@ARTICLE\{IMM2004-02815,
    author       = "M. J. Canty and A. A. Nielsen and M. Schmidt",
    title        = "Automatic Radiometric Normalization of Multitemporal Satellite Imagery",
    year         = "2004",
    month        = "jun",
    pages        = "441-451",
    journal      = "Remote Sensing of Environment",
    volume       = "91",
    editor       = "",
    number       = "3-4",
    publisher    = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/2815-full.html",
    abstract     = "The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat {TM} images over Nevada, Landsat {ETM}+ images over Morocco, and {SPOT} {HRV} images over Kenya. Results from this new automatic, combined {MAD}/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features.",
    isbn_issn    = "DOI:10.1016/j.rse.2003.10.024"
}