6533b834fe1ef96bd129d46e
RESEARCH PRODUCT
SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
Aissam BekkariDriss MammassGaëtan Le GoïcHanan AnzidAlamin Mansourisubject
010504 meteorology & atmospheric sciencesContextual image classificationComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesHigh resolutionPattern recognition02 engineering and technologySpace (commercial competition)01 natural sciencesSupport vector machineSatelliteArtificial intelligencebusiness021101 geological & geomatics engineering0105 earth and related environmental sciencesdescription
Remote-sensing focusing on image classification knows a large progress and receives the attention of the remote-sensing community day by day. Combining many kinds of extracted features has been successfully applied to High resolution urban satellite images using support vector machine (SVM). In this paper, we present a methodology that is promoting a performed classification by using pixel-wise SURF description features combined with spectral information in Cielab space for the first time on common scenes of urban imagery. The proposed method gives a promising classification accuracy when compared with the two types of features used separately.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-10-24 | Proceedings of the 12th International Conference on Intelligent Systems: Theories and Applications |