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An extension of Independent Component Analysis (ICA) to the situation when the mixture of signals is contaminated by multiplicative noise is proposed in this paper. The ICA methods search for the most independent output after a linear transformation of the data vector. If the ICA model is followed by these data, the result of this search is the inverse of the unknown mixture. On the other hand, if...
In this contribution, the relation between the principal components of the covariance matrix of a hyperspectral image and the spectra of the endmembers is studied. When the data satisfy the spectral mixing model, from this relation the spectra of the endmembers and the abundance of each endmember in the pixels of the image can be theoretically obtained through a non-lineal minimization process. The...
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