User-defined information and scientific performance evaluation
John R. Hoffman, Ronald Mahler, Tim R. Zajic · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
For the past two years at this conference we have described results in the practical implementation of a unified, scientific approach to performance measurement for data fusion algorithms. Our approach is based on finite set statistics (FISST), a generalization of conventional statistics to multisource, multitarget problems. Finite-set statistics makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems in such a way that information can be defined and measured even though any given end-user may have conflicting or even subjective definitions of what information means. In this follow-on paper we describe the performance of FISST based metrics that take into account a user's definition of information and develop a rigorous theory of partial information for multisource, multi-target problems.