SAR-based terrain classification using weakly supervised hierarchical Markov aspect models

We introduce the hierarchical Markov aspect model (HMAM), a computationally efficient graphical model for densely labeling large remote sensing images with their underlying terrain classes. HMAM resolves local ambiguities efficiently by combining the benefits of quadtree representations and aspect m...

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 21(2012), 9 vom: 07. Sept., Seite 4232-43
1. Verfasser:	Yang, Wen (VerfasserIn)
Weitere Verfasser:	Dai, Dengxin, Triggs, Bill, Xia, Gui-Song
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2012
Zugriff auf das übergeordnete Werk:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't