Caracterización multiescala de objetos como herramienta para la clasificación de imágenes de alta resolución espacial

Gonzalo Martín, Consuelo and Lillo Saavedra, Mario Fernando (2012). Caracterización multiescala de objetos como herramienta para la clasificación de imágenes de alta resolución espacial. "Revista de Teledetección : Revista de la Asociación Española de Teledetección", v. 38 (n. 2); pp. 19-27. ISSN 1988-8740.

Description

Title: Caracterización multiescala de objetos como herramienta para la clasificación de imágenes de alta resolución espacial
Author/s:
  • Gonzalo Martín, Consuelo
  • Lillo Saavedra, Mario Fernando
Item Type: Article
Título de Revista/Publicación: Revista de Teledetección : Revista de la Asociación Española de Teledetección
Date: December 2012
ISSN: 1988-8740
Volume: 38
Subjects:
Freetext Keywords: Object attributes, OBIA, object-based classification, Wavelet coefficients, segmentation, atributos de objetos, OBIA, clasificación basada en objetos, coeficientes Wavelet, segmentación.
Faculty: Facultad de Informática (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper presents a new methodology, simple and affordable, for the definition and characterization of objects at different scales in high spatial resolution images. The objects have been generated by integrating texturally and spectrally homogeneous segments. The former have been obtained from the segmentation of Wavelet coefficients of the panchromatic image. The multi-scale character of this transform has yielded texturally homogeneous segments of different sizes for each of the scales. The spectrally homogeneous segments have been obtained by segmenting the classified corresponding multispectral image. In this way, it has been defined a set of objects characterized by different attributes, which give to the objects a semantic meaning, allowing to determine the similarities and differences between them. To demonstrate the capabilities of the methodology proposed, different experiments of unsupervised classification of a Quickbird image have been carried out, using different subsets of attributes and 1-D ascendant hierarchical classifier. Obtained results have shown the capability of the proposed methodology for separating semantic objects at different scales, as well as, its advantages against pixel-based image interpretation.

More information

Item ID: 16215
DC Identifier: http://oa.upm.es/16215/
OAI Identifier: oai:oa.upm.es:16215
Official URL: http://www.aet.org.es/?q=revista38-4
Deposited by: Memoria Investigacion
Deposited on: 05 Jul 2013 14:03
Last Modified: 21 Apr 2016 16:32
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