• Aucun résultat trouvé

[PDF] Top 20 A Bayesian model for joint unmixing and robust classification of hyperspectral image

Has 10000 "A Bayesian model for joint unmixing and robust classification of hyperspectral image" found on our website. Below are the top 20 most common "A Bayesian model for joint unmixing and robust classification of hyperspectral image".

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

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

... Terms— Bayesian model, Markov random Field, super- vised learning, image ...INTRODUCTION Hyperspectral images are mainly interpreted via two widely used techniques, namely spectral ... 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

... Terms— Bayesian model, Markov random Field, super- vised learning, image ...INTRODUCTION Hyperspectral images are mainly interpreted via two widely used techniques, namely spectral ... Voir le document complet

7

A Bayesian model for joint unmixing, clustering and classification of hyperspectral data

A Bayesian model for joint unmixing, clustering and classification of hyperspectral data

... pen A rchive T oulouse A rchive O uverte (OATAO) OATAO is an open access repository that collects the work of some Toulouse researchers and makes it freely available over the web where ... Voir le document complet

31

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

... that a model similar to (2) was implicitly assumed in [21]–[23], where a single-band image acquired by scanning transmission electron microscopy is linearly unmixed by the principal component ... 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

... way of defining MRFs is applied to the joint unmixing and segmentation algorithm of ...After a pre- processing step defining the similarity regions, an implicit ... Voir le document complet

13

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

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

... 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

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

... b and w, the joint prior distri- bution of the θ can be expressed as f (θ) = f (Z)f (M)f (σ 2 )f (b|σ b 2 , w)f (σ 2 b )f ...expressions for the standard Bayesian estimators associated ... 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

... 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 ... Voir le document complet

14

Enhancing hyperspectral image unmixing with spatial correlations

Enhancing hyperspectral image unmixing with spatial correlations

... new unmixing strategy studied in this paper assumes that the hyperspectral image to be analyzed is partitioned into ho- mogeneous regions (or classes) in which the abundance vectors have the same ... Voir le document complet

10

A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

... Terms— Hyperspectral imagery, endmember vari- ability, image classification, Hamiltonian ...Spectral unmixing (SU) consists of decomposing a pixel spec- trum as a linear ... Voir le document complet

6

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery

Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery

... The Bayesian model studied in this paper uses a Gibbs sam- pling algorithm to efficiently solve the constrained spectral un- mixing problem without requiring the presence of pure pixels in the ... Voir le document complet

15

A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

A new Bayesian unmixing algorithm for hyperspectral images mitigating endmember variability

... Terms— Hyperspectral imagery, endmember vari- ability, image classification, Hamiltonian ...Spectral unmixing (SU) consists of decomposing a pixel spec- trum as a linear ... Voir le document complet

7

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 ... Voir le document complet

15

Joint Bayesian Hyperspectral Unmixing for change detection

Joint Bayesian Hyperspectral Unmixing for change detection

... variation of HSIs for CD. The authors of [4] have proposed a Linear Mixture Model for endmember and abundance estimation of each image ...vectors and ... Voir le document complet

6

Joint Bayesian Hyperspectral Unmixing for change detection

Joint Bayesian Hyperspectral Unmixing for change detection

... The joint poste- rior distribution of the vector {θ, ω} can be expressed as f( θ , ω |Y , α, β) ∝ f(Y | θ )f ( θ ...structure of the proposed model allows one to integrate out the ... Voir le document complet

5

Hyperspectral image unmixing with LiDAR data-aided spatial regularization

Hyperspectral image unmixing with LiDAR data-aided spatial regularization

... proposed a general framework to incorporate external DSM information into spa- tially regularized spectral unmixing ...maps and was exploited to weight the spatial regularization ...performances ... Voir le document complet

25

Modeling spatial and temporal variabilities in hyperspectral image unmixing

Modeling spatial and temporal variabilities in hyperspectral image unmixing

... hundreds of contiguous spectral bands, hyperspectral (HS) images have received an increasing interest due to the significant spectral information they convey about the materials present in a given ... Voir le document complet

191

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

... line of investigation concerns the rele- vance of lifting the nonnegative constraint on the outlier term ...majority of which assume the nonlinearity term to be ...may model shadow effects ... Voir le document complet

11

A classwise supervised ordering approach for morphology based hyperspectral image classification

A classwise supervised ordering approach for morphology based hyperspectral image classification

... Institue of Automation, Beijing, China Abstract We present a new method for the spectral-spatial classification of hyperspectral images, by means of morphological features ... Voir le document complet

5

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

... case of the ...each of the parameters M, A and R in ...value of the other parameters and such that the objective function is ...non-convexity of the objective function J ... Voir le document complet

12

Show all 10000 documents...