21st Signal Processing and Communications Applications Conference (SIU), CYPRUS, 24 - 26 April 2013
In the cases that the spatial resolution of the hyperspectral data is not sufficient, pixel vectors are expressed in terms of abundances of pure signatures, named as endmembers, with spectral mixture analysis. Most of the endmember extraction methods use only the spectral information, whereas spatial preprocessing methods can increase the performance by directing the endmember extraction process to spatially homogeneous regions. However, this approach results in a failure in detecting anomaly endmembers. In this paper, a two-way approach which provides high performance by directing the endmember extraction process to both anomalies and spatially homogenous regions is proposed.