PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Detecting man-made structures and changes in satellite imagery with a content-based information retrieval system built on self-organizing maps
Matthieu Molinier, Jorma Laaksonen and Tuomas Häme
IEEE Transactions on Geoscience and Remote Sensing Volume 45, Number 4, pp. 861-874, 2007.


In this study, we extended the potential of a Content-Based Image Retrieval (CBIR) system based on Self-Organizing Maps (SOMs), for the analysis of remote sensing data. A database was artificially created by splitting each image to be analyzed into small images (or imagelets). Content-based image retrieval was applied to fully polarimetric airborne SAR data, using a selection of polarimetric features. After training the system on this imagelet database, automatic queries could detect changes. Results were encouraging on airborne SAR data and may be more useful for spaceborne polarimetric data.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
Learning/Statistics & Optimisation
Information Retrieval & Textual Information Access
ID Code:3635
Deposited By:Jorma Laaksonen
Deposited On:14 February 2008