ADS)

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

Soltani, Mariem; Chehdi, Kacem; Cariou, Claude

2013-10-01

334

[Special decorrelation technique used for DWT-based hyperspectral image compression].  

PubMed

Hyperspectral images are massive data consisting of hundreds of spectral bands and have been used in a large number of applications. With growth of spectral resolution and spatial resolution of hyperspectral data, data size increases rapidly. How to effectively compress hyperspectral image becomes a key problem that affects the development and popularization of hyperspectral image. Recently, DWT-based methods have been proved promising for hyperspectral image. But their performances are restricted because it is difficult for them to efficiently take advantage of the various properties of hyperspectral image. For the traditional wavelet transform, the specific properties of hyperspectral images are basically utilized by corresponding to characteristics of wavelet coefficients. So the present paper proposes a new DWT-based method using decorrelation technique according to the spectral characters of hyperspectral image. Block predictive coding is designed to remove the spectral correlation as well as spatial correlation simultaneously and is applied into the DWT-based method. Firstly, hyperspectral image is divided into several image blocks. The bands in a single block possess high spectral correlation. Afterwards, it is deduced that bands of a single block tend to be proportional in altitudes. Bands prediction, which is done in the range of each block respectively, is designed according to this and others characteristics of hyperspectral images. Finally, reference bands of block prediction and the deviation data obtained after block prediction are compressed by 2D-DWT algorithm and 3D-DWT algorithm respectively. Experiment results indicate that compared with the well known techniques the proposed method can significantly improve SNR and PSNR performance, even to 4.2 dB (compared with AT-3DSPIHT algorithm). And the code efficiency at low bit rates is also competitive. PMID:20707162

Chen, Lei; Zhang, Xiao-Lin; Liu, Rong-Ke; Lei, Zhi-Dong

2010-06-01

335

Hyperspectral image compression using SPIHT based on DCT and DWT  

NASA Astrophysics Data System (ADS)

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 Modular Imaging Spectrometer) image and the performance of this algorithm was compared with that of 2D-SPIHT. The results show that the performance of 3D-SPIHT based on DCT and DWT is much better than that of 2D-SPIHT and the quality of the reconstructed images is satisfying.

Wei, Haiping; Zhao, Baojun; He, Peikun

2007-11-01

336

Simulation of hyperspectral radiance images with quantification of adjacency effects over rugged scenes  

NASA Astrophysics Data System (ADS)

Simulation of hyperspectral remote sensing images can be applied to the generation of simulated datasets and validation of the data processing algorithms, as well as to deriving the ground reflectance of rugged areas from remote sensing images. Realistic simulations require capabilities dealing with rugged scenes and accurate modeling of the adjacency effects. Estimation of adjacency effects remains a difficulty because of the complex phenomena induced by rugged terrains. To find the optimal tradeoff between the accuracy and the computation time, this paper describes a method of simulating hyperspectral radiance images over rugged scenes with quantitative estimation of the adjacency effects under the assumptions of Lambertian surface and single scattering. In the quantification of adjacency effects, molecular/aerosol scattering phase functions, topographic features and ground heterogeneity are taken into account. Radiance images are generated by several sequential processing steps, which create atmospheric effects using a radiative transfer model, model topographic effects based on digital elevation model and simulate the instrument response function of a given sensor. The method has been applied to the complete scene simulation and the validity of various assumptions is checked using experimental datasets from Hyperion.

Zhao, Huijie; Jiang, Cheng; Jia, Guorui; Tao, Dongxing

2013-12-01

337

Compression of hyperspectral images with discriminant features enhanced  

NASA Astrophysics Data System (ADS)

In this paper, we propose two compression methods for hyperspectral images with discriminant features enhanced. Generally, when hyperspectral images are compressed with conventional image compression algorithms, which mainly minimize mean squared errors, discriminant features of the original data may not be well preserved since they may not be necessarily large in energy. In this paper, we propose two compression methods that do preserve the discriminant information. In the first method, we enhanced the discriminant features and then compressed the enhanced data using conventional image compression algorithms such as 3D JPEG 2000. In the second method, we applied a feature extraction method and extracted the discriminantly dominant feature vectors. By examining the dominant feature vectors, we determined the discriminant usefulness of each spectral band. Based on these findings, we determined the bit allocation of each spectral band assuming 2D compression methods are used. Experiments show that the proposed methods effectively preserved the discriminant information and yielded improved classification accuracies compared to existing compression algorithms.

Lee, Chulhee; Choi, Euisun; Jeong, Taeuk; Lee, Sangwook; Lee, Jonghwa

2010-10-01

338

A Method of Particle Swarm Optimized SVM Hyper-spectral Remote Sensing Image Classification  

NASA Astrophysics Data System (ADS)

Support Vector Machine (SVM) has been proved to be suitable for classification of remote sensing image and proposed to overcome the Hughes phenomenon. Hyper-spectral sensors are intrinsically designed to discriminate among a broad range of land cover classes which may lead to high computational time in SVM mutil-class algorithms. Model selection for SVM involving kernel and the margin parameter values selection which is usually time-consuming, impacts training efficiency of SVM model and final classification accuracies of SVM hyper-spectral remote sensing image classifier greatly. Firstly, based on combinatorial optimization theory and cross-validation method, particle swarm algorithm is introduced to the optimal selection of SVM (PSSVM) kernel parameter ? and margin parameter C to improve the modelling efficiency of SVM model. Then an experiment of classifying AVIRIS in India Pine site of USA was performed for evaluating the novel PSSVM, as well as traditional SVM classifier with general Grid-Search cross-validation method (GSSVM). And then, evaluation indexes including SVM model training time, classification Overall Accuracy (OA) and Kappa index of both PSSVM and GSSVM are all analyzed quantitatively. It is demonstrated that OA of PSSVM on test samples and whole image are 85% and 82%, the differences with that of GSSVM are both within 0.08% respectively. And Kappa indexes reach 0.82 and 0.77, the differences with that of GSSVM are both within 0.001. While the modelling time of PSSVM can be only 1/10 of that of GSSVM, and the modelling. Therefore, PSSVM is an fast and accurate algorithm for hyper-spectral image classification and is superior to GSSVM.

Liu, Q. J.; Jing, L. H.; Wang, L. M.; Lin, Q. Z.

2014-03-01

339

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

NASA Astrophysics Data System (ADS)

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.

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

2013-05-01

340

Surgical and clinical needs for DLP hyperspectral imaging  

NASA Astrophysics Data System (ADS)

Surgical technology advances slowly and only when there is overwhelming need for change. Change is resisted by surgeons and is made hard by FDA rules that inhibit innovation. There is a pressing need to improve surgeon's visualization of the operative field during laparoscopic surgery to minimize the risk for significant injury that can occur when surgeons are operating around delicate, hidden structures. We propose to use a Digital Light Processor-based hyperspectral imaging system to assist an operating surgeon's ability to see through tissues and identify otherwise hidden structures such as bile ducts during laparoscopic cholecystectomy.

Livingston, Edward H.

2010-02-01

341

GPU implementation issues for fast unmixing of hyperspectral images  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

342

Classification of fecal contamination on leafy greens by hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

343

PGK algorithm in hyperspectral image compression  

Microsoft Academic Search

this paper presents compression algorithm of multispectral image. At first multispectral image is converted to N-dimensional space vector, and then using PGK clustering algorithm to cluster compression, Experiments show that this algorithm with the detection vegetation can achieve the purpose of high compression ratio, low algorithm complexity, restored

Xu Su; Tan Xue; Chen Shanxue

2011-01-01

344

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

PubMed

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

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

2010-10-01

345

Requirements on optical sensors for quantitative definition of surface parameters multispectral - hyperspectral  

NASA Astrophysics Data System (ADS)

New sensors allow a significant progress in remote sensing from qualitative interpretation of data to quantitative assessment and characterisation of the status of surface targets and phenomena. Gathered knowledge of band positioning, bandwidth and number of spectral bands in optical remote sensing allowed to improve the physical characteristics of existing and future sensors: SPOT 4/5, MOMS 02/2P, IRS-1C, LANDSAT 7, hyperspectral sensors on EO-1 HRST and HYMAP/ARIES etc. Improvements in radiometric sensor calibration, atmospheric corrections and digital evaluation methodology widen the possibilities for quantitative analysis of the data for different applications.

Bodechtel, Johann

2001-01-01

346

Extended hyperspectral imaging system modeling and implementation for subpixel target detection  

NASA Astrophysics Data System (ADS)

For hyperspectral imaging system design and parameter trade-o research, an analytical model to simulate the remote sensing system has been developed and is in progress to be made available to the community. The analytical model includes scene, sensor and target characteristics, and also atmospheric features, background spectral statistics, sensor speci cations and target spectral statistics. The model is being implemented as a web-based application through an RIT-hosted website. Predicting system performance has been veri ed by real world data collected during the RIT SHARE 2012 collection and the data shows consistency with the simulated results on calibration tarps and grass. Also, subpixel target spectral statistics are predicted by this model. Some parameter trade-o examples are given and analyzed to explain the utility of this model.

Ding, Bo; Kerekes, John P.

2013-09-01

347

Potential roles of satellite hyperspectral IR sensors in monitoring greenhouse effects  

NASA Astrophysics Data System (ADS)

As we enter a new era of using satellite hyperspectral sensors for weather and other environmental applications, this paper discusses the applicability of using IR hyperspectral data for climate change monitoring; in particular, for quantifying the greenhouse effects. While broadband 1st order statistics quantify radiative forcings, the IR hyperspectral data provides a means of monitoring feedback processes. Radiative transfer modeling of the greenhouse effect is illustrated with examples: varying surface temperature, atmospheric temperature and water vapor. Three spectral greenhouse metrics are discussed: the difference between the surface emission and the outgoing longwave radiation (G), the surface-temperature normalized greenhouse effect (g) and vertical profile of cooling rate (C). Effects of changes in water vapor, clouds, carbon dioxide and methane are modeled and their potential observables identified.

Burke, Hsiao-hua; Snow, Bill; Farrar, Kris

2005-06-01

348

Detecting pits in tart cherries by hyperspectral transmission imaging  

NASA Astrophysics Data System (ADS)

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

Qin, Jianwei; Lu, Renfu

2004-11-01

349

Lossless compression of hyperspectral images using hybrid context prediction.  

PubMed

In this letter a new algorithm for lossless compression of hyperspectral images using hybrid context prediction is proposed. Lossless compression algorithms are typically divided into two stages, a decorrelation stage and a coding stage. The decorrelation stage supports both intraband and interband predictions. The intraband (spatial) prediction uses the median prediction model, since the median predictor is fast and efficient. The interband prediction uses hybrid context prediction. The hybrid context prediction is the combination of a linear prediction (LP) and a context prediction. Finally, the residual image of hybrid context prediction is coded by the arithmetic coding. We compare the proposed lossless compression algorithm with some of the existing algorithms for hyperspectral images such as 3D-CALIC, M-CALIC, LUT, LAIS-LUT, LUT-NN, DPCM (C-DPCM), JPEG-LS. The performance of the proposed lossless compression algorithm is evaluated. Simulation results show that our algorithm achieves high compression ratios with low complexity and computational cost. PMID:22453490

Liang, Yuan; Li, Jianping; Guo, Ke

2012-03-26

350

NIR DLP hyperspectral imaging system for medical applications  

NASA Astrophysics Data System (ADS)

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

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

2011-02-01

351

Hyperspectral imaging of UVR effects on fungal spectrum  

NASA Astrophysics Data System (ADS)

The present report evaluated ultraviolet radiation (UVR) effects on the spectral signature of mycotoxin producing fungus Aspergillus flavus (A. flavus). Ultraviolet radiation has long been used to reduce microbe contamination and to inactivate mold spores. In view of the known effects of UVR on microorganisms, and because certain spectral bands in the signature of some fungi may be in the UV range, it is important to know the maximum acceptable limit of UVR exposure that does not significantly alter the fungal spectral signature and affect detection accuracy. A visible-near-infrared (VNIR) hyperspectral imaging system using focal plane pushbroom scanning for high spatial and spectral resolution imaging was utilized to detect any changes. A. flavus cultures were grown for 5 days and imaged after intermittent or continuous UVR treatment. The intermittent group was treated at 1-minute intervals for 10 minutes, and VNIR images were taken after each UVR treatment. The continuous group was irradiated for 10 minutes and imaged before and after treatment. A control sample group did not undergo UVR treatment, but was also imaged at 1-minute intervals for 10 minutes in the same manner as the intermittent group. Before and after UVR treatment, mean fungal sample reflectance was obtained through spatial subset of the image along with standard deviation and pre- and post-treatment reflectance was compared for each sample. Results show significant difference between the reflectances of treated and control A. flavus cultures after 10 min of UV radiation. Aditionally, the results demonstrate that even lethal doses of UVR do not immediately affect the spectral signature of A. flavus cultures suggesting that the excitation UV light source used in the present experiment may be safe to use with the UV hyperspectral imaging system when exposure time falls below 10 min.

Hruska, Zuzana; Yao, Haibo; DiCrispino, Kevin; Brabham, Kori; Lewis, David; Beach, Jim; Brown, Robert L.; Cleveland, Thomas E.

2005-08-01

352

Spatially-Coherent Non-Linear Dimensionality Reduction and Segmentation of Hyper-Spectral Images (PREPRINT).  

National Technical Information Service (NTIS)

Non-linear dimensionality reduction and vector segmentation of hyper- spectral images is investigated in this letter. The proposed framework takes into account the nonlinear nature of high dimensional hyper-spectral images, and projects onto a lower dimen...

A. Mohan E. Bosch G. Sapiro

2006-01-01

353

Combined Hyperspatial and Hyperspectral Imaging Spectrometer Concept.  

National Technical Information Service (NTIS)

There is a user need for increasing spatial and spectral resolution in Earth Observation (EO) optical instrumentation. Higher spectral resolution will be achieved by the introduction of spaceborne imaging spectrometers. Higher spatial resolutions of 1 - 3...

I. Burke H. Zwick

1995-01-01

354

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

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

355

Assessment of quality parameters for a new-generation hyperspectral imager  

NASA Astrophysics Data System (ADS)

This work focuses on an assessment of quality parameters characterizing a hyperspectral image collected by a new-generation high-resolution sensor named Hyper-SIMGA, which is a spectrometer operating in the push-broom configuration. By resorting to Shannon's information theory, the concept of quality is related to the information conveyed to a user by the hyperspectral data, which can be objectively defined from both the signal-to-noise ratio (SNR) and the mutual information between the unknown noise-free digitized signal and the corresponding noise-affected observed digital samples. The estimation of the mutual information has been exploited by resorting to a lossless data compression of the dataset. In fact, the bit-rate achieved by the reversible compression process is a suitable approximation of the decorrelated data entropy, which takes into account both the contribution of the "observation" noise, i.e. information regarded as statistical uncertainty, whose relevance is null to a user, and the intrinsic information of hypothetically noise-free samples. Noise estimation can be obtained once a suitable parametric model of the noise, assumed to be possibly non-Gaussian, has been preliminarily determined. Noise amplitude has been assessed by means of two independent estimators relying on two automatic procedures based on a scatterplot method and a bit-plane algorithm. Noise autocorrelation has been taken into account on the three allowed directions of the available data-volume. Results are reported and discussed employing a hyperspectral image (768 spectral bands) recorded by the new Hyper-SIMGA imaging spectrometer.

Aiazzi, Bruno; Alparone, Luciano; Barducci, Alessandro; Baronti, Stefano; Guzzi, Donatella; Marcoionni, Paolo; Pippi, Ivan; Selva, Massimo

2007-10-01

356

SETA-Hyperspectral Imaging Spectrometer for Marco Polo mission.  

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

357

Design and Implementation of a Parallel Heterogeneous Algorithm for Hyperspectral Image Analysis Using HeteroMPI  

Microsoft Academic Search

The development of efficient techniques for transforming the massive volume of remotely sensed hyperspectral data collected on a daily basis into scientific understanding is critical for space-based Earth science and planetary exploration. Although most available parallel processing strategies for hyperspectral image analysis assume homogeneity in the computing platform, heterogeneous networks of computers represent a promising cost-effective solution expected to play

David Valencia; Alexey L. Lastovetsky; Antonio Plaza

2006-01-01

358

A new subspace discriminant analysis approach for supervised hyperspectral image classification  

Microsoft Academic Search

In this work, we present a new subspace discriminantanalysis classification algorithmfor remotelysensed hyperspectralimage data. Our motivation for including subspace projection as a distinctive feature of our work is to better model noise and mixed pixels present in hyperspectral images. Two different dimensionality reduction techniques are considered: principal component analysis (PCA) and the hyperspectral signal identification by minimum error (HySime) algorithm.

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

2011-01-01

359

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

Microsoft Academic Search

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

Wei Di; Melba M. Crawford

2011-01-01

360

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

Microsoft Academic Search

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

Emmanuel Christophe; Corinne Mailhes; Pierre Duhamel

2008-01-01

361

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

Microsoft Academic Search

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

Qian Du; Nicolas H. Younan

2008-01-01

362

An efficient macroblock-based diverse and flexible prediction modes selection for hyperspectral images coding  

Microsoft Academic Search

In this paper, an efficient macroblock-based diverse and flexible prediction modes selection algorithm is proposed for coding hyperspectral images, which is inspired by the prediction scheme of H264\\/AVC. Here, different modes are specified for the corresponding macroblocks (16×16 pixel regions of a band) of hyperspectral images other than the whole band image using only one reference band image for prediction.

Fan Zhao; Guizhong Liu; Xing Wang

2010-01-01

363

A compression algorithm of hyperspectral remote sensing image based on 3-D Wavelet transform and fractal  

Microsoft Academic Search

In this paper, the 3-D wavelet-fractal coding was used to compress the hyperspectral remote sensing image. The classical eight kinds of affine transformations in 2-D fractal image compression were generalized to nineteen for the 3-D fractal image compression. Hyperspectral image date cube was first translated by 3-D wavelet and then the 3-D fractal compression coding was applied to lowest frequency

Pan Wei; Zou Yi; Ao Lu

2008-01-01

364

Pathological leucocyte segmentation algorithm based on hyperspectral imaging technique  

NASA Astrophysics Data System (ADS)

White blood cells (WBC) are comparatively significant components in the human blood system, and they have a pathological relationship with some blood-related diseases. To analyze the disease information accurately, the most essential work is to segment WBCs. We propose a new method for pathological WBC segmentation based on a hyperspectral imaging system. This imaging system is used to capture WBC images, which is characterized by acquiring 1-D spectral information and 2-D spatial information for each pixel. A spectral information divergence algorithm is presented to segment pathological WBCs into four parts. In order to evaluate the performance of the new approach, K-means and spectral angle mapper-based segmental methods are tested in contrast on six groups of blood smears. Experimental results show that the presented method can segment pathological WBCs more accurately, regardless of their irregular shapes, sizes, and gray-values.

Guan, Yana; Li, Qingli; Wang, Yiting; Liu, Hongying; Zhu, Ziqiang

2012-05-01

365

Hyperspectral imaging applied to medical diagnoses and food safety  

NASA Astrophysics Data System (ADS)

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.)

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

2003-08-01

366

Hyperspectral image segmentation of the common bile duct  

NASA Astrophysics Data System (ADS)

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

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

2013-03-01

367

Hyperspectral imaging of structure and composition in atomically thin heterostructures.  

PubMed

Precise vertical stacking and lateral stitching of two-dimensional (2D) materials, such as graphene and hexagonal boron nitride (h-BN), can be used to create ultrathin heterostructures with complex functionalities, but this diversity of behaviors also makes these new materials difficult to characterize. We report a DUV-vis-NIR hyperspectral microscope that provides imaging and spectroscopy at energies of up to 6.2 eV, allowing comprehensive, all-optical mapping of chemical composition in graphene/h-BN lateral heterojunctions and interlayer rotations in twisted bilayer graphene (tBLG). With the addition of transmission electron microscopy, we obtain quantitative structure-property relationships, confirming the formation of interfaces in graphene/h-BN lateral heterojunctions that are abrupt on a micrometer scale, and a one-to-one relationship between twist angle and interlayer optical resonances in tBLG. Furthermore, we perform similar hyperspectral imaging of samples that are supported on a nontransparent silicon/SiO2 substrate, enabling facile fabrication of atomically thin heterostructure devices with known composition and structure. PMID:23841492

Havener, Robin W; Kim, Cheol-Joo; Brown, Lola; Kevek, Joshua W; Sleppy, Joel D; McEuen, Paul L; Park, Jiwoong

2013-08-14

368

Classification of oat and groat kernels using NIR hyperspectral imaging.  

PubMed

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

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

2013-01-15

369

Monitoring biofilm attachment on medical devices surfaces using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

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

2014-02-01

370

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

NASA Astrophysics Data System (ADS)

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

Näthe, Paul; Becker, Rolf

2014-05-01

371

Design and laboratory calibration of the compact pushbroom hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

The designed hyperspectral imaging system is composed of three main parts, that is, optical subsystem, electronic subsystem and capturing subsystem. And a three-dimensional "image cube" can be obtained through push-broom. The fore-optics is commercial-off-the-shelf with high speed and three continuous zoom ratios. Since the dispersive imaging part is based on Offner relay configuration with an aberration-corrected convex grating, high power of light collection and variable view field are obtained. The holographic recording parameters of the convex grating are optimized, and the aberration of the Offner configuration dispersive system is balanced. The electronic system adopts module design, which can minimize size, mass, and power consumption. Frame transfer area-array CCD is chosen as the image sensor and the spectral line can be binned to achieve better SNR and sensitivity without any deterioration in spatial resolution. The capturing system based on the computer can set the capturing parameters, calibrate the spectrometer, process and display spectral imaging data. Laboratory calibrations are prerequisite for using precise spectral data. The spatial and spectral calibration minimize smile and keystone distortion caused by optical system, assembly and so on and fix positions of spatial and spectral line on the frame area-array CCD. Gases excitation lamp is used in smile calibration and the keystone calculation is carried out by different viewing field point source created by a series of narrow slit. The laboratory and field imaging results show that this pushbroom hyperspectral imaging system can acquire high quality spectral images.

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

2009-11-01

372

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

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

373

Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging  

NASA Astrophysics Data System (ADS)

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

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

2005-12-01

374

Dimension Reduction and Pre-emphasis for Compression of Hyperspectral Images  

Microsoft Academic Search

\\u000a As the dimensionality of remotely sensed data increases, the need for efficient compression algorithms for hyperspectral images\\u000a also increases. However, when hyperspectral images are compressed with conventional image compression algorithms, which have\\u000a been developed to minimize mean squared errors, discriminant information necessary to distinguish among classes may be lost\\u000a during compression process. In this paper, we propose to enhance such

C. Lee; E. Choi; J. Choe; T. Jeong

2004-01-01

375

Compressed hyperspectral image sensing with joint sparsity reconstruction  

NASA Astrophysics Data System (ADS)

Recent compressed sensing (CS) results show that it is possible to accurately reconstruct images from a small number of linear measurements via convex optimization techniques. In this paper, according to the correlation analysis of linear measurements for hyperspectral images, a joint sparsity reconstruction algorithm based on interband prediction and joint optimization is proposed. In the method, linear prediction is first applied to remove the correlations among successive spectral band measurement vectors. The obtained residual measurement vectors are then recovered using the proposed joint optimization based POCS (projections onto convex sets) algorithm with the steepest descent method. In addition, a pixel-guided stopping criterion is introduced to stop the iteration. Experimental results show that the proposed algorithm exhibits its superiority over other known CS reconstruction algorithms in the literature at the same measurement rates, while with a faster convergence speed.

Liu, Haiying; Li, Yunsong; Zhang, Jing; Song, Juan; Lv, Pei

2011-09-01

376

Hyperspectral image compression using three-dimensional significance tree splitting  

NASA Astrophysics Data System (ADS)

A three-dimensional (3D) wavelet coder based on 3D significance tree splitting is proposed for hyperspectral image compression. 3D discrete wavelet transform (DWT) is applied to explore the spatial and spectral correlations. Then the 3D significance tree structure is constructed in 3D wavelet domain, and wavelet coefficients are encoded via 3D significance tree splitting. This proposed algorithm does not need to use ordered lists, moreover it has less complexity and requires lower fixed memory than 3D set partitioning in hierarchical trees (SPIHT) algorithm and 3D set partitioned embedded block (SPECK) algorithm. The numerical experiments on AVIRIS images show that the proposed algorithm outperforms 3D SPECK, and has a minor loss of performance compared with 3D SPIHT. This algorithm is suitable for simple hardware implementation and can be applied to progressive transmission.

Huang, Jing; Zhu, Rihong; Li, Jianxin; He, Yong

2007-07-01

377

Towards a colony counting system using hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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.

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

2012-02-01

378

Large area CMOS image sensors  

Microsoft Academic Search

CMOS image sensors, also known as CMOS Active Pixel Sensors (APS) or Monolithic Active Pixel Sensors (MAPS), are today the dominant imaging devices. They are omnipresent in our daily life, as image sensors in cellular phones, web cams, digital cameras, ... In these applications, the pixels can be very small, in the micron range, and the sensors themselves tend to

R. Turchetta; N. Guerrini; I. Sedgwick

2011-01-01

379

Lightning Imaging Sensor Data  

NSDL National Science Digital Library

Lightning and Atmospheric Electricity Research at the Global Hydrology and Climate Center provides these "GIF images showing a graphical representation of the Lightning Imaging Sensor orbit data for each day." The lightning distribution images are available by clicking on highlighted spots on a global map. Data are released one month at a time and currently include December 1997 to the present.

380

Standoff chemical D and Id with extended LWIR hyperspectral imaging spectroradiometer  

NASA Astrophysics Data System (ADS)

Standoff detection and identification (D and Id) of unknown volatile chemicals such as chemical pollutants and consequences of industrial incidents has been increasingly desired for first responders and for environmental monitoring. On site gas detection sensors are commercially available and several of them can even detect more than one chemical species, however only few of them have the capabilities of detecting a wide variety of gases at long and safe distances. The ABB Hyperspectral Imaging Spectroradiometer (MR-i), configured for gas detection detects and identifies a wide variety of chemical species including toxic industrial chemicals (TICs) and surrogates several kilometers away from the sensor. This configuration is called iCATSI for improved Compact Atmospheric Sounding Interferometer. iCATSI is a standoff passive system. The modularity of the MR-i platform allows optimization of the detection configuration with a 256 x 256 Focal Plane Array imager or a line scanning imager both covering the long wave IR atmospheric window up to 14 ?m. The uniqueness of its extended LWIR cut off enables to detect more chemicals as well as provide higher probability of detection than usual LWIR sensors.

Prel, Florent; Moreau, Louis; Lavoie, Hugo; Bouffard, François; Thériault, Jean-Marc; Vallieres, Christian; Roy, Claude; Dubé, Denis

2013-05-01

381

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

NASA Astrophysics Data System (ADS)

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.

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

2012-05-01

382

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

NASA Technical Reports Server (NTRS)

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

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

2005-01-01

383

Automatic Extraction of Closed Pixel Clusters for Target Cueing in Hyperspectral Images.  

National Technical Information Service (NTIS)

Traditional algorithms for automatic target cueing (ATC) in hyperspectral images, such as the RX algorithm, treat anomaly detection as a simple hypothesis testing problem. Each decision threshold gives rise to a different set of anomalous pixels. The clus...

D. W. Paglieroni D. E. Perkins

2001-01-01

384

Hyperspectral sensor for gypsum detection on monumental buildings  

NASA Astrophysics Data System (ADS)

A portable hyperspectral device (ASD-FieldSpec FR Pro) has been employed for the characterization of alterations affecting the marble facade of the Santa Maria Novella church (XIII cent.) in Florence (Italy). The ASD-FieldSpec FR Pro collects the reflectance spectra of a selected target area (about 1.5 cm2). The spectra of calcite, gypsum and other mineral phases commonly occurring on outdoor surfaces exposed to the urban atmosphere were collected and presented. The spectral features of alteration minerals (depth of reflectance minima) appear to be affected by grain size, phase abundance in addition to lightness (L*) of the target area. Notwithstanding these limitations, the spectra may be used for a qualitative screening of the alteration and, under reasonable assumptions, the reflectance band depth may be used also for quantitative estimation of phase abundance. The monitoring of the conservation state of outdoor surfaces is considered of fundamental importance to plan conservative interventions on historical buildings. Our results point out that portable hyperspectral instruments may be considered as powerful tools for characterizing historical surfaces in a nondestructive and noninvasive way.

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

2011-09-01

385

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

PubMed

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

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

2012-01-01

386

Hyperspectral imaging for the detection of retinal disease  

NASA Astrophysics Data System (ADS)

Hyperspectral imaging (HSI) shows great promise for the detection and classification of several diseases, particularly in the fields of "optical biopsy" as applied to oncology, and functional retinal imaging in ophthalmology. In this paper, we discuss the application of HSI to the detection of retinal diseases and technological solutions that address some of the fundamental difficulties of spectral imaging within the eye. HSI of the retina offers a route to non-invasively deduce biochemical and metabolic processes within the retina. For example it shows promise for the mapping of retinal blood perfusion using spectral signatures of oxygenated and deoxygenated hemoglobin. Compared with other techniques using just a few spectral measurements, it offers improved classification in the presence of spectral cross-contamination by pigments and other components within the retina. There are potential applications for this imaging technique in the investigation and treatment of the eye complications of diabetes, and other diseases involving disturbances to the retinal, or optic-nerve-head circulation. It is well known that high-performance HSI requires high signal-to-noise ratios (SNR) whereas the application of any imaging technique within the eye must cope with the twin limitations of the small numerical aperture provided by the entrance pupil to the eye and the limit on the radiant power at the retina. We advocate the use of spectrally-multiplexed spectral imaging techniques (the traditional filter wheel is a traditional example). These approaches enable a flexible approach to spectral imaging, with wider spectral range, higher SNRs and lower light intensity at the retina than could be achieved using a Fourier-transform (FT) approach. We report the use of spectral imaging to provide calibrated spectral albedo images of healthy and diseased retinas and the use of this data for screening purposes. These images clearly demonstrate the ability to distinguish between oxygenated and deoxygenated hemoglobin using spectral imaging and this shows promise for the early detection of various retinopathies.

Harvey, Andrew R.; Lawlor, Joanne; McNaught, Andrew I.; Williams, John W.; Fletcher-Holmes, David W.

2002-09-01

387

Automatic target recognition for hyperspectral imagery using high-order statistics  

Microsoft Academic Search

Due to recent advances in hyperspectral imaging sensors many subtle unknown signal sources that cannot be resolved by multispectral sensors can be now uncovered for target detection, discrimination, and identification. Because the information about such sources is generally not available, automatic target recognition (ATR) presents a great challenge to hyperspectral image analysts. Many approaches developed for ATR are based on

Hsuan Ren; Qian Du; Jing Wang; Chein-I Chang; JAMES O. JENSEN; JANET L. JENSEN

2006-01-01

388

Geometric Correction of PHI Hyperspectral Image without Ground Control Points  

NASA Astrophysics Data System (ADS)

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

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

2014-03-01

389

Semi-Supervised Marginal Fisher Analysis for Hyperspectral Image Classification  

NASA Astrophysics Data System (ADS)

The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification. In this paper, we proposed a novel method, called semi-supervised marginal Fisher analysis (SSMFA), to process HSI of natural scenes, which uses a combination of semi-supervised learning and manifold learning. In SSMFA, a new difference-based optimization objective function with unlabeled samples has been designed. SSMFA preserves the manifold structure of labeled and unlabeled samples in addition to separating labeled samples in different classes from each other. The semi-supervised method has an analytic form of the globally optimal solution, and it can be computed based on eigen decomposition. Classification experiments with a challenging HSI task demonstrate that this method outperforms current state-of-the-art HSI-classification methods.

Huang, H.; Liu, J.; Pan, Y.

2012-07-01

390

Hyperspectral image classification through bilayer graph-based learning.  

PubMed

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

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

2014-07-01

391

Hyperspectral image lossy-to-lossless compression using the 3D Embedded Zeroblock Coding alogrithm  

Microsoft Academic Search

In this paper, we propose a hyperspectral image lossy-to-lossless compression coder based on the Three-Dimensional Embedded ZeroBlock Coding (3D EZBC) algorithm. This coder adopts the three-dimensional integer wavelet packet transform with unitary scaling to decorrelate and the 3D EZBC algorithm without motion compensation to process bitplane zeroblock coding. For hyperspectral image compression using the 3D EZBC algorithm, the lossy-to-lossless compression

Ying Hou; Guizhong Liu

2008-01-01

392

Hyperspectral Image Zeroblock Coding Algorithm Based on 3D KLT and Wavelet Transform  

Microsoft Academic Search

Based on the characteristics of hyperspectral images, in this paper three-dimensional Set Partitioned Embedded Zero Block Coding (3D SPEZBC) algorithm based on spectral Karhunen-Loeve transform (KLT) and spatial wavelet transform (WT) for hyperspectral image compression is presented. This algorithm adopts ID KLT as spectral decorrelator and 2D WT as spatial decorrelator, the partitioning coding method based on the set representation

Ying Hou; Long Liu; Lei Yang; Xiaolong Kang

2010-01-01

393

SPATIALLY-COHERENT NON-LINEAR DIMENSIONALITY REDUCTION AND SEGMENTATION OF HYPERSPECTRAL IMAGES  

Microsoft Academic Search

Abstract— Non-linear dimensionality reduction and,vector segmentation of hyper-spectral images is investigated in this letter. The proposed framework,takes into account the nonlinear nature of high dimensional hyper-spectral images, and projects onto a lower dimensional space via a spatially-coherent locally linear embedding,technique. The spatial coherence is introduced by comparing individual pixels based on their local surrounding neighborhood structure. This neighborhood concept is

Anish Mohan; Guillermo Sapiro

394

Rapidly updated hyperspectral sounding and imaging data for severe storm prediction  

NASA Astrophysics Data System (ADS)

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

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

2013-09-01

395

Comparison of support vector machine-based processing chains for hyperspectral image classification  

NASA Astrophysics Data System (ADS)

Many different approaches have been proposed in recent years for remotely sensed hyperspectral image classification. Despite the variety of techniques designed to tackle the aforementioned problem, the definition of standardized processing chains for hyperspectral image classification is a difficult objective, which may ultimately depend on the application being addressed. Generally speaking, a hyperspectral image classification chain may be defined from two perspectives: 1) the provider's viewpoint, and 2) the user's viewpoint, where the first part of the chain comprises activities such as data calibration and geo-correction aspects, while the second part of the chain comprises information extraction processes from the collected data. The modules in the second part of the chain (which constitutes our main focus in this paper) should be ideally flexible enough to be accommodated not only to different application scenarios, but also to different hyperspectral imaging instruments with varying characteristics, and spatial and spectral resolutions. In this paper, we evaluate the performance of different processing chains resulting from combinations of modules for dimensionality reduction, feature extraction/ selection, image classification, and spatial post-processing. The support vector machine (SVM) classifier is adopted as a baseline due to its ability to classify hyperspectral data sets using limited training samples. A specific classification scenario is investigated, using a reference hyperspectral data set collected by NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Indian Pines region in Indiana, USA.

Rojas, Marta; Dópido, Inmaculada; Plaza, Antonio; Gamba, Paolo

2010-08-01

396

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

PubMed Central

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

Moroni, Monica; Dacquino, Carlo; Cenedese, Antonio

2012-01-01

397

An adaptive OPD and dislocation prediction used characteristic of interference pattern for interference hyperspectral image compression  

NASA Astrophysics Data System (ADS)

According to the imaging principle and characteristic of LASIS (Large Aperture Static Interference Imaging Spectrometer), we discovered that the 3D (three dimensional) image sequences formed by different interference pattern frames, which were formed in the imaging process of LASIS Interference hyperspectral image, had much stronger correlation than the original interference hyperspectral image sequences, either in 2D (two dimensional) spatial domain or in the spectral domain. We put this characteristic into image compression and proposed an adaptive OPD (optical path difference) and dislocation prediction algorithm for interference hyperspectral image compression. Compared the new algorithm proposed in this paper with Dual-Direction Prediction [1] proposed in 2009, lots of experimental results showed that the prediction error entropy of the new algorithm was much smaller. In the prediction step of lifting wavelet transform, this characteristic would also reduce the entropy of coefficients in high frequency significantly, which would be more advantageous for quantification coding [2].

Wen, Jia; Ma, Caiwen; Shui, Penglang

2011-09-01

398

CMOS image sensors for sensor networks  

Microsoft Academic Search

We report on two generations of CMOS image sensors with digital output fabricated in a 0.6 ?m CMOS process. The imagers embed\\u000a an ALOHA MAC interface for unfettered self-timed pixel read-out targeted to energy-aware sensor network applications. Collision\\u000a on the output is monitored using contention detector circuits. The image sensors present very high dynamic range and ultra-low\\u000a power operation. This

Eugenio Culurciello; Andreas G. Andreou

2006-01-01

399

Multisource Classification of Color and Hyperspectral Images Using Color Attribute Profiles and Composite Decision Fusion  

Microsoft Academic Search

In this work, we treat the problem of combined classification of a high spatial resolution color image and a lower spatial resolution hyperspectral image of the same scene. The problem is particularly challenging, since we aim for classification maps at the spatial resolution of the color image. Contextual information is obtained from the color image by introducing Color Attribute Profiles

Guy Thoonen; Zahid Mahmood; Stijn Peeters; Paul Scheunders

2012-01-01

400

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

Microsoft Academic Search

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

Yifan Zhang; Steve De Backer; Paul Scheunders

2009-01-01

401

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

NASA Astrophysics Data System (ADS)

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

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

2007-03-01

402

Nearest feature line embedding approach to hyperspectral image classification  

NASA Astrophysics Data System (ADS)

In this paper, a nearest feature line (NFL) embedding transformation is proposed for dimension reduction of hyperspectral image (HSI). Eigenspace projection approaches are generally used for feature extraction of HSI in remote sensing image classification. In order to improve the classification accuracy, the feature vectors of high dimensions are reduced to the low dimensionalities by the effective projection transformation. Similarly, the proposed NFL measurement is embedded into the transformation during the discriminant analysis stage instead of the matching stage. The class separability, neighborhood structure preservation, and NFL measurement are also simultaneously considered to find the effective and discriminating transformation in eigenspaces for image classification. The nearest neighbor classifier is used to show the discriminative performance. The proposed NFL embedding transformation is compared with several conventional state-of-the-art algorithms. It was evaluated by the AVIRIS data sets of Northwest Tippecanoe County. Experimental results have demonstrated that NFL embedding method is an effective transformation for dimension reduction in land cover classification of earth remote sensing.

Chang, Yang-Lang; Liu, Jin-Nan; Han, Chin-Chuan; Chen, Ying-Nong; Hsieh, Tung-Ju; Huang, Bormin

2012-10-01

403

Damage and quality assessment in wheat by NIR hyperspectral imaging  

NASA Astrophysics Data System (ADS)

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

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

2010-04-01

404

Multiplexed hyperspectral imaging and spectrometry using spatial light modulators  

NASA Astrophysics Data System (ADS)

The signal-noise-ratio, (SNR) is often the primary figure of merit when evaluating instrument performance. Multiplexing is one method employed in spectrometry and imaging to increase the magnitude of a signal received by a detector during a period of measurement. Optical masks employing Hadamard encoding matrices for multiplexing can be used to increase the SNR of some spectrometric and hyperspectrometric imaging measurements. A transmissive/opaque metal-etched optical mask and a reflective micro-mirror optical mask were used to investigate Hadamard transform (HT) multiplexing in spectrometric and hyperspectrometric imaging measurements. HT spectrometry (HTS) is a combination of dispersive and multiplexing spectrometry employing a one- dimensional (1D) optical mask. Dividing and folding the ID Hadamard, encoded optical mask used for spectral encoding in HT multiplexing spectrometry results in a two-dimensional (2D) mask that can be used for spatial encoding in Hadamard transform imaging (HTI). An etched, mechanically translated 2D optical mask and a digital micro-mirror array (DMA) encoded by a cyclic S255 matrix were successfully employed in the investigation of spatial multiplexing in HT Raman chemical mapping systems. Imaging heterogeneous liquid and solid samples using a 2D Hadamard encoded metal- etched moving mask was successfully demonstrated using conventional Raman spectroscopic equipment. The DMA is an improvement in Hadamard optical mask technology over moving optical masks and was successfully applied to visible Raman hyperspectral imaging of heterogeneous liquid and solid samples. The DMA was also successfully demonstrated to be effective for improving SNR in near- infrared (NIR) FITS as a 1D Hadamard encoded optical mask.

Deverse, Richard Andrew

1999-11-01

405

Development and characterization of a chromotomosynthetic hyperspectral imaging system  

NASA Astrophysics Data System (ADS)

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

Bostick, Randall L.

406

Quantitative vibrational imaging by hyperspectral stimulated Raman scattering microscopy and multivariate curve resolution analysis.  

PubMed

Spectroscopic imaging has been an increasingly critical approach for unveiling specific molecules in biological environments. Toward this goal, we demonstrate hyperspectral stimulated Raman loss (SRL) imaging by intrapulse 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

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

2013-01-01

407

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

PubMed Central

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.

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

2013-01-01

408

A potential hyperspectral remote sensing imager for water quality measurements  

NASA Astrophysics Data System (ADS)

Utilization of Pan Chromatic and Multi Spectral Remote Sensing Imagery is wide spreading and becoming an established business for commercial suppliers of such imagery like ISI and others. Some emerging technologies are being used to generate Hyper-Spectral imagery (HSI) by aircraft as well as other platforms. The commercialization of such technology for Remote Sensing from space is still questionable and depends upon several parameters including maturity, cost, market reception and many others. HSI can be used in a variety of applications in agriculture, urban mapping, geology and others. One outstanding potential usage of HSI is for water quality monitoring, a subject studied in this paper. Water quality monitoring is becoming a major area of interest in HSI due to the increase in water demand around the globe. The ability to monitor water quality in real time having both spatial and temporal resolution is one of the advantages of Remote Sensing. This ability is not limited only for measurements of oceans and inland water, but can be applied for drinking and irrigation water reservoirs as well. HSI in the UV-VNIR has the ability to measure a wide range of constituents that define water quality. Among the constituents that can be measured are the pigment concentration of various algae, chlorophyll a and c, carotenoids and phycocyanin, thus enabling to define the algal phyla. Other parameters that can be measured are TSS (Total Suspended Solids), turbidity, BOD (Biological Oxygen Demand), hydrocarbons, oxygen demand. The study specifies the properties of such a space borne device that results from the spectral signatures and the absorption bands of the constituents in question. Other parameters considered are the repetition of measurements, the spatial aspects of the sensor and the SNR of the sensor in question.

Zur, Yoav; Braun, Ofer; Stavitsky, David; Blasberger, Avigdor

2003-04-01