A. Bhattacharya
Indexing satellite images with features computed from man-made structures on the Earth’s surface
Bhattacharya, A.; Roux, M.; Maitre, H.; Jermyn, I.H.; Descombes, X.; Zerubia, J.
Authors
Abstract
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database.
Citation
Bhattacharya, A., Roux, M., Maitre, H., Jermyn, I., Descombes, X., & Zerubia, J. (2007). Indexing satellite images with features computed from man-made structures on the Earth’s surface. In 2007 International Workshop on Content-Based Multimedia Indexing ; proceedings (244-250). https://doi.org/10.1109/cbmi.2007.385418
Conference Name | 2007 International Workshop on Content-Based Multimedia Indexing |
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Conference Location | Bordeaux |
Publication Date | Jun 1, 2007 |
Deposit Date | Aug 12, 2011 |
Publicly Available Date | Apr 20, 2016 |
Pages | 244-250 |
Series ISSN | 1949-3983 |
Book Title | 2007 International Workshop on Content-Based Multimedia Indexing ; proceedings. |
ISBN | 142441010X3 |
DOI | https://doi.org/10.1109/cbmi.2007.385418 |
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© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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