Hyperspectral expert classifier based on data fusion technique

In this paper a Hyperspectral Expert Classifier (HEC) based on data-fusion technique was presented. The spectral-spatial contextual image analysis approaches were applied on hyperspectral images, ETM+ images, and GIS data. First, the samples were selected according to the available information to build the reference spectral and calculate the maximum angle after data fusion. The created maps using Spectral Angle Mapping (SAM), GIS data, hyperspectral image, and ETM+ images were used as an input data in HEC. The result showed that the Land-use in the study area could be identified from Hyperion data efficiently. The hyperspectral expert classifier approach is found to have a merit of high classification precision, low computational cost, and without much interference from the users compared with other classifiers. This methodology could easily extended to a large number of classes and used in practical applications (for example mine exploration).