@ARTICLE\{IMM2012-06005,
    author       = "M. J. Canty and A. A. Nielsen",
    title        = "Linear and kernel methods for multivariate change detection",
    year         = "2012",
    keywords     = "CUDA; {ENVI}; {IDL}; {IR-MAD}; iMAD; kPCA; kMAF; kMNF; Matlab; Radiometric Normalization; Remote Sensing; Multi-resolution",
    pages        = "107-114",
    journal      = "Computers and Geosciences",
    volume       = "38",
    editor       = "",
    number       = "1",
    publisher    = "Elsevier",
    note         = "For Matlab code see http://www.imm.dtu.dk/pubdb/p.php?4695 and http://www.imm.dtu.dk/pubdb/p.php?5925. For {ENVI}/{IDL} and Python code see Mort Canty's homepage.",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/6005-full.html",
    abstract     = "The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsupervised change detection in multi- and hyper-spectral remote sensing imagery as well as for automatic radiometric normalization of multitemporal image sequences. Principal components analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of {IR-MAD} images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. {IDL} (Interactive Data Language) implementations of {IR-MAD,} automatic radiometric normalization and kernel {PCA}/MAF/{MNF} transformations are presented which function as transparent and fully integrated extensions of the {ENVI} remote sensing image analysis environment. Matlab code is also available which allows for fast data xploration and experimentation with smaller datasets. New, multi-resolution versions of {IR-MAD} which accelerate convergence and which further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed to run on massively parallel {CUDA-}enabled graphics processors, when available, giving an order of magnitude enhancement in computational speed. The software is available from the authors' websites.",
    isbn_issn    = "doi:10.1016/j.cageo.2011.05.012"
}