A relevance feedback method based on genetic programming for classification of remote sensing images

Authors:
J. A. dos Santos;C. D. Ferreira;R. da S. Torres;M. A. Gonçalves;R. A. C. Lamparelli
Affiliations:
Institute of Computing, University of Campinas, Campinas, SP, Brazil;Institute of Computing, University of Campinas, Campinas, SP, Brazil;Institute of Computing, University of Campinas, Campinas, SP, Brazil;Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil;Center for Research in Agriculture, University of Campinas, Campinas, SP, Brazil
Venue:
Information Sciences: an International Journal
Year:
2011

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Abstract

This paper presents an interactive technique for remote sensing image classification. In our proposal, users are able to interact with the classification system, indicating regions of interest (and those which are not). This feedback information is employed by a genetic programming approach to learning user preferences and combining image region descriptors that encode spectral and texture properties. Experiments demonstrate that the proposed method is effective for image classification tasks and outperforms the traditional MaxVer method.