@CONFERENCE{rozell.04b,
  author = {Rozell, C.J. and Manolakis, D.},
  title = {Matched filter performance for unequal target and background covariance matrices},
  booktitle = {Proceedings of the SPIE Defense and Security Symposium: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X},
  year = {2004},
  address = {Orlando, FL},
  month = {April},
  pages = {109--117},
  abstract = {Detection of military and civilian targets from
	 airborne platforms using hyperspectral imaging (HSI) sensors is of
	 great interest. Relative to multispectral sensing, hyperspectral
	 sensing can increase the detectability of targets by exploiting finer
	 detail in spectral signatures. A multitude of adaptive detection
	 algorithms have appeared in the literature or have found their way into
	 software packages and end-user systems. The most widely known among them
	 is the linear matched filter. However, despite its popularity, the
	 fact that the matched filter is used under conditions that deviate
	 from the implicit optimality assumptions has not been investigated.},
}