A relevance feedback method based on genetic programming for classification of remote sensing images
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 learn...
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Veröffentlicht in: | Information sciences 2011-07, Vol.181 (13), p.2671-2684 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | 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. |
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ISSN: | 0020-0255 1872-6291 |
DOI: | 10.1016/j.ins.2010.02.003 |