Abstract
The increasing amount and resolution of satellite sensors demand new techniques for browsing remote sensing image archives. Content-based querying allows an efficient retrieval of images based on the information they contain, rather than their acquisition date or geographical extent. Self-organizing maps (SOMs) have been successfully applied in the PicSOM system to content-based image retrieval in databases of conventional images. In this paper, we investigate and extend the potential of PicSOM for the analysis of remote sensing data. We propose methods for detecting man-made structures, as well as supervised and unsupervised change detection, based on the same framework. In this paper, a database was artificially created by splitting each satellite image to be analyzed into small images. After training the PicSOM on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes between two very high resolution images from different years. Experimental results were both evaluated quantitatively and discussed qualitatively, and suggest that this new approach is suitable for analyzing very high resolution optical satellite imagery. Possible applications of this work include interactive detection of man-made structures or supervised monitoring of sensitive sites.
| Original language | English |
|---|---|
| Pages (from-to) | 861-874 |
| Journal | IEEE Transactions on Geoscience and Remote Sensing |
| Volume | 45 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Apr 2007 |
| MoE publication type | A1 Journal article-refereed |
Fingerprint
Keywords
- Change detection
- Content-based information retrieval
- High-resolution optical satellite images
- Man-made structure detection
- Self-organizing maps (SOMs)
Cite this
}
Detecting man-made structures and changes in satellite imagery with a content-based information retrieval system built on self-organizing maps. / Molinier, Matthieu; Laaksonen, Jorma; Häme, Tuomas.
In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 4, 01.04.2007, p. 861-874.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - Detecting man-made structures and changes in satellite imagery with a content-based information retrieval system built on self-organizing maps
AU - Molinier, Matthieu
AU - Laaksonen, Jorma
AU - Häme, Tuomas
PY - 2007/4/1
Y1 - 2007/4/1
N2 - The increasing amount and resolution of satellite sensors demand new techniques for browsing remote sensing image archives. Content-based querying allows an efficient retrieval of images based on the information they contain, rather than their acquisition date or geographical extent. Self-organizing maps (SOMs) have been successfully applied in the PicSOM system to content-based image retrieval in databases of conventional images. In this paper, we investigate and extend the potential of PicSOM for the analysis of remote sensing data. We propose methods for detecting man-made structures, as well as supervised and unsupervised change detection, based on the same framework. In this paper, a database was artificially created by splitting each satellite image to be analyzed into small images. After training the PicSOM on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes between two very high resolution images from different years. Experimental results were both evaluated quantitatively and discussed qualitatively, and suggest that this new approach is suitable for analyzing very high resolution optical satellite imagery. Possible applications of this work include interactive detection of man-made structures or supervised monitoring of sensitive sites.
AB - The increasing amount and resolution of satellite sensors demand new techniques for browsing remote sensing image archives. Content-based querying allows an efficient retrieval of images based on the information they contain, rather than their acquisition date or geographical extent. Self-organizing maps (SOMs) have been successfully applied in the PicSOM system to content-based image retrieval in databases of conventional images. In this paper, we investigate and extend the potential of PicSOM for the analysis of remote sensing data. We propose methods for detecting man-made structures, as well as supervised and unsupervised change detection, based on the same framework. In this paper, a database was artificially created by splitting each satellite image to be analyzed into small images. After training the PicSOM on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes between two very high resolution images from different years. Experimental results were both evaluated quantitatively and discussed qualitatively, and suggest that this new approach is suitable for analyzing very high resolution optical satellite imagery. Possible applications of this work include interactive detection of man-made structures or supervised monitoring of sensitive sites.
KW - Change detection
KW - Content-based information retrieval
KW - High-resolution optical satellite images
KW - Man-made structure detection
KW - Self-organizing maps (SOMs)
UR - http://www.scopus.com/inward/record.url?scp=33947677651&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2006.890580
DO - 10.1109/TGRS.2006.890580
M3 - Article
VL - 45
SP - 861
EP - 874
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
SN - 0196-2892
IS - 4
ER -