Results 161 to 170 of about 835 (219)

Mapping heavy mineral deposits on the coast of the state of Rio Grande do Sul (Brazil) using orbital and proximal remote sensing. [PDF]

PLoS One
Prates Hallal G, de Almeida Espinoza JM, Veettil BK, Porcher CC, Oliveira Righi da Silva M, Beatriz Alves Rolim S.   +5 more
europepmc   +1 more source

A tale of two planets: Disparate evolutionary models for Mars inferred from radiogenic isotope compositions of Martian meteorites. [PDF]

Proc Natl Acad Sci U S A
Borg LE, Kruijer TS.
europepmc   +1 more source

Crystal structure and doping in synthetic enstatite: an analysis of Li/Fe³⁺-doped single-crystal samples. [PDF]

Acta Crystallogr B Struct Sci Cryst Eng Mater
Ballirano P, Celata B, Pacella A, Bloise A, Bosi F.   +4 more
europepmc   +1 more source

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Sampling Piecewise Convex Unmixing and Endmember Extraction

IEEE Transactions on Geoscience and Remote Sensing, 2013
A Metropolis-within-Gibbs sampler for piecewise convex hyperspectral unmixing and endmember extraction is presented. The standard linear mixing model used for hyperspectral unmixing assumes that hyperspectral data reside in a single convex region. However, hyperspectral data are often nonconvex.
Alina Zare, Paul Gader
exaly   +2 more sources

Endmember extraction analysis considering endmember variability

2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2013
In recent years, several kinds of endmember extraction algorithms have been proposed from hyperspectral data set which extracts/selects one single standard endmember spectrum for each existing endmember class or scene component. In this article, endmember variability is considered to the mixture spectrum analysis by representing each endmember by a set
Mingming Xu 0001, Liangpei Zhang 0001, Bo Du 0001   +2 more
openaire   +1 more source

Spatial Preprocessing for Endmember Extraction

IEEE Transactions on Geoscience and Remote Sensing, 2009
Endmember extraction is the process of selecting a collection of pure signature spectra of the materials present in a remotely sensed hyperspectral scene. These pure signatures are then used to decompose the scene into abundance fractions by means of a spectral unmixing algorithm. Most techniques available in the endmember extraction literature rely on
Maciel Zortea, Antonio Plaza
openaire   +1 more source

Improving the quality of extracted endmembers

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009
Endmember extraction for spectral mixture analysis is a necessary step when endmember information is unknown. If endmembers are assumed to be pure pixels present in an image scene, endmember extraction is to search the most distinctive pixels. Popular algorithms using the criteria of simplex volume maximization (e.g., N-FINDR) and spectral signature ...
Qian Du 0001, Liangpei Zhang 0001, Nareenart Raksuntorn   +2 more
openaire   +1 more source

Spectral-textural endmember extraction

2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2010
Several available techniques for endmember extraction and spectral unmixing use only the spectral information contained in the hyperspectral data. In this paper, we introduce a novel method for spatial-spectral endmember extraction which incorporates texture features in the quantification of spatial information (jointly with spectral information ...
Maciel Zortea, Devis Tuia, Fabio Pacifici, Antonio J. Plaza   +3 more
openaire   +1 more source

Sparse endmember extraction and demixing

2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
A novel algorithm for endmember extraction is presented. The approach follows the linear mixture model for hyperspectral data. Endmembers are identified based on sparsity consideration. Theoretical and experimental results suggest the potential of the method.
Martin Ehler, Matthew J. Hirn
openaire   +2 more sources