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Estimating abundance fraction of materials in hyperspectral images is an important area of study in the field of remote sensing. The need for fraction estimation in remotely sensed images arises from the fact that the sampling distance is generally larger than the size of the targets of interest. The abundance sum-to-one constraint and the abundance nonnegativity constraint are the two physical constraints...
Nonlinear spectral mixture analysis for hyperspectral imagery is investigated without prior information about the image scene. A simple but effective nonlinear mixture model is adopted, where the multiplication of each pair of endmembers results in a virtual endmember representing multiple scattering effect during pixel construction process. The analysis is followed by linear unmixing for abundance...
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