Oct 28, 2011 · In this paper the problem of semisupervised hyper spectral unmixing is considered. More specifically, the unmixing process is formulated as ...
sparse. In this paper, a novel hierarchical Bayesian approach for semisupervised hyperspectral unmixing is presented, which is based on the sparsity ...
Experimental results on both synthetic and real hyperspectral data illustrate that the proposed method converges fast, favors sparsity in the abun dances' ...
In this paper the problem of semisupervised hyper spectral unmixing is considered. More specifically, the unmixing process is formulated as a linear ...
In this paper the problem of semisupervised hyperspectral unmixing is considered. More specifically, the unmixing process is formulated as a linear ...
TL;DR: Two novel unmixing algorithms are introduced in an attempt to exploit both spatial correlation and sparse representation of pixels lying in the ...
In this paper a novel hierarchical Bayesian model for sparse semi-supervised hyperspectral unmixing is presented. Adopting the sparsity hypothesis and ...
Missing: Approach | Show results with:Approach
In this paper the problem of semisupervised hyperspectral unmixing is considered. More specifically, the unmixing process is formulated as a linear ...
In this paper the problem of semisupervised hyper spectral unmixing is considered. More specifically, the unmixing process is formulated as a linear ...
In this paper, a novel hierarchical Bayesian model is presented, which is based on the sparsity hypothesis and non-negativity prop- erty of the abundance vector ...