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检索条件"任意字段=Conference on Algorithms for Multispectral and Hyperspectral Imagery IV"

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Automated coregistration of MTI spectral bands

Automated coregistration of MTI spectral bands

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Theiler, J Galbraith, A Pope, P Ramsey, K Szymanski, J Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)0819444758

In the focal plane of a pushbroom imager, a linear array of pixels is scanned across the scene, building up the image one row at a time. For the multispectral Thermal Imager (MTI), each of fifteen different spectral bands has its own linear array. These arrays are pushed across the scene together, but since each band's array is at a different position on the focal plane, a separate image is produced for each band. The standard MTI data products (LEVEL1B-R-COREG and LEVEL1B_R_GEO) resample these separate images to a common grid and produce coregistered multispectral image cubes. The coregistration software employs a direct "dead reckoning" approach. Every pixel in the calibrated image is mapped to an absolute position on the surface of the earth, and these are resampled to produce an undistorted. coregistered image of the scene. To do this requires extensive information regarding the satellite position and pointing as a function of time, the precise configuration of the focal plane, and the distortion due to the optics. These must be combined with knowledge about the position and altitude of the target on the rotating ellipsoidal earth. We will discuss the direct approach to MTI coregistration, as well as more recent attempts to "tweak" the precision of the band-to-band registration using correlations in the imagery itself.

关键词： MTI multispectral imagery coregistration

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Efficient anomaly detection and discrimination for hyperspectral imagery

Efficient anomaly detection and discrimination for hyperspec...

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Ren, H Du, Q Jensen, J USA Edgewood Chem & Biol Ctr Aberdeen Proving Ground MD 21010 USA

ISBN: (纸本)0819444758

With the improvement of remote sensing sensor techniques, hyperspectral imagery is widely used today. Hundreds of frequency channels are used to collect radiance from the ground, which results in hundreds of co-registered images. How to process this huge amount of data is a great challenge, especially when no information of the image scene is available. Under this circumstance, anomaly detection becomes more difficult. Several methods are devoted to this problem, such as the well-known RX algorithm which takes advantage of the second-order statistics. In this paper we propose an effective algorithm for anomaly detection and discrimination based on high-order statistics. They include the normalized third central moment referred to as skewness and the normalized fourth central moment referred to as kurtosis, which measure the asymmetry and the flatness of a distribution respectively. The Gaussian distribution is completely determined by the first two statistics and has zero skewness and kurtosis, so these two indices tell us the deviation of a distribution from the Gaussian and are suitable to anomaly detection. The proposed algorithm can be generalized to use any high-order moment. The experimental results with AVIRIS data demonstrate that it can provide comparable detection results with low computational complexity.

关键词： anomaly detection high-order statistics hyperspectral imagery skewness kurtosis

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Performance analysis for CEM and OSP

Performance analysis for CEM and OSP

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Du, Q Ren, H Texas A&M Univ Dept Elect Engn & Comp Sci Kingsville TX 78363 USA

ISBN: (纸本)0819444758

We investigate two well-known techniques Constrained Energy Minimization (CEM) and Orthogonal Subspace Projection (OSP) and find out that they can be theoretically treated as equivalent methods when the noise is independent and identically distributed (i.i.d) and its variance is small enough compared to signals, i.e., SNR is large enough. In order to make the condition true, two approaches are applied to modify the OSP technique. One is to estimate the noise covariance matrix and whiten the noise to be i.i.d and unit variance. The other is to estimate sufficient undesired signatures such that the noise approaches i.i.d when the data is projected onto the orthogonal subspace of undesired signatures. The results using simulated and real data demonstrate that our conclusion on the relationship between the OSP and the CEM is correct. It will be instructive to algorithm selection in practical application.

关键词： Orthogonal Subspace Projection (OSP) Constrained Energy Minimization (CEM) detection classification hyperspectral imagery

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Utilizing spatial features in classifying high-resolution imagery data

Utilizing spatial features in classifying high-resolution im...

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Kiang, RK NASA Goddard Space Flight Ctr Greenbelt MD 20771 USA

ISBN: (纸本)0819444758

The spatial resolution of spaceborne instrument has increased substantially in the three decades since Landsat-1 was launched. Higher spatial resolution has made some applications possible. But it has also brought about new challenges in ground cover classification. At a resolution around 1 meter, vegetation often displays distinct textures. Hence texture may make differentiation among some cover types possible. Ikonos panchromatic and multispectral data are used to examine how spatial features improve classification accuracy. In this study, textural features are extracted from co-occurrence matrices, contextual features are derived from neighborhood properties, and maximum likelihood method is used for classifications. It is shown that for the test data both types of spatial features, and especially the contextual measures, can significantly improve the classification accuracies. Discrete wavelet transform is used to extract textural features for two types of vegetation. Transformed divergence, a measure of separability, is shown much enhanced when textural features are included.

关键词： spatial textural contextual Ikonos wavelet transform

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Automated material map generation using hyperspectral data: a case study using AVIRIS imagery

Automated material map generation using hyperspectral data: ...

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Lucey, P Winter, M Winter, E Steutel, D Univ Hawaii Manoa HIGP Honolulu HI 96822 USA

ISBN: (纸本)0819444758

The University of Hawaii's Efficient Materials Mapping program aims to automatically and rapidly produce material maps from hyperspectral scenes. The program combines an end-member determination algorithm and a material identification algorithm to produce context maps in real time without user intervention. The material identification algorithm is a combination of a spectral database and analytic code;each spectrum in the library augmented with computer readable diagnostic instructions. At present, the material library consists of over three hundred different spectra, generally geological materials from the USGS digital spectral library, however selected spectra from other libraries have been incorporated. Our method has been applied to an AVIRIS scene taken over Kaneohe bay, Hawaii. This scene contains large expanses of ocean, developed and undeveloped land, thus providing a good test bed for the program. The results of applying this methodology were verified by ground truth where possible by team equipped with a hand held spectrometer. Algorithm derived archetypical end-member locations were well matched well by the material identification database, however the end-member determination itself operated sub-optimally on this scene. These results will guide progress with respect to the continued development of this program.

关键词： AVIRIS N-FINDR hyperspectral mapping

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Proceedings of SPIE: algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

Proceedings of SPIE: Algorithms and Technologies for Multisp...

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algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

This Volume 4725 of the conference proceedings contains 59 papers. Topics discussed include band selection, endmember selection and feature extraction, emissive remote sensing applications, atmospheric characterization and correction, spectral applications and methodology, detection and identification, clustering and classification, multispectral thermal imager, atmospheric characterization and correction, imaging spectrometry projects and sharpening and compression.

关键词： Spectrum analysis

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Empirical radiometric correction of optical remote sensing imagery

Empirical radiometric correction of optical remote sensing i...

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conference on algorithms and Technologies for multispectral, hyperspectral, and Ultraspectral imagery VIII

作者： Palubinskas, G Müller, R Reinartz, P DLR German Aerosp Ctr D-82234 Wessling Germany

ISBN: (纸本)0819444758

We propose an empirical radiometric correction method for the effects, such as atmospheric effects and anisotropic reflection of the surface, in optical remote sensing data. These distortions are sensor viewing (scanning) angle dependent, thus they can be significant for data received from airborne sensors due to their wide field of view. The procedure is based solely on the digital image data and consists of several steps. First, the initial image region near nadir (minimal distortions) is clustered by an extended k-means algorithm, which automatically detects the clusters (surface types) in an image. Then, for each cluster an average line profile is calculated. These profiles (initially defined in a middle part of an image fine) are extrapolated to the whole line of an image by a polynomial approximation. Finally, from these polynomial functions the linear regression over all clusters is build using the radiative transfer equation, which allows the radiometric correction for each viewing angle in an image relative to the reference angle, usually nadir. The procedure is iterative, that is the correction is first performed for a narrow part around the initial region. Then the procedure is initialized with this newly corrected image region and repeated until the whole image is corrected. The experiments for data acquired by airborne multispectral scanner DAEDALUS AADS 1268 ATM show the effectiveness of the proposed method especially for the mosaicking and classification applications.

关键词： image-based atmospheric correction sensor viewing angle effects BRDF effects airborne scanner data

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Evolving feature extraction algorithms for hyperspectral and fused imagery

Evolving feature extraction algorithms for hyperspectral and...

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5th International conference on Information Fusion, FUSION 2002

作者： Brumby, Steven P. Pope, Paul A. Galbraith, Amy E. Szymanski, John J. Space and Remote Sensing Sciences Los Alamos National Laboratoty Mail Stop D436 Los Alamos NM 87545 United States

ISBN: (纸本)0972184414

hyperspectral imagery with moderate spatial resolution (/spl sim/30 m) presents an interesting challenge to feature extraction algorithm developers, as both spatial and spectral signatures may be required to identify the feature of interest. We describe a genetic programming software system, called GENIE, which augments the human scientist/analyst by evolving customized spatio-spectral feature extraction pipelines from training data provided via an intuitive, point-and-click interface. We describe recent work exploring geospatial feature extraction from hyperspectral imagery, and from a multi-instrument fused dataset. For hyperspectral imagery, we demonstrate our system on NASA Earth Observer 1 (EO-1) Hyperion imagery, applied to agricultural crop detection. We present an evolved pipeline, and discuss its operation. We also discuss work with multi-spectral imagery (DOE/NNSA multispectral Thermal Imager) fused with USGS digital elevation model (DEM) data, with the application of detecting mixed conifer forest. © 2002 Int. Soc. of Information Fusion.

关键词： Genetic programming

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Evolving feature extraction algorithms for hyperspectral and fused imagery

Evolving feature extraction algorithms for hyperspectral and...

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International conference on Information Fusion

作者： S.P. Brumby P.A. Pope A.E. Galbraith J.J. Szyinanski Space and Remote Sensing Sciences Los Alamos National Laboratory Los Alamos New Mexico USA Los Alamos National Laboratory Los Alamos NM US Space & Remote Sensing Sci. Los Alamos Nat. Lab. NM USA

关键词： Feature extraction hyperspectral imaging Pipelines Spatial resolution Genetic programming Software systems Humans Training data NASA Earth

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An automatic target recognition system for hyperspectral imagery using ORASIS

An automatic target recognition system for hyperspectral ima...

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conference on algorithms for multispectral, hyperspectral, and Ultraspectral imagery VII

作者： Gillis, D Palmadesso, P Bowles, J USN Res Lab Remote Sensing Div Washington DC 20375 USA

ISBN: (纸本)0819440760

We present an automatic target recognition system (ATR) for hyperspectral imagery. The system has been designed to use the output from ORASIS (the Optical Real-time Adaptive Spectral Identification System), a hyperspectral analysis package designed at the Naval Research Laboratory. The ATR system is capable of performing both target recognition (including subpixel identification) and anomaly detection, in near real-time and with no a priori scene knowledge. In this paper we discuss the algorithms we use in the ATR and include experimental results using the HYDICE Forest Radiance data set.

关键词： hyperspectral analysis ATR ORASIS

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