Land-Cover Mapping by Markov Modeling of Spatial-Contextual Information in Very-High-Resolution Remote Sensing Images

Markov models represent a wide and general family of stochastic models for the temporal and spatial dependence properties associated to 1-D and multidimensional random sequences or random fields. Their applications range over a wide variety of subareas of the information and communication technology...

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Bibliographic Details
Published in:Proceedings of the IEEE 2013-03, Vol.101 (3), p.631-651
Main Authors: Moser, Gabriele, Serpico, Sebastiano B., Benediktsson, Jon Atli
Format: Article
Language:English
Subjects:
Computational modeling
Data fusion
Focusing
Image classification
Image segmentation
Land cover
land-cover mapping
Mapping
Markov models
Markov processes
Markov random fields
Mathematical models
Remote sensing
remote sensing image classification
Spatial resolution
Speech processing
Stochastic models
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Summary:Markov models represent a wide and general family of stochastic models for the temporal and spatial dependence properties associated to 1-D and multidimensional random sequences or random fields. Their applications range over a wide variety of subareas of the information and communication technology (ICT) field, including networking, automation, speech processing, genomic-sequence analysis, or image processing. Focusing on the applicative problem of land-cover mapping from very-high-resolution (VHR) remote sensing images, which is a relevant problem in many applications of environmental monitoring and natural resource exploitation, Markov models convey a great potential, thanks to their capability to effectively describe and incorporate the spatial information associated with image data into an image-classification process. In this framework, the main ideas and previous work about Markov modeling for VHR image classification will be recalled in this paper and processing results obtained through recent methods proposed by the authors will be discussed.
ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2012.2211551