@article {aCalderero12,
	title = {Multispectral Cooperative Partition Sequence Fusion for Joint Classification and Hierarchical Segmentation},
	journal = {Geoscience and Remote Sensing Letters, IEEE},
	volume = {9},
	year = {2012},
	pages = {1012-1016},
	abstract = {<p>In this letter, a region-based fusion methodology is presented for joint classification and hierarchical segmentation of specific ground cover classes from high-spatial-resolution remote sensing images. Multispectral information is fused at the partition level using nonlinear techniques, which allows the different relevance of the various bands to be fully exploited. A hierarchical segmentation is performed for each individual band, and the ensuing segmentation results are fused in an iterative and cooperative way. At each iteration, a consensus partition is obtained based on information theory and is combined with a specific ground cover classification. Here, the proposed approach is applied to the extraction and segmentation of vegetation areas. The result is a hierarchy of partitions with the most relevant information of the vegetation areas at different levels of resolution. This system has been tested for vegetation analysis in high-spatial-resolution images from the QuickBird and GeoEye satellites.</p>},
	keywords = {GeoEye satellite, geophysical image processing, geophysical techniques, ground cover classification, hierarchical segmentation, high-spatial-resolution remote sensing images, image classification, image fusion, image region analysis, Image segmentation, information fusion, information theory, joint classification, Joints, Merging, multispectral cooperative partition sequence fusion, multispectral images, multispectral information, nonlinear techniques, partition level, QuickBird satellite, region merging, region-based fusion methodology, Remote sensing, Spatial resolution, specific ground cover classes, Vegetation mapping},
	issn = {1545-598X},
	doi = {10.1109/LGRS.2012.2188776},
	author = {Calderero, F. and F. Eugenio and Marcello, J. and Marqu{\'e}s, F.}
}
