Target Manifolds for Hyperspectral Data Sets
Assessment of target detection limits in hyperspectral data
... Abstract: Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband ...the ...
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Strategies for MCR image analysis of large hyperspectral data sets
... The hyperspectral images from eight polymer spots, chosen from a 576 spot array because they exhibited chemical heterogene- ities, were analysed by ...image data, 256 256 pixels, over an area of 500 500 m m ...
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Strategies for MCR image analysis of large hyperspectral data-sets
... Supporting information may be found in the online version of this article. Keywords: time-of-flight secondary ion mass spectrometry; multivariate curve resolution; microarray; high-performance computing Introduction Many ...
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Hyperspectral-Augmented Target Tracking
... with hyperspectral imagery. The research effort evaluates hyperspectral data classification using fuzzy c-means and the self-organizing map clustering algorithms for remote identification of moving ...
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A Comparative Analysis of Hyperspectral Target Detection Algorithms in the Presence of Misregistered Data
... scanning hyperspectral imaging systems are capable of capturing accurate spatial and spectral information about a ...These data can be useful for detecting sub-pixel ...collect data from multiple ...
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Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets
... unstable manifolds of hyperbolic trajectories, this one involves evolving in time (forward in time for the un- stable manifold, backward in time for the stable manifold) a small initial segment of the manifold ...
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Subpixel Target Enhancement in Hyperspectral Images
... LMM is not guaranteed to produce non-negative abundances and hence there always exists a requirement of a more robust unmixing model such as constrained linear mixing model or a nonlinear mixing model may for obtaining ...
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Automatic Target Detection for Sparse Hyperspectral Images
... sensing data analysis and future challenges,” IEEE Geoscience and Remote Sensing Magazine , ...for hyperspectral image processing,” Remote Sensing of Environment, ...
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Determination of target detection limits in hyperspectral data using band selection and dimensionality reduction
... sensing data can be used for civil and military applications to robustly detect and classify target ...of hyperspectral data can compensate for the comparatively low spatial resolution, which ...
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Comparison of Hyperspectral Imagery Target Detection Algorithm Chains
... AFAR) graphs for the VF1 target that employed the ACORN atmospheric compensation algorithm and the OSP matched filter... ROC Curves and AFAR Data[r] ...
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A Review of Unsupervised Spectral Target Analysis for Hyperspectral Imagery
... spectral target defined as above what we are particularly interested in this paper from an aspect of sta- tistical signal processing are two types of spectral targets, one characterized by 2nd order sample ...
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Essays on hyperspectral image analysis: classification and target detection
... HSI target detection focuses on identifying very small objects sparsely scattered in a ...Typical target detection applications include mineral detection and military ...HSI target detection can be ...
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Hyperspectral Image Processing for Automatic Target Detection Applications
... resolved target materials, some pixels will be entirely filled by the material, some may be partially filled, and some may be in ...the data and manually label the pixels in the vicinity of a target ...
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Nonmonotone algorithm for minimization on closed sets with applications to minimization on Stiefel manifolds
... also called weighted orthogonal Procrustes problem (WOPP). Following [ 19 ], if m = n and C = I the case will be referred to as balanced, while if n < m, the case will be refereed to as unbalanced. The problem has ...
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Multiple target tracking based on sets of trajectories
... for sets of ...new target estimates at the current time step to estimated trajectories at the previous time ...labelled target states at two consecutive time steps based on the global hypotheses with ...
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Detection of pests and diseases in vegetable crops using hyperspectral sensing: a comparison of reflectance data for different sets of symptoms
... location data collected simultaneously, field level maps can be created by spatial interpolation among the sampling ...crop data can be used routinely with various spectral-matching type algorithms for ...
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Hyperspectral imaging using notions from type-2 fuzzy sets
... image data is imprecise in very different manners, from the very capture of the information (sensor noise) to the scene-bounded factors (perspective, illumination, ...imaging data, literature is also vast ...
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Comparative Assessment of Some Target Detection Algorithms for Hyperspectral Images
... IntroductIon Hyperspectral images portray a continuous spectrum of each pixel by capturing the data in several narrow and contiguous spectral ...a target of interest. On the contrary, target ...
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Matched filter stochastic background characterization for hyperspectral target detection
... the data, and handle the influence of target ...of target contamination through perfect exclusion and each technique improved the multivariate normality of the background to a level where small ...
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Target Detection of Hyperspectral Images Based on Their Fourier Spectral Features
... the hyperspectral sensor, research- ers in the remote sensing field are now able to extract ample spectral information to identify and discriminate between the spectral similarities of ...The hyperspectral ...
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