- Several approaches for segmenting hyperspectral data and automatically detecting unusual objects in natural scenes are discussed. We demonstrate segmentations of hyperspectral imagery based on of the most significant principal components of the hyperspectral data cube. Several applications of the segmented data are treated. Digital morphological operations can be used to isolate segments that match target criteria. Alternatively, background segments can be used to define background endmembers; pixels that are quantitatively spectrally different from the background can then be designated. Analog morphological operations can then be used for clutter rejection and for the detection of objects of particular size and shape.