Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm

Gordo, O.; Martínez Izquierdo, María Estíbaliz; Gonzalo Martín, Consuelo y Arquero Hidalgo, Águeda (2011). Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm. "IEEE Latin America Transactions", v. 9 (n. 1); pp. 743-748. ISSN 1548-0992. https://doi.org/10.1109/TLA.2011.5876414.

Descripción

Título: Classification of Satellite Images by means of Fuzzy Rules generated by a Genetic Algorithm
Autor/es:
  • Gordo, O.
  • Martínez Izquierdo, María Estíbaliz
  • Gonzalo Martín, Consuelo
  • Arquero Hidalgo, Águeda
Tipo de Documento: Artículo
Título de Revista/Publicación: IEEE Latin America Transactions
Fecha: 2011
Volumen: 9
Materias:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Arquitectura y Tecnología de Sistemas Informáticos
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The data acquired by Remote Sensing systems allow obtaining thematic maps of the earth's surface, by means of the registered image classification. This implies the identification and categorization of all pixels into land cover classes. Traditionally, methods based on statistical parameters have been widely used, although they show some disadvantages. Nevertheless, some authors indicate that those methods based on artificial intelligence, may be a good alternative. Thus, fuzzy classifiers, which are based on Fuzzy Logic, include additional information in the classification process through based-rule systems. In this work, we propose the use of a genetic algorithm (GA) to select the optimal and minimum set of fuzzy rules to classify remotely sensed images. Input information of GA has been obtained through the training space determined by two uncorrelated spectral bands (2D scatter diagrams), which has been irregularly divided by five linguistic terms defined in each band. The proposed methodology has been applied to Landsat-TM images and it has showed that this set of rules provides a higher accuracy level in the classification process

Más información

ID de Registro: 11215
Identificador DC: http://oa.upm.es/11215/
Identificador OAI: oai:oa.upm.es:11215
Identificador DOI: 10.1109/TLA.2011.5876414
URL Oficial: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5876414&tag=1
Depositado por: Memoria Investigacion
Depositado el: 09 Jul 2012 09:03
Ultima Modificación: 20 Abr 2016 19:21
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