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000001742 084__ $$2WoS$$aEnvironmental Sciences
000001742 084__ $$2WoS$$aRemote Sensing
000001742 084__ $$2WoS$$aImaging Science & Photographic Technology
000001742 1001_ $$0P:(DE-Juel1)VDB4989$$aCanty, M. J.$$b0$$uFZJ
000001742 245__ $$aAutomatic radiometric normalization of multitemporal satellite imagery with the iteratively ie-weighted MAD transformation
000001742 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2008
000001742 300__ $$a1025 - 1036
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000001742 440_0 $$012722$$aRemote Sensing of Environment$$v112$$x0034-4257$$y3
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000001742 520__ $$aA recently proposed method for automatic radiometric normalization of multi- and hyperspectral imagery based on the invariance property of the Multivariate Alteration Detection (MAD) transfortnation and orthogonal linear regression is extended by using an iterative re-weighting scheme involving no-change probabilities. The procedure is first investigated with partly artificial data and then applied to multitemporal, multispectral satellite imagery. Substantial improvement over the previous method is obtained for scenes which exhibit a high proportion of change. (C) 2007 Elsevier Inc. All rights reserved.
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000001742 65320 $$2Author$$achange detection
000001742 65320 $$2Author$$amultispectral imagery
000001742 65320 $$2Author$$aiteratively reweighted multivariate alteration detection (IR-MAD)
000001742 65320 $$2Author$$acanonical correlation analysis (CCA)
000001742 65320 $$2Author$$aradiometric
000001742 7001_ $$0P:(DE-HGF)0$$aNielsen, A. A.$$b1
000001742 773__ $$0PERI:(DE-600)1498713-2$$a10.1016/j.rse.2007.07.013$$gVol. 112, p. 1025 - 1036$$p1025 - 1036$$q112<1025 - 1036$$tRemote sensing of environment$$v112$$x0034-4257$$y2008
000001742 8567_ $$uhttp://dx.doi.org/10.1016/j.rse.2007.07.013
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