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000017745 084__ $$2WoS$$aComputer Science, Interdisciplinary Applications
000017745 084__ $$2WoS$$aGeosciences, Multidisciplinary
000017745 1001_ $$0P:(DE-Juel1)VDB4989$$aCanty, M. J.$$b0$$uFZJ
000017745 245__ $$aLinear and Kernel Methods for Multivariate Change Detection
000017745 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2012
000017745 300__ $$a107 - 114
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000017745 520__ $$aThe iteratively reweighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsupervised change detection in multi- and hyperspectral remote sensing imagery and 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 that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that 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' Web sites. (C) 2011 Elsevier Ltd. All rights reserved.
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000017745 65320 $$2Author$$aIR-MAD
000017745 65320 $$2Author$$aiMAD
000017745 65320 $$2Author$$aKernel methods
000017745 65320 $$2Author$$aMatlab
000017745 65320 $$2Author$$aRadiometric normalization
000017745 65320 $$2Author$$aRemote sensing
000017745 65320 $$2Author$$aMultiresolution
000017745 7001_ $$0P:(DE-HGF)0$$aNielsen, A.A.$$b1
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000017745 8567_ $$uhttp://dx.doi.org/10.1016/j.cageo.2011.05.012
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