论文信息 - Spectral unmixing based on improved extended support vector machines

Spectral unmixing based on improved extended support vector machines

Extended support vector machines (ESVM) was introduced recently for spectral unmixing. It models a class using a group of representative spectra to accommodate within class spectral variation. This paper presents a further geometry analysis of this method, and an improved ESVM is developed, which takes into account both within-class spectral variability and within each mixed case. The experiments illustrate that the new proposed algorithm can obtain more realistic unmixing results.

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