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Index Terms-Hyperspectral Images

A robust test for nonlinear mixture detection in hyperspectral images

A robust test for nonlinear mixture detection in hyperspectral images

... Index Terms — Nonlinearity detection, Hyperspectral images, Linear mixing ...tral images, such as those containing sand, trees or vegetation ...in images with relief such as ...

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Nonlinear unmixing of hyperspectral images based on multi-kernel learning

Nonlinear unmixing of hyperspectral images based on multi-kernel learning

... Index TermsHyperspectral image, nonlinear unmix- ing, multi-kernel learning ...sensed hyperspectral data, due to the relatively low spatial res- olution of ...identified, ...

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Nearest neighbor-density-based clustering methods for large hyperspectral images

Nearest neighbor-density-based clustering methods for large hyperspectral images

... kappa index of ...in terms of ACCR, and a similar behavior is observed for ModeSeek, knnClust-WM and GWENN-WM for the same value of ...in terms of ACCR, whereas it is worse than the latter in OCCR ...

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Matrix Cofactorization for Joint Unmixing and Classification of Hyperspectral Images

Matrix Cofactorization for Joint Unmixing and Classification of Hyperspectral Images

... Index Terms—supervised learning, spectral unmixing, cofac- torization, hyperspectral ...sensing images, many methods have been proposed to extract infor- mation from such specific ...of ...

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A robust test for nonlinear mixture detection in hyperspectral images

A robust test for nonlinear mixture detection in hyperspectral images

... This paper studies a pixel by pixel nonlinearity detector for hyper- spectral image analysis. The reflectances of linearly mixed pixels are assumed to be a linear combination of known pure spectral compo- nents ...

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Joint unmixing-deconvolution algorithms for hyperspectral images

Joint unmixing-deconvolution algorithms for hyperspectral images

... Index TermsHyperspectral image unmixing, hyperspectral image deconvolution, non-negative Tikhonov regularization ...of hyperspectral im- agers, the surface area covered by any pixel of ...

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A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

... Index TermsHyperspectral imagery, endmember vari- ability, image classification, Hamiltonian ...a hyperspectral (HS) image, known as endmembers, and of estimating the corresponding ...

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Unsupervised Nearest Neighbors Clustering with Application to Hyperspectral Images

Unsupervised Nearest Neighbors Clustering with Application to Hyperspectral Images

... (and stored) beforehand still remains quadratic in N (the number of pixels), which can severely lower its usage for large size images. In the particular domain of multivariate imagery ...

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Unmixing multitemporal hyperspectral images accounting for smooth and abrupt variations

Unmixing multitemporal hyperspectral images accounting for smooth and abrupt variations

... V. C ONCLUSION AND FUTURE WORK A Bayesian model has been introduced to simultaneously represent smooth and abrupt variations possibly affecting multitemporal hyper- spectral (MTHS) images. The proposed unmixing ...

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Pairwise Markov fields for segmentation in astronomical hyperspectral images

Pairwise Markov fields for segmentation in astronomical hyperspectral images

... [4] Figure 3: Results insights under low SNR for synthetic images. Red circles represent the ground truth (cf. Fig. 2a). • the four methods yield very close averaged error rates, providing for all of them less ...

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Online unmixing of multitemporal hyperspectral images accounting for spectral variability

Online unmixing of multitemporal hyperspectral images accounting for spectral variability

... Abstract— Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing a hyperspectral image and their relative abundance fractions in each ...the hyperspectral unmixing ...

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Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

... sensing images is richer than this simple state- ...conventional hyperspectral unmixing approach can leverage the spatial information to help for spectral ...

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Unmixing multitemporal hyperspectral images with variability: an online algorithm

Unmixing multitemporal hyperspectral images with variability: an online algorithm

... a hyperspectral image –referred to as endmem- bers – and their relative abundance fractions in each ...describe hyperspectral data ...several images acquired over the same area at different time ...

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Fusion of multispectral and hyperspectral images based on sparse representation

Fusion of multispectral and hyperspectral images based on sparse representation

... sensing images since they do not necessarily adapt to the nature of the observed ...observed images instead of using prede•ned bases generally improves signal representation ...

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Nonlinear unmixing of Hyperspectral images

Nonlinear unmixing of Hyperspectral images

... Supervised nonlinear spectral unmixing using a postnonlinear mixing model for hyperspectral imagery... Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mi[r] ...

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Robust nonnegative matrix factorization for nonlinear unmixing of hyperspectral images

Robust nonnegative matrix factorization for nonlinear unmixing of hyperspectral images

... First, to evaluate the relevance of the proposed rLMM and the accu- racy of the corresponding robust NMF algorithm, some simulations have been conducted on synthetic data. Four 64 × 64-pixel images composed of K = ...

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Robust nonnegative matrix factorization for nonlinear unmixing of hyperspectral images

Robust nonnegative matrix factorization for nonlinear unmixing of hyperspectral images

... from images using the nonlinear end- member extraction algorithm proposed in [18], denoted as Heylen’s algorithm in what ...in terms of global mean square error related to the the endmember ...

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Online unmixing of multitemporal hyperspectral images accounting for spectral variability

Online unmixing of multitemporal hyperspectral images accounting for spectral variability

... Abstract— Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing a hyperspectral image and their relative abundance fractions in each ...the hyperspectral unmixing ...

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Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

... orbital hyperspectral images, developing a non-linear algorithm to char- acterize the composition of magmatic rocks, with applications to the study of the Earth and ...resolution hyperspectral ...

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Unmixing multitemporal hyperspectral images accounting for smooth and abrupt variations

Unmixing multitemporal hyperspectral images accounting for smooth and abrupt variations

... a hyperspectral (HS) image – referred to as endmembers – and their abundance fractions within each pixel of the ...(MTHS) images. However, MTHS images, which are composed of images ...

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