Segmentation of multiband imagery using minimum spanning trees

We present a new technique for the automatic segmentation of multiband imagery. Our approach is based on the computation of a minimum spanning tree over a graph derived from the image. We use a fast graph-search algorithm and a custom tree-splitting algorithm to provide a high level of performance. This approach captures some of the gestalt characteristics of human perceptual grouping and is easily adaptable to a variety of spectral and spatial criteria. We demonstrate our technique on multispectral and hyperspectral imagery of the earth's surface.