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[PDF] Top 20 Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery

Has 10000 "Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery" found on our website. Below are the top 20 most common "Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery".

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery

... S AND SAD S B ETWEEN E XTRACTED E NDMEMBERS AND L ABORATORY R EFLECTANCES FOR THE B AYESIAN , VCA, AND N-FINDR A LGORITHMS ...the endmember spectra in the observed scene and ... Voir le document complet

15

Relationships between nonlinear and space-variant linear models in hyperspectral image unmixing

Relationships between nonlinear and space-variant linear models in hyperspectral image unmixing

... variability and nonlinear mixtures are physically very different ...(usually linear) mixing model, while a general nonlinear mixing model is spatially ...based-model for the deviations from the LMM ... Voir le document complet

6

Non-linear unmixing of hyperspectral images using multiple-kernel self-organizing maps

Non-linear unmixing of hyperspectral images using multiple-kernel self-organizing maps

... the unmixing process, two initialisation tasks should be ...the unmixing process, as well as their number, should be ...an endmember extraction algorithm already proposed in the literature ... Voir le document complet

7

A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images

A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images

... light and the observed materials, implies that the observed spectra are mix- tures of several signatures corresponding to distinct ...Spectral unmixing then consists in identifying a limited number of ... Voir le document complet

15

Hyperspectral unmixing accounting for spatial correlations and endmember variability

Hyperspectral unmixing accounting for spatial correlations and endmember variability

... Terms— Hyperspectral imagery, endmember variability, image classification, Markov chain ...INTRODUCTION Unmixing hyperspectral (HS) images consists of decomposing a pixel spectrum into ... Voir le document complet

6

Contributions to Hyperspectral Unmixing

Contributions to Hyperspectral Unmixing

... mentioned unmixing algorithms have been used on synthesized and real datasets in different settings in order to be evaluated and compared with exist- ing state-of-the-art ...SAGA+ and ... Voir le document complet

149

Unmixing multitemporal hyperspectral images accounting for endmember variability

Unmixing multitemporal hyperspectral images accounting for endmember variability

... Engineering and Physical Sciences, Edinburgh, ...unsupervised Bayesian algorithm for unmixing successive hyperspectral images while accounting for temporal and spatial ... Voir le document complet

6

Bayesian algorithm for unsupervised unmixing of hyperspectral images using a post-nonlinear model

Bayesian algorithm for unsupervised unmixing of hyperspectral images using a post-nonlinear model

... constraints for the abundances and endmembers was included in the Bayesian framework through appropriate prior ...resulting joint posterior distribution and the number of parameters to ... Voir le document complet

6

A Bayesian model for joint unmixing and robust classification of hyperspectral image

A Bayesian model for joint unmixing and robust classification of hyperspectral image

... classification and spectral unmixing are two methods to extract information from hyperspectral ...hierarchical Bayesian model to perform simultaneously both analysis in order to ensure that ... Voir le document complet

6

Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

... nonlinear unmixing, such as [1] and those reviewed in [14], linear models continue to receive much ...are extraction-led and instead assume that the pure signatures are present, ... Voir le document complet

14

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image

... Abstract— Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or end- members) ... Voir le document complet

14

Hyperspectral unmixing accounting for spatial correlations and endmember variability

Hyperspectral unmixing accounting for spatial correlations and endmember variability

... Terms— Hyperspectral imagery, endmember variability, image classification, Markov chain ...INTRODUCTION Unmixing hyperspectral (HS) images consists of decomposing a pixel spectrum into ... Voir le document complet

5

A Bayesian model for joint unmixing and robust classification of hyperspectral image

A Bayesian model for joint unmixing and robust classification of hyperspectral image

... classification and spectral unmixing are two methods to extract information from hyperspectral ...hierarchical Bayesian model to perform simultaneously both analysis in order to ensure that ... Voir le document complet

7

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image

Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image

... Abstract— Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or end- members) ... Voir le document complet

13

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

... As hyperspectral images contain rich spectral information, many unmixing methods focus on exploiting it and often neglect the spatial ...common endmember matrix [2], ...the extraction ... Voir le document complet

14

Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

Toward a Sparse Bayesian Markov Random Field Approach to Hyperspectral Unmixing and Classification

... powerful Bayesian hyperspectral unmixing algorithms can be significantly improved by incorporating the inherent local spatial correlations between pixel class labels via the use of Markov random ... Voir le document complet

15

Joint unmixing-deconvolution algorithms for hyperspectral images

Joint unmixing-deconvolution algorithms for hyperspectral images

... the linear mixing model which is the one adopted in this ...models and a comprehensive treatment of different non-linear mixing models and resulting non-linear unmixing ... Voir le document complet

6

Residual Component Analysis of Hyperspectral Images - Application to Joint Nonlinear Unmixing and Nonlinearity Detection

Residual Component Analysis of Hyperspectral Images - Application to Joint Nonlinear Unmixing and Nonlinearity Detection

... hierarchical Bayesian algorithm for joint linear/nonlinear spectral unmixing of hyperspectral images and nonlinearity ...a linear or nonlinear mixture of endmembers ... Voir le document complet

12

Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

... per endmember is included in the data ...a linear combination of some points is included in the simplex, issued from these points; as a consequence extreme points of the simplex correspond to ...is ... Voir le document complet

18

Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery

Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery

... 3 endmember spectra obtained by the N-FINDR ...3) for the pixel ...algorithm for the pure materials are represented in ...samples for each pixel, according to the MMSE ...map and by ... Voir le document complet

12

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