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000053329 084__ $$2WoS$$aRemote Sensing
000053329 084__ $$2WoS$$aImaging Science & Photographic Technology
000053329 1001_ $$0P:(DE-Juel1)VDB4989$$aCanty, M. J.$$b0$$uFZJ
000053329 245__ $$aVisualization and unsupervised classification of changes in multispectral satellite imagery
000053329 260__ $$aLondon$$bTaylor & Francis$$c2006
000053329 300__ $$a3961 - 3975
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000053329 440_0 $$02845$$aInternational Journal of Remote Sensing$$v27$$x0143-1161$$y18
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000053329 520__ $$aThe statistical techniques of multivariate alteration detection, minimum/maximum autocorrelation factors transformation, expectation maximization and probabilistic label relaxation are combined in a unified scheme to visualize and to classify changes in multispectral satellite data. The methods are demonstrated with an example involving bitemporal LANDSAT TM imagery.
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000053329 7001_ $$0P:(DE-HGF)0$$aNielsen, A. A.$$b1
000053329 773__ $$0PERI:(DE-600)1497529-4$$a10.1080/01431160500222608$$gVol. 27, p. 3961 - 3975$$p3961 - 3975$$q27<3961 - 3975$$tInternational journal of remote sensing$$v27$$x0143-1161$$y2006
000053329 8567_ $$uhttp://dx.doi.org/10.1080/01431160500222608
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