Unsupervised Change Detection From Multichannel SAR Data by Markovian Data Fusion

In applications related to environmental monitoring and disaster management, multichannel synthetic aperture radar (SAR) data present a great potential, owing both to their insensitivity to atmospheric and Sun-illumination conditions and to the improved discrimination capability they may provide as...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 2009-07, Vol.47 (7), p.2114-2128
Hauptverfasser:	Moser, G., Serpico, S.B.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive optics Algorithms Applied geophysics Biomedical optical imaging Change detection Channels Condition monitoring Context modeling Data fusion Data integration Earth sciences Earth, ocean, space Exact sciences and technology expectation-maximization (EM) Frequency Internal geophysics Markov random fields Markov random fields (MRFs) Multichannel multichannel SAR Pixel Polarization Radar detection Studies Synthetic aperture radar synthetic aperture radar (SAR) Unmanned aerial vehicles
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