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[PDF] Top 20 Hyperspectral image unmixing with LiDAR data-aided spatial regularization

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Hyperspectral image unmixing with LiDAR data-aided spatial regularization

Hyperspectral image unmixing with LiDAR data-aided spatial regularization

... simulated hyperspectral image and simulated LiDAR ...the hyperspectral image, M = 5 endmember spectra have been randomly selected from the USGS spectral library (see ...The ... Voir le document complet

25

Spatial regularization for nonlinear unmixing of hyperspectral data with vector-valued kernel functions

Spatial regularization for nonlinear unmixing of hyperspectral data with vector-valued kernel functions

... incorporating spatial regularization into a nonlinear unmixing procedure dedicated to hyperspectral ...The spatial regularizer and the nonlinear contributions are jointly mod- eled by a ... Voir le document complet

7

Spatial regularization for nonlinear unmixing of hyperspectral data with vector-valued kernel functions

Spatial regularization for nonlinear unmixing of hyperspectral data with vector-valued kernel functions

... incorporating spatial regularization into a nonlinear unmixing procedure dedicated to hyperspectral ...The spatial regularizer and the nonlinear contributions are jointly mod- eled by a ... Voir le document complet

6

Improved Local Spectral Unmixing of hyperspectral data using an algorithmic regularization path for collaborative sparse regression

Improved Local Spectral Unmixing of hyperspectral data using an algorithmic regularization path for collaborative sparse regression

... Spectral Unmixing (LSU) is a technique in which the unmixing is performed in local regions of the image, instead of a whole ...the unmixing locally were using sliding windows [9, ...an ... Voir le document complet

6

Hyperspectral Image Unmixing with Endmember Bundles and Group Sparsity Inducing Mixed Norms

Hyperspectral Image Unmixing with Endmember Bundles and Group Sparsity Inducing Mixed Norms

... EALING WITH SPECTRAL VARIABILITY WITH ENDMEMBER BUNDLES ...the image data is a procedure whose goal is to obtain various instances of each endmember, still in a blind unmixing ...the ... Voir le document complet

17

Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex Geometry

Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex Geometry

... Note that all the discussion of this section applies only to the noiseless case. The study [21] defines the concept of Minimum Volume Enclosing Simplex (MVES) as the largest simplex (in terms of its volume [46]) which ... Voir le document complet

16

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

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

... spectral unmixing are two methods to extract information from hyperspectral ...a spatial regularization through a Potts-Markov potential and also includes a local potential induced by the ... Voir le document complet

7

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

Matrix cofactorization for joint spatial-spectral unmixing of hyperspectral images

... — Hyperspectral unmixing aims at identifying a set of elementary spectra and the corresponding mixture coefficients for each pixel of an ...introduce spatial information to complement the spectral ... Voir le document complet

14

Hyperspectral image unmixing using a multiresolution sticky HDP

Hyperspectral image unmixing using a multiresolution sticky HDP

... constrained unmixing (SCU) algorithm that simultaneously segments the image into disparate abundance regions and performs ...model with different parameters, thus the nonnegativity and sum-to-one ... Voir le document complet

17

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) with their corresponding ... Voir le document complet

14

Contributions to unsupervised and nonlinear unmixing of hyperspectral data

Contributions to unsupervised and nonlinear unmixing of hyperspectral data

... Spectral unmixing has been an active field of research since the earliest days of hyper- spectral remote ...concerned with the case where various materials are found in the spatial extent of a pixel, ... Voir le document complet

166

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) with their corresponding ... Voir le document complet

13

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

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

... spectral unmixing are two methods to extract information from hyperspectral ...a spatial regularization through a Potts-Markov potential and also includes a local potential induced by the ... Voir le document complet

6

Nonlinear unmixing of hyperspectral data with partially linear least-squares support vector regression

Nonlinear unmixing of hyperspectral data with partially linear least-squares support vector regression

... nonlinear unmixing [6, 12, ...Furthermore, spatial cor- relation is also considered by a local regularization term which does not introduce extra computational ...kernel unmixing work [6, ... Voir le document complet

6

Enhancing hyperspectral image unmixing with spatial correlations

Enhancing hyperspectral image unmixing with spatial correlations

... spectral image unmixing. Most unmixing algorithms proposed in the literature do not take into account the possible spatial correlations between the ...The image to be unmixed is assumed ... Voir le document complet

10

LiDAR-driven spatial regularization for hyperspectral unmixing

LiDAR-driven spatial regularization for hyperspectral unmixing

... of spatial regulariza- tions consists in not properly preserving the edges between homogeneous areas, even when using total variation (TV)- like ...The spatial regularization for these pixels can be ... Voir le document complet

5

LiDAR-driven spatial regularization for hyperspectral unmixing

LiDAR-driven spatial regularization for hyperspectral unmixing

... (a) (b) Fig. 1: SIM1: (a) Synthetic DSM. (b) Color composition of the synthetic hyperspectral data. no-weight performs poorly compared to other methods incor- porating DSM information. In particular, RMSE ... Voir le document complet

6

Modeling spatial and temporal variabilities in hyperspectral image unmixing

Modeling spatial and temporal variabilities in hyperspectral image unmixing

... Linear unmixing of hyperspectral images Whereas traditional red / green / blue and multispectral images are composed of a few spectral channels (from three to tens), hyperspectral (HS) images are ... Voir le document complet

191

Spectral-spatial rotation forest for hyperspectral image classification

Spectral-spatial rotation forest for hyperspectral image classification

... and data transformation techniques to improve both the diversity and accuracy of base ...considers data transforma- tion on spectral ...spectral-spatial data trans- formation into RoF and thus ... Voir le document complet

5

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

... the hyperspectral unmixing algorithms proposed in the signal & image processing and geoscience literatures rely on the commonly admitted linear mixing model (LMM), Y ≈ ... Voir le document complet

11

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