@CONFERENCE\{IMM2012-06282,
    author       = "A. A. Nielsen and J. S. Vestergaard",
    title        = "Parameter optimization in the regularized kernel minimum noise fraction transformation",
    year         = "2012",
    month        = "jul",
    pages        = "370-373",
    booktitle    = "{IEEE} {IGARSS}",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "Munich, Germany",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/6282-full.html",
    abstract     = "This contribution gives a simple method for finding optimal parameters in a regularized version of the recently suggested kernel minimum noise fraction (kMNF) transformation. The method considers the model signal-to-noise ratio (SNR) as a function of the kernel parameter(s) and the regularization parameter. In a grid search we find the parameters that maximize the model {SNR}. The method is succesfully demonstrated on a remote sensing change detection example with data from the {DLR} {3K} camera system covering a busy motorway. In this example no regularization is chosen and the optimized choice for the kernel parameter gives much better {SNR} than the default choice."
}