Classification-based vehicle detection in high-resolution satellite images
| Autor: | Line Eikvil, Lars Aurdal, Hans Koren |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
business.industry
Computer science Multispectral image Process (computing) High resolution Atomic and Molecular Physics and Optics Computer Science Applications Panchromatic film Vehicle detection Clutter Computer vision Segmentation Satellite Artificial intelligence Computers in Earth Sciences business Engineering (miscellaneous) Remote sensing |
| Zdroj: | ISPRS Journal of Photogrammetry and Remote Sensing. 64:65-72 |
| ISSN: | 0924-2716 |
| DOI: | 10.1016/j.isprsjprs.2008.09.005 |
| Popis: | In this study, we have looked into the problem of vehicle detection in high-resolution satellite images. Based on the input from the local road authorities, we have focused not only on highways, but also on inner city roads, where more clutter is expected. The study site is the city of Oslo, Norway. To do vehicle detection in these areas, we propose an automatic approach, consisting of a segmentation step, followed by two stages of object classification. In the process, we utilize multispectral images, panchromatic images and a road network. The approach has been tested on Quickbird images, and the results that are obtained have been compared with manual counts and classifications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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