SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
Authors: 
Hanan Anzid, Gaetan Le Goic, Aissam Bekkari, Alamin Mansouri, Driss MammassAuthors Info & Claims
Hanan Anzid, Gaetan Le Goic, Aissam Bekkari, Alamin Mansouri, Driss MammassAuthors Info & ClaimsArticle No.: 2, Pages 1 - 5
Abstract
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.
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Index Terms
- SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
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Information & Contributors
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Published In
October 2018
301 pages
ISBN:9781450364621
DOI:10.1145/3289402
- Conference Chairs:
- Abdelaziz Berrado,
- Zohra Bakkoury,
- Program Chairs:
- Bernadette Bouchon-Meunier,
- Mohammed Ramdani
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Published: 24 October 2018
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