A Nagao-Matsuyama approach to high-resolution satellite image classification

A knowledge-based, hierarchical, unsupervised classification scheme for high-resolution multispectral satellite (HRMS) images is described. This scheme, which finds its conceptual bases in the work of Nagao and Matsuyama for structural analysis of aerial photographs, introduces a new filtering algor...

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Veröffentlicht in:	IEEE transactions on geoscience and remote sensing 1994-07, Vol.32 (4), p.749-758
Hauptverfasser:	Baraldi, A., Parmiggiani, F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Areal geology. Maps Earth sciences Earth, ocean, space Exact sciences and technology Filtering algorithms Focusing Geologic maps, cartography Human resource management Image analysis Image classification Image sensors Remote sensing Satellite broadcasting Soils Spatial resolution Surficial geology
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Beschreibung
Zusammenfassung:	A knowledge-based, hierarchical, unsupervised classification scheme for high-resolution multispectral satellite (HRMS) images is described. This scheme, which finds its conceptual bases in the work of Nagao and Matsuyama for structural analysis of aerial photographs, introduces a new filtering algorithm which is able to preserve fine linear structures of the image. An example of the application of this classification scheme to a Landsat Thematic Mapper multispectral image is presented.< >
ISSN:	0196-2892 1558-0644
DOI:	10.1109/36.298004