Attribute profiles on derived features for urban land cover classification

Bharath Bhushan Damodaran 1 Joachim Höhle 2 Sébastien Lefèvre 1
1 OBELIX - Environment observation with complex imagery
UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This research deals with the automatic generation of 2D land cover maps of urban areas using very high resolution multispectral aerial imagery. The appropriate selection of classifier and attributes is important to achieve high thematic accuracies. In this paper, new attributes are generated to increase the discriminative power of auxiliary information provided by remote sensing images. The generated attributes are derived from the vegetation index and elevation information using morphological attribute profiles. The extended experimental evaluation and comparison of attribute profile-based mapping solutions is conducted to derive the optimal combinations of attributes required for classification and to understand the genericity of attributes on a range of classifiers, i.e., various combinations of attributes and classifiers. Experimental results with two high resolution images show that the proposed attributes derived on auxiliary information outperform the existing attribute profiles computed on original image and its principal components.
Type de document :
Article dans une revue
Photogrammetric engineering and remote sensing, Asprs American Society for Photogrammetry and, 2017
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https://hal.archives-ouvertes.fr/hal-01447454
Contributeur : Sébastien Lefèvre <>
Soumis le : jeudi 26 janvier 2017 - 20:39:29
Dernière modification le : vendredi 7 avril 2017 - 10:13:12

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  • HAL Id : hal-01447454, version 1

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Bharath Bhushan Damodaran, Joachim Höhle, Sébastien Lefèvre. Attribute profiles on derived features for urban land cover classification. Photogrammetric engineering and remote sensing, Asprs American Society for Photogrammetry and, 2017. <hal-01447454>

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