Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48689
Title: Bayesian segmentation and clustering for determining cloud mask images
Authors: Barreto, D.
Murtagh, F.
Marcello, J. 
UNESCO Clasification: 250616 Teledetección (Geología)
Keywords: Bayes factor
multiband image
Markov model
Gaussian mixture model
Segmentation, et al
Issue Date: 2002
Journal: Proceedings of SPIE - The International Society for Optical Engineering 
Conference: Opto-Ireland 2002: Optical metrology, Imaging, and Machine Vision 
Abstract: We assess both marginal density clustering, and spatial clustering using a Markov random field, on multiband Earth observation data. We use a Bayes factor assessment procedure in all cases. We find that the spatial model leads to better results, although the non-spatial clustering achieves a better false alarm rate.
URI: http://hdl.handle.net/10553/48689
ISSN: 0277-786X
DOI: 10.1117/12.463768
Source: Proceedings of SPIE - The International Society for Optical Engineering[ISSN 0277-786X],v. 4877, p. 144-155
Appears in Collections:Actas de congresos
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