[PDF] Top 20 Robust adaptive target detection in hyperspectral imaging
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Robust adaptive target detection in hyperspectral imaging
... issue in detecting a target from an hyperspectral image relies on properly identifying the ...resulting detection schemes assume that the background distribution remains the same whether the ... Voir le document complet
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Adaptive target detection in hyperspectral imaging from two sets of training samples with different means
... Abstract In this paper, we consider local detection of a target in hyperspectral imaging and we assume that the spectral signature of interest is buried in a background ... Voir le document complet
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One-step Generalized Likelihood Ratio Test for Subpixel Target Detection in Hyperspectral Imaging
... For target detection purposes, many algorithms developed for other applications (such as radar or array processing) have been adapted to the hyperspectral ...the adaptive matched filter (AMF) ... Voir le document complet
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Non Zero Mean Adaptive Cosine Estimator and Application to Hyperspectral Imaging
... Mean Adaptive Cosine Estimator and Application to Hyperspectral Imaging Franc¸ois Vincent and Olivier Besson Abstract—The Adaptive Cosine Estimator (ACE) has become a popular detection ... Voir le document complet
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Generalized Likelihood Ratio Test for Modified Replacement Model in Hyperspectral Imaging Detection
... The first step of the processing aims at converting the raw measurements into a reflectance map, for which the unitary constraint on the abundances is supposed to be verified. To this end, we use the ELM technique, ... Voir le document complet
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Extended faint source detection in astronomical hyperspectral images
... Keeping in mind these specificities, we now describe previous work on detection in ...Works in HSI Detection When considering the detection of target spectra in ... Voir le document complet
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Detection of nonlinear mixtures using Gaussian processes: Application to hyperspectral imaging
... pixels in hyperspectral ...combined in a test statistics for which it is possible to estimate a detection threshold given a required probability of false ...a robust nonlinearity ... Voir le document complet
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Detection of nonlinear mixtures using Gaussian processes: Application to hyperspectral imaging
... pixels in hyperspectral ...combined in a test statistics for which it is possible to estimate a detection threshold given a required probability of false ...a robust nonlinearity ... Voir le document complet
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Active hyperspectral imaging of chemicals on surfaces
... Active hyperspectral imaging (HSI) is a promising technique for the detection of chemicals at standoff ...distances. In active HSI, a target is illuminated by a laser source at many ... Voir le document complet
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Detection of minor compounds in food powder using near infrared hyperspectral imaging
... using hyperspectral imaging, a PLA sample holder and the PLS regression method to study the light penetration depth in a wheat flour ...the detection depth, the maximum thickness of wheat ... Voir le document complet
129
Sub-pixel detection in hyperspectral imaging with elliptically contoured t-distributed background
... t Detection of a target with known spectral signature when this target may occupy only a fraction of the pixel is an important issue in hyperspectral ...a target induces a ... Voir le document complet
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Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection
... answering in an elegant way the questions raised in Section 2 ...concerns in particular the modeling of mu- sical rules and their rigorous structured organization in the system, which avoids ... Voir le document complet
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Adaptive robust optimization with applications in inventory and revenue management
... programs in static ...adequate in many realistic settings, a sequence of later papers (Ben-Tal et ...[14] in- troduced a setting in which a subset of the decision variables in a linear ... Voir le document complet
213
Online deconvolution for industrial hyperspectral imaging systems
... Fig. 6: Transient behavior model validation in non-stationary environment original image but deblurring is very limited. Better results are obtained when the 560 block size increases as shown in Figure 7(d) ... Voir le document complet
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Adaptive Robust Control Under Model Uncertainty
... problem in continuous time, that involves learning, has been done in [ KOZ14 ...follows. In Section 2 we briefly review some of the existing method- ologies of solving stochastic control problems ... Voir le document complet
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Detection of wheat root and straw in soil by use of NIR hyperspectral imaging spectroscopy and Partial Least Square discriminant analysis
... L.M. Dale et al.: 2012. Chemometric tools for NIRS and NIR Hyperspectral Imaging. Bulletin UASVM Agriculture, 69: 1. 70-76. J.A. Fernandez Pierna et al.: 2012. NIR Hyperspectral imaging ... Voir le document complet
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Joint Bayesian Hyperspectral Unmixing for change detection
... follows. In the Section 2, we present the proposed method for HS-CD by unmixing including the adopted Hierarchical Bayesian ...given in Section 3 demonstrating its validity and per- ...drawn in ... Voir le document complet
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Fluctuating target detection in fluctuating K-distributed clutter
... (22) In order to obtain the probability of detection, one must inte- grate over the ...of detection as a function of ...estimation in -distributed noise, the probability of detection of ... Voir le document complet
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Raman Hyperspectral Imaging: An essential tool in the pharmaceutical field
... studied in our laboratory was the quantitative detection of an impurity in a pharmaceutical formulation ...present in a very low dosage in the pharmaceutical products, consequently ... Voir le document complet
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Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization
... advocated, in particular for unmixing purposes [8]–[11]. Conversely, in remotely sensed images composed of vegetation ...explained in [18], many of these models only differ by the constraints imposed ... Voir le document complet
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