Edge detection on hyperspectral imagery via Manifold techniques

For hyperspectral imagery, the term “spectral edge” has not been clearly defined because of the complexity of the high dimensional properties in spectral space. In this paper, a new definition of the spectral edge is presented based on a data-driven mathematic approach Manifold Learning. It considers both the spectral features in spectral space and the discontinuity of image function in image space. Experimental analysis using EO-1 hyperspectral imagery shows that the spectral edge based method has desired performance to describe the edge contours in the hyperspectral imagery.