@CONFERENCE\{IMM2012-06273,
    author       = "A. A. Nielsen and A. Müller",
    title        = "Optimal class separation in hyperspectral image data: iterated canonical discriminant analysis",
    year         = "2012",
    month        = "may",
    pages        = "64-67",
    booktitle    = "Third Annual Hyperspectral Imaging Conference",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "Instituto Nazionale di Geofisica e Vulcanologia",
    organization = "",
    address      = "{INGV,} Rome, Italy",
    note         = "Matlab code is provided in zip file. - The sentence {''}This method is in itself a univariate version of {CDA''} in page 65 makes no sense.",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/6273-full.html",
    abstract     = "This paper describes canonical discriminant analysis and sketches an iterative version which is then applied to obtain optimal separation between a region, here examplified by either “water” or “wood/trees” and the rest of a HyMap image. We show that the iterative version greatly enhances the separation between the regions."
}