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Gonzalo Martín, Consuelo and Lillo Saavedra, Mario Fernando (2011). Multiscale object-based classification of satellite images merging multispectral information with panchromatic textural features. In: "31st EARSeL Symposium and 35th General Assembly 2011", 30/05/2011 - 02/06/2011, Praga, República Checa. pp. 394-400.
Title: | Multiscale object-based classification of satellite images merging multispectral information with panchromatic textural features |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 31st EARSeL Symposium and 35th General Assembly 2011 |
Event Dates: | 30/05/2011 - 02/06/2011 |
Event Location: | Praga, República Checa |
Title of Book: | Proceedings of 31st EARSeL Symposium and 35th General Assembly 2011 |
Date: | 2011 |
Subjects: | |
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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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.
Item ID: | 12749 |
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DC Identifier: | https://oa.upm.es/12749/ |
OAI Identifier: | oai:oa.upm.es:12749 |
Official URL: | http://www.conferences.earsel.org/abstract/show/22... |
Deposited by: | Memoria Investigacion |
Deposited on: | 13 Dec 2012 18:24 |
Last Modified: | 21 Apr 2016 12:01 |