An efficient algorithm for endmember selection is illustrated. Endmembers are estimated by an unsupervised segmentation procedure based on spectral analysis. Preliminary results obtained on experimental data are presented and discussed
International audienceIn this letter, an eigenvalue-based empirical method is proposed in order to e...
This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing, accounting ...
International audienceThis paper presents an unsupervised Bayesian algorithm for hyperspectral image...
Hyperspectral imaging is an active area of research in Earth and planetary observation. One of the m...
Spectral unmixing in hyperspectral images involves determining endmembers and their associated abund...
In this paper, we present an unsupervised classification algorithm for hyperspectral images. For red...
Abstract Hyperspectral imaging is an active area of re-search in Earth and planetary observation. On...
Hyperspectral imagery is a new class of image data which is mainly used in remote sensing. It is cha...
Abstract—Spectral unmixing is an important task in hyperspec-tral data exploitation. It amounts to e...
In this paper, we try to identify and quantify the chemical species present on the surface of planet...
Spectral unmixing is an important technique for hyperspectral data exploitation, in which a mixed sp...
During the last years, several high-resolution sensors have been developed for hyperspectral remote ...
Abstract—In this letter, an eigenvalue-based empirical method is proposed in order to estimate the n...
This dissertation investigates two issues of finding endmembers which have been overlooked in the pa...
Over the last decade, several algorithms have been devel-oped for automatic or semi-automatic extrac...
International audienceIn this letter, an eigenvalue-based empirical method is proposed in order to e...
This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing, accounting ...
International audienceThis paper presents an unsupervised Bayesian algorithm for hyperspectral image...
Hyperspectral imaging is an active area of research in Earth and planetary observation. One of the m...
Spectral unmixing in hyperspectral images involves determining endmembers and their associated abund...
In this paper, we present an unsupervised classification algorithm for hyperspectral images. For red...
Abstract Hyperspectral imaging is an active area of re-search in Earth and planetary observation. On...
Hyperspectral imagery is a new class of image data which is mainly used in remote sensing. It is cha...
Abstract—Spectral unmixing is an important task in hyperspec-tral data exploitation. It amounts to e...
In this paper, we try to identify and quantify the chemical species present on the surface of planet...
Spectral unmixing is an important technique for hyperspectral data exploitation, in which a mixed sp...
During the last years, several high-resolution sensors have been developed for hyperspectral remote ...
Abstract—In this letter, an eigenvalue-based empirical method is proposed in order to estimate the n...
This dissertation investigates two issues of finding endmembers which have been overlooked in the pa...
Over the last decade, several algorithms have been devel-oped for automatic or semi-automatic extrac...
International audienceIn this letter, an eigenvalue-based empirical method is proposed in order to e...
This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing, accounting ...
International audienceThis paper presents an unsupervised Bayesian algorithm for hyperspectral image...
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