Mar 8, 2010 · This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called ...

Feb 4, 2022 · Abstract—This paper studies a new Bayesian unmixing algo- rithm for hyperspectral images. Each pixel of the image is modeled as a linear ...

This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called ...

Tourneret, "Bayesian Estimation of Linear Mixtures Using the Normal Compositional Model. Application to Hyperspectral Imagery," in IEEE Transactions on ...

This paper proposes to estimate the mixture coefficients (referred to as abundances) using a Bayesian algorithm. Suitable priors are assigned to the ...

We consider Bayesian analysis of data from multivariate linear regression models whose errors have a distribution that is a scale mixture of normals. Such ...

Bayesian estimation of linear mixtures using the normal compositional model: application to hyperspectral imagery. IEEE Transactions on Image Processing. (2010).

Bayesian Estimation of Linear Mixtures Using the Normal Compositional Model. Application to Hyperspectral Imagery · Computer Science, Environmental Science. IEEE ...

In this paper, we study a new Bayesian approach for the analysis of linearly mixed structures. In particular, we consider the case of hyperspectral images, ...

Oct 26, 2016 · ABSTRACT. This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing accounting for endmember variability.