Continuum fusion: a new methodology for creating hyperspectral detection algorithms

A new formalism has been developed for producing detection algorithms in model-based problems, in which one or more parameter values is unknown. Continuum fusion can be used to generate different flavors of algorithm for any composite hypothesis testing problem. The method is defined by a fusion logic that can be translated into a set of partial differential relations. However, some important hyperspectral models can be solved with purely geometrical means, one of which is described. The new methodology affords a new interpretation of the orthodox solution, the generalized likelihood ratio test, which is revealed as but one point in a spectrum of fusion methods.