A self-organizing map framework for detection of man-made structures and changes in satellite imagery

Matthieu Molinier*, Jorma Laaksonen, Tuomas Häme

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    Content-based querying allows efficient retrieval of images based on the information they contain, rather than acquisition date or geographical extent. We extend the potential of a content-based image retrieval (CBIR) system based on Self-Organizing Maps (SOMs), to the analysis of remote sensing data. A database was artificially created by splitting each satellite image to be analyzed into small images. After training the CBIR system on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes. Experimental results suggest that this new approach is suitable for analyzing very high-resolution optical satellite imagery. Possible applications include interactive detection of man-made structures and supervised monitoring of sensitive sites.

    Original languageEnglish
    Title of host publication2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
    Pages53 - 56
    Number of pages4
    DOIs
    Publication statusPublished - 1 Dec 2006
    MoE publication typeA4 Article in a conference publication
    Event2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States
    Duration: 31 Jul 20064 Aug 2006

    Conference

    Conference2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
    Abbreviated titleIGARSS 2006
    Country/TerritoryUnited States
    CityDenver, CO
    Period31/07/064/08/06

    Keywords

    • Change detection
    • Self-Organizing Maps

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