Hierarchical segmentation of vegetation areas in high spatial resolution images by fusion of multispectral information
Visualitza/Obre
10.1109/IGARSS.2009.5417329
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/9494
Tipus de documentText en actes de congrés
Data publicació2009
Condicions d'accésAccés obert
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Abstract
A new region-based methodology for the automated extraction and
hierarchical segmentation of vegetation areas into high spatial
resolution images is proposed. This approach is based on the
iterative and cooperative fusion of the independent segmentation
results of equal or different resolution spectral bands, combined
with an unsupervised classification into vegetation and novegetation
regions. The result is a hierarchy of partitions with most
relevant information at different levels of resolution of the
vegetation areas. In addition, the high flexibility of the scheme
allows different configurations depending on the final purpose. For
instance, considering the size of the vegetation areas into the
hierarchy, or prioritizing the information into the high resolution
panchromatic band to improve the accuracy of both vegetation
extraction and segmentation. This general tool for vegetation
analysis is tested into high spatial resolution images from IKONOS
and QuickBird satellites.
CitacióCalderero, F. [et al.]. Hierarchical segmentation of vegetation areas in high spatial resolution images by fusion of multispectral information. A: IEEE International Geoscience and Remote Sensing Symposium. "2009 IEEE International Geoscience and Remote Sensing Symposium". 2009, p. 232-235.
ISBN978-1-4244-3394-0
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HierachicalSegmentation.pdf | 887,4Kb | Visualitza/Obre |