Abstract
Self-Organising Maps (SOMs) have been successfully applied to
content-based image retrieval (CBIR). In this study, we investigate the
potential of PicSOM, an image database browsing system, applied to
quad-polarised ALOS PALSAR images. Databases of small images were artificially
created, either from a single satellite image for object detection, or two
satellite images when considering change detection. Polarimetric features were
extracted from the images to allow image indexing. By querying the databases,
it was possible to detect target classes, as well as changes between the two
images. Results open a full range of applications, from structure detection to
change detection, to be embedded in a same operative system. The framework
may be particularly suitable for long-term monitoring of strategic sites.
Original language | English |
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Title of host publication | Proceedings of ESA-EUSC Symposium 2008 – WPP-278 |
Number of pages | 8 |
Edition | cd-rom |
Publication status | Published - 2008 |
MoE publication type | Not Eligible |
Keywords
- content-based information retrieval
- self-organising maps
- high resolution satellite images
- polarimetric spaceborne SAR
- change detection