@CONFERENCE\{IMM2015-06882,
    author       = "A. A. Nielsen and A. Müller",
    title        = "Optimal Iterated Two-Class Separation in Hyperspectral Data",
    year         = "2015",
    month        = "apr",
    booktitle    = "9th EARSeL {SIG} Imaging Spectroscopy workshop",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    note         = "See also: Allan A. Nielsen and Andreas Müller (2012). Optimal class separation in hyperspectral image data: iterated canonical discriminant analysis, Third Annual Hyperspectral Imaging Conference (HSI), Rome, Italy, 15-16 May 2012. http://www.imm.dtu.dk/pubdb/p.php?6273.",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/6882-full.html",
    abstract     = "This paper gives an iterated extension of canonical discriminant analysis for separation between two groups or classes in multi- or hypervariate data.  We show that the iterative extension greatly enhances the separation between classes in a case with 110-band HyMap data covering part of the Sokolov mining area in the Czech Republic where we separate water from {''}every thing else'."
}