Observatorio de I+D+i UPM

Memorias de investigación
Book chapters:
: Multiscale object-based classification of satellite images merging multispectral information with panchromatic textural features
Year:2012
Research Areas
  • Remote sensing,
  • Image processing
Information
Abstract
Once admitted the advantages of object-based classification compared to pixel-based classification; the need of simple and affordable methods to define and characterize objects to be classified, appears. This paper presents a new methodology for the identification and characterization of objects at different scales, through the integration of spectral information provided by the multispectral image, and textural information from the corresponding panchromatic image. In this way, it has defined a set of objects that yields a simplified representation of the information contained in the two source images. These objects can be characterized by different attributes that allow discriminating between different spectral&textural patterns. This methodology facilitates information processing, from a conceptual and computational point of view. Thus the vectors of attributes defined can be used directly as training pattern input for certain classifiers, as for example artificial neural networks. Growing Cell Structures have been used to classify the merged information
International
Si
Book Edition
Book Publishing
Universidad Técnica de Praga
ISBN
978-80-01-04868-9
Series
Book title
Remote Sensing and Geoinformation not only for Scientific Cooperation
From page
394
To page
400
Participants
  • Autor: Consuelo Gonzalo Martin (UPM)
  • Autor: Mario Fernando Lillo Saavedra (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Informática Aplicada al Procesado de Señal e Imagen
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)