Classification of hyperspectral ROSIS data from urban areas

Classification of high-resolution hyperspectral ROSIS 03 (Reflective Optics System Imaging Spectrometer) data based on extended morphological profiles is considered. For classification of high-resolution panchromatic data, simple morphological profiles are constructed with a repeated use of morphological opening and closing operators with a structuring element of increasing size, starting with the original panchromatic image. In order to apply the morphological approach to hyperspectral data, principal components of the hyperspectral imagery are computed. The most significant principal components are used as base images for an extended morphological profile, i.e., a profile based on more than one original image. The extended morphological profiles arc used as inputs to a neural network classifier. In experiments, two hyperspectral data sets from an urban area in Pavia, Italy are classified.