PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Self-Organizing Map Framework for Detection of Man-Made Structures and Changes in Satellite Imagery
Matthieu Molinier, Jorma Laaksonen and Tuomas Häme
In: IEEE International Geoscience And Remote Sensing Symposium, 31 Jul - 4 Aug 2006, Denver, Colorado.

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.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Information Retrieval & Textual Information Access
ID Code:2586
Deposited By:Jorma Laaksonen
Deposited On:14 February 2008